Asia Faculty Summit 2014

About

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The Asia Faculty Summit 2014 is organized by Microsoft Research Asia and conducted in partnership with Tsinghua University. The event will be held in Beijing, China, from October 30 to 31, 2014. The summit brings together hundreds of leading academic researchers, educators, and Microsoft researchers to discuss topics related to the theme “Computing in Science.” Cross-disciplinary collaborations in research and education will be addressed and explored, as well as how academia and computer science students can be better equipped to work with other disciplines in data-intensive sciences.

Featured speakers

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Jining Chen

President,
Tsinghua University

Kap-Young Jeong

President,
Yonsei University

Takeo Kanade

Professor,
Carnegie Mellon University

Butler W. Lampson

Technical Fellow, Microsoft Research

Christos H. Papadimitriou

Professor,
UC Berkeley

Jeannette Wing

Corporate Vice President,
Microsoft Research

Andrew Yao

Professor,
Tsinghua University

General chairs

hsiao-wuen-hon90x130 andrew_chi-chih-yao90x130
Hsiao-Wuen Hon

Chairman,
Microsoft
Asia-Pacific
R&D Group |
Managing Director,
Microsoft
Research Asia

Andrew Yao

Professor,
Tsinghua
University

Program chairs

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Tim Pan

University
Relations
Director,
Microsoft
Research Asia

Ming Zhou

Principal
Researcher,
Microsoft
Research Asia

Agenda

Thursday, October 30, 2014

Time Session Speaker Location 
8:45–8:50 Welcome Speech Jining Chen, President, Tsinghua University Lecture Hall,
Main Building,
Tsinghua University
 

8:50–9:00

 

Welcome and Microsoft Research Asia Update slides | video

 

Hsiao-Wuen Hon, Chairman, Microsoft Asia-Pacific R&D Group | Managing Director, Microsoft Research Asia

 

9:00–9:10

 

Group Photo

 

9:10–9:50

 

Computational Thinking
in the Sciences and Beyond
 slides | video

 

Jeannette Wing, Corporate Vice President, Microsoft Research

9:50–10:30  

The Demand for New
Knowledge and Interdisciplinary Education
at Yonsei University

| slides | video

Kap-Young Jeong, President, Yonsei University
 

10:30-10:50

 

Break

10:50–12:00 Panel Discussion
Fostering Interdisciplinary Talents | video
Moderator: Tim Pan, University Relations Director, Microsoft Research Asia

Panelists:

  • Peng Gong, Tsinghua University
  • Kap-Young Jeong, Yonsei University
  • David S. Rosenblum, National University of Singapore | slides
  • Jeannette Wing, Microsoft Research
12:00–13:00 Lunch Break
 

13:00–13:40

 

Computer Vision: New
and Renewed Opportunities
  | video

 

Takeo Kanade, Professor, Carnegie Mellon University

13:40–14:20  

Hints and Principles for Computer System Design
 | slides | video

Butler W. Lampson, Technical Fellow, Microsoft Research
14:20–15:00  

Computational Ideas and
the Theory of Evolution

slides | video

 

Christos H. Papadimitriou, Professor, UC Berkeley

 

15:00–15:30

 

Break

15:30–16:10  

Interdisciplinarity: A View
from Theoretical Computer Science
 | slides | video

Andrew Yao, Professor, Tsinghua University
16:10–17:10 Panel Discussion

Interdisciplinarity: The
Future of Computer Science?
 | video

 

Moderator: Thomas Moscibroda, Senior Researcher, Microsoft Research Asia | Chair Professor, Tsinghua University

Panelists:

  • Takeo Kanade, Carnegie Mellon University
  • Butler W. Lampson, Microsoft Research
  • Christos H. Papadimitriou, UC Berkeley
  • Andrew Yao, Tsinghua University
 

17:10–17:30

 

Microsoft Research
Outreach and Closing Remarks

 

P. Anandan, Distinguished Scientist, Managing Director, Microsoft Research Outreach

 

17:30–18:30

 

Transit to Hotel

18:30–20:30 Banquet Ballroom,
Beijing Beichen InterContinental Hotel

 

Friday, October 31, 2014

Time Session Speaker Location
8:45–12:30 Urban Science in the Cloud Chair: Winnie Cui, Microsoft Research Asia Conference Room 1409,
Tower 1, Microsoft Beijing West Campus
 

8:45–8:50

 

Opening

 

Winnie Cui, Microsoft Research Asia

 

8:50–9:20

 

Urban Computing: Using Big Data
to Solve Urban Challenges

 

Yu Zheng, Microsoft Research Asia

 

9:20–9:45

 

Real-Time Urban Travel Time
Prediction Using KNN and Online
Traffic Simulator in the Microsoft
Cloud System

 

Hwasoo Yeo, Korea Advanced Institute of Science and Technology

 

9:45–10:10

 

Enabling Causality-Based Air Quality Monitoring with Urban Big Data

 

Victor Li, The University of Hong Kong

 

10:10–10:20

 

Q&A

 

10:20–10:30

 

Break

 

10:30–10:55

 

To Feel the City’s Pulse with Mobile
Crowd Sensing

 

Yanmin Zhu, Shanghai Jiao Tong University

 

10:55–11:20

 

Environmental Modeling and
Visualization System for Eco-Friendly Behavior in Urban Traffics

 

Takeshi Oishi, The University Of Tokyo

 

11:20–11:45

 

Build Smart Campus Based on Human Behavioral Data

 

Guangzhong Sun, University of Science and Technology of China

 

11:45–12:15

 

Deploying Connected Devices for Research

 

Arjmand Samuel, Microsoft Research

 

12:15–12:30

 

Q&A

 

8:45–12:30

 

Computing in Science

 

Chair: Miran Lee, Microsoft Research Asia

 

Conference Room 1103,
Tower 1, Microsoft Beijing West Campus

 

8:45–8:50

 

Opening

 

Miran Lee, Microsoft Research Asia

 

8:50–9:20

 

Biodiversity Monitoring Based on Cloud Environment and Citizen Science

 

Zheping Xu, Chinese Academy of Sciences

 

9:20–9:50

 

Visual Analysis of Topic Coopetition
on Social Media

 

Tai-Quan Peng, Nanyang Technological University

 

9:50–10:20

 

Collaborative Exercitation of
Geography Course Supported by
Geospatial Service Web

 

Huayi Wu, Wuhan University

 

10:20–10:30

 

Break

 

10:30–11:00

 

DigSee: Text Mining for Identifying
Disease-Gene-Biological Events
Relationships

 

Hyunju Lee, Gwangju Institute of Science and Technology

 

11:00–11:30

 

Social Media Mining with Machine
Learning Methods

 

Jun Zhu, Tsinghua University

 

11:30–12:30

 

The Power of Azure Machine Learning

 

Junsheng Hao, Shanghai Yungoal Info Tech Co., Ltd.

 

8:45–12:30

 

New Age of Interaction:
Computer and Human

 

Chair: Noboru Kuno, Microsoft Research Asia

 

MPR,
Tower 1, Microsoft Beijing West Campus

 

8:45–8:50

 

Opening

 

Noboru Kuno, Microsoft Research Asia

 

8:50–9:20

 

Visual-Haptic Interactive Telepresence

 

Jeha Ryu, Gwangju Institute of Science and Technology

Sangyoun Lee, Yonsei University

 

9:20–9:50

 

Whole-Body Haptic Interaction

 

Hiroyuki Kajimoto, University of Electro-Communications

 

9:50–10:20

 

Using Kinect to Study the Role of Hand Gestures During Conversations

 

Hao-Chuan Wang, National Tsing Hua University

 

10:20–10:30

 

Break

10:30–11:00 Building Communication Bridges for
Chinese Minority Ethnic Languages:
An Efficient Translation Framework
Based on Microsoft Translator Hub
Conghui Zhu, Harbin Institute of Technology
 

11:00–11:30

 

Speaker Support: Activity-Based Tools
for Presentation Authoring and
Language Learning

 

Darren Edge, Microsoft Research Asia

 

11:30–12:00

 

Office Mix: Online Lessons Made Simple

 

Kangping Liu, Microsoft Research Asia

 

12:00–12:30

 

The Software and Data Challenges of Games
for Coding

 

Judith Bishop, Microsoft Research

12:30–14:00 Lunch and DemoFest Reception Area
Tower 1, Microsoft Beijing West Campus
 

14:00–16:00

 

Microsoft Research Asia Open House

Have you ever wondered what goes on inside Microsoft Research Asia? We sincerely invite all Asia Faculty Summit guests to Microsoft Research Asia Open House events. Events will be organized by research areas with talks and demos.

 

Multimedia and User Interface

 

Chair: Baining Guo, Microsoft Research Asia

 

MPR,
Tower 1, Microsoft Beijing West Campus

 

14:00–14:10

 

Welcome and Overview

 

Baining Guo, Microsoft Research Asia

 

14:10–14:30

 

Virtualize Everything

 

Shipeng Li, Microsoft Research Asia

 

14:30–14:50

 

Embracing Cloud Media

 

Wenjun Zeng, Microsoft Research Asia

 

14:50–15:10

 

Recent Graphics Research in Microsoft
Research Asia

 

Xin Tong, Microsoft Research Asia

 

15:10–15:30

 

Toward Human-Level Performance on
Face Understanding

 

Jian Sun, Microsoft Research Asia

 

15:30–15:50

 

A Glimpse of Several Multimodal
Interaction Technologies

 

Qiang Huo, Microsoft Research Asia

 

15:50–16:10

 

Haptics at the Fingertips

 

Hong Tan, Microsoft Research Asia

 

Machine Learning, Knowledge
Mining, and Machine
Comprehension of Text

 

Chair: Wei-Ying Ma, Microsoft Research Asia

 

Conference Room 1103,
Tower 1, Microsoft Beijing West Campus

 

14:00–14:20

 

Welcome and Overview

 

Wei-Ying Ma, Microsoft Research Asia

 

14:20–14:35

 

Deep Information Extraction and Entity Extraction

 

Zaiqing Nie, Microsoft Research Asia

 

14:35–14:50

 

Learning Word Embedding from Big
Text Data

 

Bin Gao, Microsoft Research Asia

 

14:50–15:05

 

Knowledge Embedding

 

Jianwen Zhang, Microsoft Research Asia

 

15:05–15:20

 

Graph Computation

 

Bin Shao, Microsoft Research Asia

 

15:20–15:40

 

Natural Language Computing

 

Ming Zhou, Microsoft Research Asia

 

15:40–15:55

 

Q&A

 

Systems and IOT

 

Chair: Feng Zhao, Microsoft Research Asia

 

Conference Room 1409,
Tower 1, Microsoft Beijing West Campus

 

14:00–14:05

 

Welcome and Overview

 

Feng Zhao, Microsoft Research Asia

 

14:05–14:30

 

Incentive Networks

 

Thomas Moscibroda, Microsoft Research Asia

 

14:30–14:55

 

Mobile App Development: Contextual
Fuzzing

 

Mike Liang, Microsoft Research Asia

 

14:55–15:20

 

Cloud Scheduling: Apollo

 

Ming Wu, Microsoft Research Asia

 

15:20–15:45

 

Software Analytics: DriverMine

 

Shi Han, Microsoft Research Asia

 

15:45–16:00

 

Q&A

 

Speakers

P. Anandan

P. Anandan has been the managing director of Microsoft Research India since its inception in 2005. Since June 1997, before being named managing director of Microsoft Research India, Anandan was a senior researcher at Microsoft Research headquarters in Redmond, Washington, where he built one of the world’s strongest research teams in computer vision and video processing. During that time, he also served as an ambassador for the Microsoft Research University Relations program in India and helped develop strong relationships between Indian universities and Microsoft Research. He has represented Microsoft in meetings with the government of India to emphasize the company’s commitment to research and development. He was part of the working group constituted by the 12th Planning Commission to make recommendations on India’s Higher Education Policy. Anandan continues Microsoft Research’s ongoing relationships with the government and academic communities in his new role.

Before joining Microsoft, Anandan was an assistant professor of computer science for four years at Yale University. Following this, he was a research manager at Sarnoff Corp, Princeton, NJ. He holds a Ph.D. in computer science from the University of Massachusetts, Amherst, which presented him with a Distinguished Alumni award in 2006. He also attended the University of Nebraska, Lincoln, where he received his Master of Science degree in computer science, and the Indian Institute of Technology Madras, where he earned his undergraduate degree in electrical engineering. He received the Distinguished Alumni award from IIT Madras in 2010, and was inducted into the “Hall of Computing” by the University of Nebraska in 2010. Anandan is currently on the Board of Governors of IIT Madras.

Judith Bishop

Judith Bishop is director of Computer Science at Microsoft Research. Her role is to create strong links between Microsoft’s research groups and universities globally, through encouraging projects, supporting conferences, and engaging directly in research. Her expertise is in programming languages and mobile computing, with a strong practical bias. Her current projects are TouchDevelop and Code Hunt, and she worked previously on TryF#. She received her PhD from the University of Southampton and was a professor in South Africa for many years, with visiting positions in the United Kingdom, Germany, Canada, Italy, and the United States. She was general co-chair of ICSE 2010 and co-chair of several Microsoft Research summits and serves frequently on editorial, program, and award committees. She has written 16 books on programming, which have been translated into six languages. Her awards include the IFIP Silver Core and Outstanding Service Award (2006) and the South Africa’s Distinguished Woman Scientist of the Year (2005).

Jining Chen

Dr. Jining Chen is professor of Environmental System Analysis, Tsinghua University. Dr. Chen received his bachelor’s degree from Tsinghua University’s Department of Environmental Engineering in 1986 and earned his Ph.D. from Imperial College London in 1993. He became a research associate at Imperial College London in 1994. He joined the staff of Tsinghua University in 1998 as vice dean of the Department of Environmental Engineering and became dean of the department in 1999. Dr. Chen was appointed vice president of Tsinghua University in 2006 and became executive president of Tsinghua in 2007. Dr. Chen was appointed president of Tsinghua University in January 2012.

Dr. Chen is currently a member of the National Environmental Advisory Commission, deputy chair of the Science and Technology Committee of MEP, vice president of the Chinese Society for Environmental Sciences, and board member of the Chinese Environmental Foundation. He is also a member of many other scientific committees, professional associations, and advisory councils related to water, environment, and education.

Winnie Cui

Winnie Cui is a senior university relation manager at Microsoft Research Asia. She is responsible for creating links and building long-term and mutually beneficial collaboration and partnership between Microsoft Research and universities in Asia. She engages with academics to identify high-impact research areas and work with universities on talent development programs. Winnie started her career in the Internet industry in the United States after obtaining her M.S. and Ph.D. degree in Biomedical Engineering from the University of Memphis. She joined GE Healthcare as an international leader to manage a team spanning in Asia and Europe on the digitization excellence for go-to-market applications and programs. She also served as a regional head and initiated a partner collaboration mechanism in Hong Kong when she worked in the consulting industry on Customer Relationship Management. Winnie joined Microsoft in 2006 as the China IT Manager in the Information Technology group, responsible for accelerating Microsoft’s state-of-the-art technologies in the Greater China region, as well as for helping industrial partners benefit from cutting-edge technologies.

Darren Edge

Darren Edge is a lead researcher in Human-Computer Interaction at Microsoft Research Asia, based in Beijing, China. His 2008 PhD dissertation was the first work to explore the concept of “peripheral interaction” with objects on the boundary of the user’s attention, and much of his ongoing research aims to facilitate similarly lightweight, episodic engagement with activities of significant personal and social value. In his work to date, this has led him to explore how technology can support learning and communication across a variety of domains, resulting in award-winning papers in the areas of mobile micro-learning (Best Paper and Honorable Mention at MobileHCI’12), social exertion gaming (Honorable Mention at CHI’12), and presentation authoring (two Honorable Mentions at CHI’14; one at MobileHCI’14). He holds a BA in Computer Science and Management Studies and a PhD in Human-Computer Interaction, both from the University of Cambridge.

Bin Gao

Bin Gao is a lead researcher in Internet Economics and Computational Advertising Group (IECA), Microsoft Research. His research interests include machine learning, data mining, information retrieval, and computational advertising. He has authored two book chapters, 30 papers in top conferences and journals, and over 20 granted or pending patents. He co-authored the best student paper at SIGIR (2008). He serves as PC for SIGIR (2009–2014), WWW (2011–2013), and senior PC for CIKM (2011). He is a reviewer for TKDE, TIST, PRL, IRJ, and others. He is a tutorial speaker at WWW (2011) and SIGIR (2012). He is a workshop organizer at ICDM (2012), SIGIR (2013), KDD (2013), and ICML (2014). Prior to joining Microsoft, he got his Ph.D. degree from School of Mathematical Sciences, Peking University, and got his bachelor degree from the School of Mathematical and System Sciences, Shandong University.

Peng Gong

Prof. Peng Gong is the director of the Center for Earth System Science, Tsinghua University, and a professor at the department of Environmental Science, Policy and Management at the University of California, Berkeley. He received his Ph.D. in Geography from the University of Waterloo in 1990.

He has published more than 300 papers and edited seven books. His achievements in remote sensing image processing, analysis and application, GIS theory, techniques and application, and global change studies have been acknowledged both nationally and internationally by the receipt of numerous awards, including Overseas Assessor (1999, Chinese Academy of Sciences), Distinguished Young Scientist Award (1998, NSF China), the Talbert Abrams Grand Award from ASPRS for Best Paper in Photogrammetry (1994), the ASPRS ERDAS Award for Best Scientific Paper in Remote Sensing (1993), and the John I. Davidson ASPRS President’s Award for Practical Papers (1993).

Baining Guo

Dr. Baining Guo is assistant managing director of Microsoft Research Asia, where he also leads the graphics lab. Prior to joining Microsoft Research in 1999, he was a senior staff researcher with the Microcomputer Research Labs of Intel Corporation in Santa Clara, California. Dr. Guo graduated from Beijing University with B.S. in mathematics. He received his M.S and Ph.D. in Computer Science and Applied Mathematics from Cornell University in 1989 and 1991 respectively. Dr. Guo is a fellow of IEEE.

Dr. Guo’s research interests include computer graphics, visualization, and natural user interface. A focus of his work is data-driven techniques for texture and reflectance modeling, particularly techniques for studying light transmission and reflection in complex materials and environments through the discovery of coherent structures in large-scale, high-dimensional image data. He also worked on real-time rendering, geometry modeling, and gesture recognition (for Kinect natural user interface). Dr. Guo was on the editorial boards of IEEE Transactions on Visualization and Computer Graphics (2006–2010) and Computer and Graphics (2007–2011). He is currently an associate editor of IEEE Computer Graphics and Applications. He is serving as the papers chair for the 2014 ACM SIGGRAPH Asia conference. He has been on the program committees of numerous conferences in graphics and visualization, including ACM SIGGRAPH and IEEE Visualization. Dr. Guo holds over 50 US patents.

Shi Han

Shi Han is a lead researcher in the Software Analytics group at Microsoft Research Asia. His research interests include data-driven software analysis, machine learning, and large-scale computing platform. Incorporating expertise from these domains, he has been pursuing research on performance analysis for large-scale system software. Since 2009, he has been the key contributor to StackMine—a scalable stack-trace mining platform for Windows performance debugging in the large. Prior to 2009, he was a key contributor to the research and development of the HMM-based East Asian language handwriting recognition engine in Windows 7. He received his BS and MS in computer science from Zhejiang University in 2003 and 2006 respectively.

Junsheng Hao

Junsheng is the founder and CTO of Shanghai Yungoal Info Tech Co., Ltd. (Yungoal). He has more than 10 years’ experience in software development, project management, and running start-ups.

Junsheng was with Microsoft for approximately seven years. He worked in CSS and R&D on VB support, System Center Configuration Manager, Commerce Transaction Platform, and other projects. He was also founder and software designer of Prismlab, which manufactured machines for digital photo processing and finishing.

Junsheng devoted himself to the public cloud industry starting in 2012. His team contributed to some projects of public cloud in Asia. He is also a trainer for Microsoft Azure for Research, Azure University, and Azure Partner Readiness.

Hsiao-Wuen Hon

Dr. Hsiao-Wuen Hon is the chairman of Microsoft Asia-Pacific R&D Group, and managing director of Microsoft Research Asia. Dr. Hon oversees Microsoft’s research and development activities as well as collaborations with academia in Asia Pacific.

An IEEE Fellow and a Distinguished Scientist of Microsoft, Dr. Hon is an internationally recognized expert in speech technology. He serves on the editorial board of the international journal, Communications of the ACM. Dr. Hon has published more than 100 technical papers in international journals and at conferences. He co-authored a book, Spoken Language Processing, which is a graduate-level textbook and reference book in the area of speech technology used in many universities all over the world. Dr. Hon holds three dozen patents in several technical areas.

Dr. Hon has been with Microsoft since 1995. He joined Microsoft Research Asia in 2004 as a deputy-managing director, and was promoted to managing director in 2007. In 2014, Dr. Hon was appointed as chairman of Microsoft Asia-Pacific R&D Group. In addition, he founded and managed the Microsoft Search Technology Center (STC) from 2005 to 2007 and led development of the Microsoft internet Search product (Bing) in Asia Pacific. Prior to joining Microsoft Research Asia, Dr. Hon was the founding member and architect of the Natural Interactive Services Division at Microsoft Corporation. Besides overseeing all architectural and technical aspects of the award winning Microsoft Speech Server product, Natural User Interface Platform and Microsoft Assistance Platform, he is also responsible for managing and delivering statistical learning technologies and advanced search. Dr. Hon joined Microsoft Research as a senior researcher in 1995 and has been a key contributor to Microsoft’s SAPI and speech engine technologies. He previously worked at Apple Computer, where he led research and development for Apple’s Chinese Dictation Kit.

Dr. Hon received a Ph.D. in Computer Science from Carnegie Mellon University and a B.S. in Electrical Engineering from National Taiwan University.

Qiang Huo

Dr. Qiang Huo is a principal researcher and research manager of Speech Group at Microsoft Research Asia. Prior to joining Microsoft Research Asia in August 2007, Qiang had been a faculty member at the Department of Computer Science, The University of Hong Kong (HKU) since 1998. From 1995 to 1997, he worked at ATR (Advanced Telecommunications Research Institute), Kyoto, Japan. From 1991 to 1994, he did his Ph.D. research at HKU. In the past 25 years, he has been doing research and making fundamental contributions in the areas of speech recognition, handwriting recognition, OCR, gesture recognition, biometric-based user authentication, hardware design for speech and image processing. Qiang received the B.Eng. degree from the University of Science and Technology of China (USTC), Hefei, China, in 1987, the M.Eng. degree from Zhejiang University, Hangzhou, China, in 1989, and the Ph.D. degree from the USTC, in 1994, all in electrical engineering.

Kap-Young Jeong

Kap-Young Jeong, Ph.D., is an economist with expertise in the fields of industrial organization, public policy, and East Asian economy, as well as a visionary educator and education administrator.

After graduating from Yonsei University, Kap-Young Jeong obtained his master’s degree from the University of Pennsylvania, and his doctoral degree in Economics from Cornell University. Since becoming a professor at Yonsei University in 1986, he has focused his research on areas of industrial organization, public policy, and East Asian economy.

For his research accomplishments in economics, he has been listed in the Marquis Who’s Who in the World and has received a wide range of awards such as the Dasan Economics Award from Hankyung Economic Daily, as well as the Economist of the Year from Maeil Economic Daily.

Jeong has held a variety of posts, including president of the Korea Academic Society of Industrial Organization, president of the Korea Association for Comparative Economics, commissioner of Korea Communications Commission, Distinguished Research Fellow of the Samsung Economics Research Institute, chairman of The Center for Free Enterprise and guest editorial writer for The Dong-A Ilbo. Currently, he is an editor at the Global Economic Review (SSCI Journal, Published by Institute of East and West Studies, Yonsei University). He also serves as member and chair of the Policy Planning Committee under the Ministry of Justice, as well as the member of the Macroeconomy and Finance Subcommittee Chairperson under the National Economic Advisory Council.

His major scholarly publications include The Third Capital (2009, Samsung Economic Research Institute), Industrial Organization Theory (2009, Ed. 6, Pakyoungsa), Comparative Analysis of Korea and Japan’s Economic Development and Political Environment (Joint authorship; 2003, Jipmoondang), and many more.

He has shared his economics expertise with public—and even children—by publishing a series of educational books and cartoons including Nine is Greater Than Ten, A Coin for Charon, and Economics Read with Cartoons. He makes regular appearances on a variety of television shows such as Economics in My Hand at MBC, Economics Focus at KBS, and TV Column at SBS.

In addition to his profession as an economist, Professor Kap-Young Jeong has demonstrated outstanding capabilities as an educational administrator. At Yonsei University, he has held various posts such as the dean of Academic Affairs, dean of the Graduate School of Information, and senior vice president of Wonju Campus. He has served as president of Yonsei University since February 2012.

Hiroyuki Kajimoto

Hiroyuki Kajimoto is associate professor at the University of Electro-Communications, Japan. He also serves as a researcher for the Japan Science and Technology Agency. He earned his bachelor degree in mathematical engineering in 1998 and received a PhD in information science and technology in 2006 from The University of Tokyo. He was a research fellow of the Japan Society for the Promotion of Science from 2001 to 2003, and was assistant professor of the University of Tokyo from 2003 to 2006.

His research interests include tactile displays, tactile sensors, electrical nerve stimulation, human computer interaction, welfare devices, and virtual reality. He has published over 100 papers for international conferences such as IEEE Haptics Symposium, EuroHaptics, and Conference on Human Factors in Computing Systems, and for peer-reviewed journals such as IEEE Computer Graphics & Applications Magazine and IEEE Transactions on Haptics. He was a founding member of IEEE Technical Committee on Haptics and is a member of IEEE and ACM.

Takeo Kanade

Takeo Kanade is the U. A. and Helen Whitaker University Professor of Computer Science and Robotics. He received his doctoral degree in Electrical Engineering from Kyoto University, Japan, in 1974. After holding a faculty position in the Department of Information Science, Kyoto University, he joined Carnegie Mellon University in 1980. He was the Director of the Robotics Institute from 1992 to 2001, and a founding director of Quality of Life Technology Research Center from 2006 to 2012. In Japan, he founded the Digital Human Research Center in Tokyo and served as the founding director from 2001 to 2010.

Dr. Kanade works in multiple areas of robotics: computer vision, multi-media, manipulators, autonomous mobile robots, medical robotics, and sensors. He has written more than 300 technical papers and reports in these areas, and holds more than 20 patents. He has been the principal investigator of more than a dozen major vision and robotics projects at Carnegie Mellon.

Dr. Kanade has been elected to the National Academy of Engineering, and also to the American Academy of Arts and Sciences. He is a Fellow of the IEEE, a Fellow of the ACM, a Founding Fellow of American Association of Artificial Intelligence (AAAI), and the former and founding editor of the International Journal of Computer Vision. The awards he has received include the Franklin Institute Bower Prize, Okawa Award, C&C Award, ACM/AAAI Allen Newell Award, Joseph Engelberger Award, IEEE Robotics and Automation Society Pioneer Award, FIT Accomplishment Award, and IEEE PAMI-TC Azriel Rosenfeld Lifetime Accomplishment Award.

Noboru Kuno

Noboru (Sean) Kuno is a university relations manager at Microsoft Research Asia. He is based in Tokyo and he is in charge of Microsoft Research academic collaboration in Japan. Kuno leads the Mt. Fuji Plan, a comprehensive program that works to encourage collaboration between academia in Japan and Microsoft Research. The program is organized around four pillars: Research Collaboration, Talent Fostering, Academic Exchanges, and Curriculum Innovation. Kuno is responsible for the entire program strategy, planning, and operation to engage with universities, research institutes, and government agencies. Kuno joined Microsoft Research Asia in 2009. Before he joined Microsoft, he worked for the Japan Science and Technology Agency (JST), the second largest funding agency in Japan, where he acquired more than four years’ experience of project funding, program management, and promotion of basic science research projects and academic exchange events. Before JST, he worked as a manager of marketing and product & business development in the cable and satellite industry in Japan. He received a bachelor degree (1996) and a master’s degree (1998) in Quantum Engineering and Systems Science from the Graduate School of Engineering, the University of Tokyo.

Butler W. Lampson

Butler Lampson is a Technical Fellow at Microsoft Corporation and an adjunct professor of Computer Science and Electrical Engineering at MIT. He was on the faculty at Berkeley and then at the Computer Science Laboratory at Xerox PARC and at Digital’s Systems Research Center. He has worked on computer architecture, local area networks, raster printers, page description languages, operating systems, remote procedure call, programming languages and their semantics, programming in the large, fault-tolerant computing, transaction processing, computer security, WHSIWYG editors, and tablet computers. He was one of the designers of the SDS 940 time-sharing system, the Alto personal distributed computing system, the Xerox 9700 laser printer, two-phase commit protocols, the Autonet LAN, the SDSI/SPKI system for network security, the Microsoft Tablet PC software, the Microsoft Palladium high-assurance stack, and several programming languages.

He received an AB from Harvard University, a PhD in EECS from the University of California at Berkeley, and honorary ScDs from the Eidgenössische Technische Hochschule, Zurich and the University of Bologna. He holds a number of patents on networks, security, raster printing, and transaction processing. He is a member of the National Academy of Sciences and the National Academy of Engineering, and is a Fellow of the Association for Computing Machinery and the American Academy of Arts and Sciences. He received the ACM Software Systems Award in 1984 for his work on the Alto, the IEEE Computer Pioneer award in 1996, the National Computer Systems Security Award in 1998, the IEEE von Neumann Medal in 2001, the Turing Award in 1992, and the National Academy of Engineering’s Draper Prize in 2004.

At Microsoft, he has worked on anti-piracy, security, fault-tolerance, and user interfaces. He was one of the designers of Palladium, and spent two years as an architect in the Tablet PC group. Currently he is in Microsoft Research, working on security, privacy, and fault-tolerance, and kibitzing in systems, networking, and other areas.

Hyunju Lee

Professor Hyunju Lee is currently an associate professor of GIST. She received B.S. degree from Korea Advanced Institute of Science and Technology (KAIST), Daejon, Korea, in 1997; M.S. degree from Seoul National University, Seoul, Korea, in 1999; and Ph.D. degree from University of Southern California, United States in 2006. She have served as a faculty member at the School of Information and Communications of GIST since 2007. Prior to joining GIST, she was a post-doctoral researcher at the Harvard Medical School from 2006 to 2007.

Lee’s research interests include data mining, bioinformatics, cancer genetics, and text mining, and she has published highly-cited papers in international journals. She has been developing novel data mining methods for diverse areas—from the Internet to life science. Currently, she is building a search engine for cancer researchers and integrative algorithms for revealing new biomarkers for various diseases.

Miran Lee

Miran Lee is a principal research program manager of Microsoft Research Outreach Group at Microsoft Research responsible for academic collaboration in Korea and Asia-Pacific region.

Lee joined Microsoft Research Asia in 2005 as university relations manager to build long-term and mutually beneficial relations with academia. She is based in Korea, where she engages with leading research universities, research institutes, and relevant government agencies. She establishes strategies and directions, identifies business opportunities, designs various programs and projects, and manages budget. She works with students, researchers, faculty members, and university administrators to build strong partnerships, and works closely with the research groups at Microsoft Research, focusing on research collaboration, curriculum development, talent fostering, and academic exchanges. She has successfully run a number of global and regional programs such as Gaming & Graphics, Web-Scale NLP, Machine Translation, eHealth, SORA (Software Radio), Kinect, and Microsoft Azure for Research.

Prior to her current role, Miran Lee co-founded Smart Systems, which specializes in IT outsourcing services in Illinois, United States. As CEO of Smart Systems, she successfully led the business with more than 100 percentage annual growth. From 1993 to 2002, she worked at British Telecom Korea in various positions ranging from systems engineer to account director to vice president. Lee also worked at Samsung SDS, where she was responsible for International VAN (Value Added Network) businesses and led the International VAN business team. She started her business career as a system developer at General Electric Information Services, where she developed email, EDI, and in-house applications.

Miran Lee was an adjunct professor in the Telecommunication Department at Anyang University for two years (2001–2002) and she earned her MS in Engineering from Ewha Womans University.

Sangyoun Lee

Sangyoun Lee is a professor in the Department of Electrical and Electronic Engineering at Yonsei University. He received his BS and MS degrees from Yonsei University. After he completed his MS, he started to work for Korea Telecom (KT). During this time, he completed his PhD degree in Electrical and Computer engineering from Georgia Institute of Technology. At KT, he focused on multimedia standards development, especially on MPEG (Moving Picture Expert Group: ISO/IEC SC29/WG11). Some of his proposals on MPEG-7 area were adopted as the international standard. From 2004, he moved to Yonsei University as a faculty member in Electrical and Electronic Engineering. He also became a faculty researcher at BERC (Biometric Engineering Research Center), focusing on biometric technology (fingerprint, iris, face, and speech). He was vice director of the center from 2004 to 2011. At the center, he worked on 2D/3D face recognition and modeling. He also worked with KIST (Korea Institute of Science and Technology) to develop a 3D montage system. This system is the first approach in the world that extends 2D montage to 3D montage for more reliable and robust montage generation. He has also worked with many mobile, TV, and car companies—including Samsung, LG, Hyundai, and Pantech—on computer vision applications.

Shipeng Li

Dr. Shipeng Li joined and helped to found Microsoft Research’s Beijing lab in May 1999. His research interests include multimedia processing, analysis, coding, streaming, networking, and communications. From Oct. 1996 to May 1999, Dr. Li was with Sarnoff Corporation. Dr. Li has been actively involved in research and development in broad multimedia areas and international standards. He has authored and co-authored six books/book chapters and more than 280 referred journal and conference papers. He holds more than 140 granted US patents.

Dr. Li received his B.S. and M.S. in Electrical Engineering (EE) from the University of Science and Technology of China (USTC) in 1988 and 1991, respectively. He received his Ph.D. in EE from Lehigh University in 1996. He was a faculty member at USTC in 1991–1992. Dr. Li is a fellow of IEEE. He is now serving as deputy editor-in-chief of IEEE Transactions on Circuits and Systems for Video Technology.

Victor Li

Victor O.K. Li received SB, SM, EE and ScD degrees in Electrical Engineering and Computer Science from MIT in 1977, 1979, 1980, and 1981, respectively. He is chair professor of Information Engineering, and head of the department of Electrical & Electronic Engineering at the University of Hong Kong (HKU). He also chairs the Executive Committee of the HKU Initiative on Clean Energy and Environment. He served as associate dean of Engineering, and managing director of Versitech Ltd., the technology transfer and commercial arm of HKU. He has served on the board of China.com Inc., and now serves on the boards of Sunevision Holdings Ltd. and Anxin-China Holdings Ltd., listed on the Hong Kong Stock Exchange. Previously, he was professor of Electrical Engineering at the University of Southern California (USC), Los Angeles, California, United States, and director of the USC Communication Sciences Institute. Sought by government, industry, and academic organizations, Professor Li has lectured and consulted extensively around the world. He has received numerous awards, including the PRC Ministry of Education Changjiang Chair Professorship at Tsinghua University, the UK Royal Academy of Engineering Senior Visiting Fellowship in Communications, the Croucher Foundation Senior Research Fellowship, and the Order of the Bronze Bauhinia Star, Government of the Hong Kong Special Administrative Region, China. He is a Registered Professional Engineer and a Fellow of the Hong Kong Academy of Engineering Sciences, the IEEE, the IAE, and the HKIE.

Mike Liang

Mike joined the Mobile and Sensing Systems (MASS) group in 2011, after he got his PhD from Johns Hopkins University. Mike’s research interests center around systems and tools that enable large-scale systems solving problems in mobile and sensing areas.

Kangping Liu

Kangping Liu is a senior university relations manager at Microsoft Research Asia. In his current role, Kangping works closely with college students, faculty members, and university administrators to build long-term and mutually beneficial collaborations and partnerships between Microsoft Research and academia in Asia. He engages with academics to identify high-impact research topics and works with universities on talent programs. Kangping is the program manager of Microsoft Research Asia’s “Accelerating Urban Informatics with Microsoft Azure” research theme. He also is program manager of the Microsoft Research Asia Faculty Summit 2014.

Prior to joining Microsoft Research Asia in 2010, Kangping worked on technical consulting and business development for IBM and Sun Microsystems. He has been an early advocate of cloud computing in China since 2006 and has been invited to speak at various industry events. Kangping joined GE Global Research Center in Shanghai as a senior engineer after receiving his Ph.D. in Computer Science from Xi’an Jiaotong University in 2002. Kangping also earned his B.S. and M.S. in Electronics Engineering from Xi’an University of Technology in 1994 and 1997 respectively.

Wei-Ying Ma

Dr. Wei-Ying Ma is an assistant managing director at Microsoft Research Asia where he oversees multiple research groups including Web Search and Data Mining, Natural Language Computing, and Human Computer Interaction.

Under his leadership, Wei-Ying’s team of researchers has been recognized a global powerhouse in search, data mining, and multimedia information retrieval related research. The team has transferred key technologies into Microsoft’s search and online service products. In addition, the team has published extensively at major conferences such as the SIGIR, WWW, and ACM Multimedia.

Before joining Microsoft in 2001, Wei-Ying was with HP Labs in Palo Alto, California, where he worked in the fields of multimedia adaptation and distributed media services infrastructure. From 1994 to 1997, Wei-Ying was engaged in the Alexandria Digital Library project at the University of California, Santa Barbara. During this time, he developed one of the first web-based image-retrieval systems, Netra, which is regarded as one of the most influential image-retrieval systems.

As an active member of the research community, Wei-Ying has published more than 250 papers at international conferences. He currently serves on the editorial boards of ACM Transactions on Information System and ACM/Springer Multimedia Systems Journal. In recent years, he served as program co-chair of WWW 2008, program co-chair of PCM 2007, general co-chair of AIRS 2008, and general co-chair of MMM 2005.

Wei-Ying received a Bachelor of Science in electrical engineering from the National Tsing Hua University in Taiwan in 1990. He earned a Master of Science degree and doctorate in electrical and computer engineering from the University of California at Santa Barbara in 1994 and 1997, respectively.

Thomas Moscibroda

Thomas Moscibroda is a senior researcher and founding manager of the System Algorithms (SysAlgo) Research Group at Microsoft Research Asia. He is also the chair professor for Network Science at the Institute for Interdisciplinary Information Sciences (IIIS) at Tsinghua University. Prior to founding the new SysAlgo group, Thomas was a member of the Mobile & Sensing Systems Research Group at Microsoft Research Asia. Before moving to China in 2011, he was a member of the Distributed Systems Research group at Microsoft Research in Redmond for five years, and he was an affiliate member of the Networking Research Group and the Computer Architecture Research group at Microsoft Research Redmond, respectively.

Thomas’ research interests are in (wireless) networking, computer architecture, and distributed systems, with ongoing projects in each of these areas. He has a particular focus on algorithmic and mathematical approaches to practical system design. He obtained his PhD in 2006 from ETH Zurich, and was awarded the ETH Medal for his doctoral thesis. His research is documented in more than 60 research papers, and he has received Best Paper Awards at several top-tier conferences, including IPSN 2007, SIGCOMM 2009, NSDI 2009, ASPLOS 2010, EuroSys 2012, as well as PODC 2004 and 2012. His articles on DRAM scheduling and on-chip networking in multi-core systems were selected as IEEE Micro Top-Pick Computer Architecture papers in 2008 and 2010, respectively. He is also the recipient of the MICS Research on Communications Award by the National Research Foundation of Switzerland (NCCR) for his contributions to the area of Mobile Communications and Information Systems.

Zaiqing Nie

Zaiqing Nie is a senior researcher at Microsoft Research Asia. He leads a research team working on web-scale entity search and knowledge mining. Nie and his team aim at building web-scale Entity Graph through interactive knowledge mining and crowdsourcing, and they have built several web-scale entity search systems including Renlifang, Microsoft Academic Search, and EntityCube. Before joining Microsoft in April 2004, Nie received a Ph.D. in Computer Science from Arizona State University in 2004, a Master of Engineering degree in Computer Applications from Tsinghua University in 1998, and a Bachelor of Engineering degree in Computer Science and Technology from Tsinghua University from in 1996. His research interests include web search, data mining, crowdsourcing, and machine learning. Nie has many publications in high quality conferences and journals including SIGKDD, WWW, ICML, CIDR, ICDE, JMLR, and TKDE. His recent academic activities include PC co-chair of IIWeb 2014, senior PC of IJCAI 2013, SDM 2013, and KDD 2012, and PC member of WWW 2014, KDD 2014, WSDM 2015. Some entity mining and search technologies he developed have been transferred to Microsoft Bing.

Takeshi Oishi

Takeshi Oishi is an associate professor at the Institute of Industrial Science, the University of Tokyo. He received the B.Eng. degree in Electrical Engineering from Keio University in 1999, and the Ph.D. degree in Interdisciplinary Information Studies from the University of Tokyo in 2005. His research interests are in 3D modeling from reality, digital archiving of cultural heritage assets, and mixed/augmented reality. He has served as program committee member for several computer vision conferences, including ICCV, CVPR, ACCV, and 3DIM/3DPVT (merged into 3DV). He also organized the first three ACCV Workshops on e-Heritage and ICPR Workshop on Depth Image Analysis (WDIA).

Tim Pan

Dr. Tim Pan is university relations director of Microsoft Research Asia, responsible for the lab’s academic collaboration in the Asia-Pacific region.

Tim Pan leads a regional team with members based in China, Japan, and Korea engaging universities, research institutes, and certain relevant government agencies. He establishes strategies and directions, identifies business opportunities, and designs various programs and projects that strengthen partnership between Microsoft Research and academia.

Tim Pan earned his Ph.D. in Electrical Engineering from Washington University in St. Louis. He has 20 years of experience in the computer industry and has co-founded two technology companies. Tim has a great passion for talent fostering. He served as a board member of St. John’s University (Taiwan) for 10 years, offered college-level courses, and wrote a textbook about information security. Between 2005 and 2007, Tim worked for Microsoft Research Asia as a university relations manager for Taiwan and Hong Kong. He rejoined Microsoft Research Asia in 2012.

Christos H. Papadimitriou

Christos H. Papadimitriou is the C. Lester Hogan Professor of Computer Science at UC Berkeley, and the Senior Scientist of the Simons Institute for the Theory of Computing. Before joining Berkeley in 1996, he taught at Harvard, MIT, Athens Polytechnic, Stanford, and University of California, San Diego. He has written five textbooks and many articles on algorithms and complexity, and their applications to optimization, databases, AI, the Internet, economics, and evolution. He has also published three novels. He is a member of the National Academy of Sciences (United States), the American Academy of Arts and Sciences, and the National Academy of Engineering. He holds a PhD from Princeton, and seven honorary doctorates.

Tai-Quan Peng

Tai-Quan (Winson) Peng (PhD, City University of Hong Kong, 2008) is currently an assistant professor at the Wee Kim Wee School of Communication of Nanyang Technological University at Singapore. His recent research interest lies in political communication on social media, public sentiment on social media, and the diffusion of viral messages on social media. His work has been supported by Microsoft, Singapore Academic Research Fund, and Nanyang Technological University.

David S. Rosenblum

David S. Rosenblum is professor of Computer Science and Dean of the School of Computing at the National University of Singapore, where he also directs the Felicitous Computing Institute. He received his PhD from Stanford University in 1988, and he was previously a research scientist at AT&T Bell Laboratories (Murray Hill); associate professor at the University of California, Irvine; principal architect and chief technology officer of PreCache (a technology startup funded by Sony Music); and professor of Software Systems at University College London. His research interests are centered on problems in the design, analysis, and testing of large-scale distributed software systems and ubiquitous computing systems. He is currently the Editor-in-Chief of the ACM Transactions on Software Engineering and Methodology (ACM TOSEM). In 2002 he received the ICSE Most Influential Paper Award for his ICSE 1992 paper on assertion checking, and in 2008 he received the first ACM SIGSOFT Impact Paper Award with Alexander L. Wolf for their ESEC/FSE 1997 paper on Internet-scale event notification. He has been the recipient of an NSF CAREER grant in the United States and a Wolfson Research Merit Award from the Royal Society in the United Kingdom. He is a fellow of the ACM and IEEE and a senior member of the Singapore Computer Society, and he is the past chair of the ACM Special Interest Group in Software Engineering (ACM SIGSOFT).

Jeha Ryu

Jeha Ryu received his B.S. degree at Seoul National University, Korea, in 1982, M.S. degree at the Korea Advanced Institute of Science and Technology (KAIST), Korea, in 1984, and Ph.D. degree at the University of Iowa, United States, in 1991—all in mechanical engineering. He has been a professor in the Department of Mechatronics at the Gwangju Institute of Science and Technology (GIST) since 1994. He was a visiting researcher at the Virtual Reality Lab at Rutger University’s CAIP Center during 2001–2002. He has been the director of the Korean National Haptics Technology Research Center since 2008. His main research area is the haptic technology that includes haptic interaction control in virtual environments, haptic tele-operation over any networks, tele-rehabilitation robotics, design and control of haptic devices, haptic rendering, modeling, authoring, and haptic broadcasting systems. He served as an associate editor of the IEEE Transactions on Haptics during 2008–2011 and as the president of the Korean Haptic society during 2013–2014.

Arjmand Samuel

Arjmand Samuel works with the academic community to foster research and collaborations in the devices and services research areas. He leads the mobile and cloud computing research and outreach for Microsoft Research (Project Hawaii and TouchDevelop). His recent research interests are in software architectures and programming paradigms for devices of all shapes and forms (TouchDevelop and HomeOS). He has published in a variety of publications on topics of security, privacy, location aware access control, and innovative use of mobile technology. Samuel has a Ph.D. in Information Security from Purdue University.

Bin Shao

Bin Shao is a researcher at Microsoft Research (Beijing, China). He joined Microsoft after receiving his Ph.D. degree from Fudan University in July 2010. He received his B.S. degree from Shandong University in July 2005. Bin Shao is the architect, and the main developer of the Microsoft Research Trinity project, which builds a graph processing engine on a distributed in-memory storage infrastructure called memory cloud. His research interests include in-memory databases, distributed systems, graph query processing, and optimistic consistency maintenance.

Guangzhong Sun

Dr. Guangzhong Sun is an associate professor in School of Computer Science and Technology, University of Science and Technology of China (USTC). He is a member of National High Performance Computing Center (Hefei). He got his Ph.D. in computer science at USTC in 2005. He worked as a visiting researcher in Microsoft Research Asia from October 2007 to August 2008 and from September 2010 to February 2011. He has published more than 40 papers, including papers in reputed journals and major international conferences. He is a senior member of IEEE and CCF and a member of ACM and SIAM. His research interests include pervasive computing, data processing, parallel computing, and combinatorial algorithms.

Jian Sun

Jian was born in Xian (home of Terracotta Army), China. He received a BS degree, a MS degree, and a PhD degree from Xian Jiaotong University in 1997, 2000, and 2003. He joined Microsoft Research Asia in 2003. His research is in the fields of computer vision and computer graphics, with particular interests in interactive compute vision (user interface + vision), and internet compute vision (large image collection + vision). He is also interested in stereo matching, computational photography, face recognition, and deep learning. He received Best Paper Award for the paper “Single Image Haze Removal Using Dark Channel Prior” at CVPR 2009. In 2010, he was named one of the world’s top 35 young innovators by MIT Technology Review. He served as an area chair for ICCV 2011, CVPR 2013, and as a committee member for Siggraph 2011. Now, he is leading a compute vision team at Microsoft Research Asia.

Hong Tan

Born in Shanghai, China, Hong studied Biomedical Engineering at Shanghai Jiao Tong University, and later earned her master’s and doctorate degrees, both in Electrical Engineering and Computer Science, from Massachusetts Institute of Technology (MIT). She became fascinated with haptics research after meeting a deaf and blind person who “read” speech by placing his hand on the speaker’s talking face. During her doctoral research, Hong built a device called the Tactuator and demonstrated its ability to transmit 12 bits per second through touch, the same rate at which the deaf and blind person can read speech with hand. Afterwards, Hong worked at the MIT Media Lab as a research scientist and developed the Sensing Chair, a sitting posture classifier using real-time pressure distribution data from an office chair. Since 1998, Hong has been on the faculty at Purdue University, taking a perception-based approach to developing haptic interfaces that match human sensory and motor capabilities. In 2011, Hong took a sabbatical leave from Purdue University to explore the commercialization of haptics technologies at Microsoft Research Asia in Beijing, China. She is currently a senior researcher and manager of the Human Computer Interaction group at Microsoft Research Asia. Her current research interests include haptic interactions on touchscreens and in wearables.

Xin Tong

Xin Tong is a principal researcher in Internet Graphics Group of Microsoft Research Asia. He obtained my Ph.D. degree in Computer Graphics from Tsinghua University in 1999. Before that, Xin got my B.S. Degree and Master Degree in Computer Science from Zhejiang University in 1993 and 1996 respectively. His research interests include appearance modeling and rendering, texture synthesis, image based modeling and rendering, and performance capturing. Xin Tong is associate editor of IEEE Transactions on Visualization and Graphics now. He also serves as Co-Chair of Pacific Graphics 2013 and paper committee member of SIGGRAPH and SIGGRAPH ASIA.

Hao-Chuan Wang

Hao-Chuan Wang has been an assistant professor at the Department of Computer Science and the Institute of Information Systems and Applications of National Tsing Hua University since February 2012. He received his Ph.D. in Information Science from Cornell University in 2011. He also studied and worked at the School of Computer Science, Carnegie Mellon University (2006–2008) and the Institute of Information Science, Academia Sinica (2004–2006). Prof. Wang’s main research interest lies in the collaborative and social aspects of human-computer interaction (HCI). His work aims to integrate computing research and behavioral and social sciences for problem solving and value creation. His recent projects include designing and evaluating machine translation tools for supporting cross-lingual communication and collaboration, using motion sensors to study human communication, and supporting education and learning with visualization and mobile devices. He is an active participant of international and regional HCI communities, such as ACM SIGCHI. He serves as one of the Program Committee associate chairs for CHI 2015, CSCW 2015, CHI 2014, CSCW 2013, and the Demonstrations co-chair for CSCW 2014. He is also the Program co-chair for Chinese CHI 2014. Professor Wang has received funding support for his research from the Ministry of Science and Technology of Taiwan, Microsoft Research Asia, Google, Industrial Technology Research Institute, and Delta Electronics.

Jeannette Wing

Jeannette M. Wing is corporate vice president, Microsoft Research. She is in charge of the seven Microsoft Research labs worldwide. She joined Microsoft last year from Carnegie Mellon University, where she was President’s Professor of Computer Science and twice served as the head of the Computer Science Department. From 2007 to 2010, she was the assistant director of the Computer and Information Science and Engineering Directorate at the National Science Foundation. She received her S.B., S.M., and Ph.D. degrees in computer science, all from the Massachusetts Institute of Technology. Dr. Wing has published extensively in the areas of trustworthy computing (including security and privacy), specification and verification, concurrent and distributed systems, programming languages, and software engineering.

She has been on many government, academic, and industrial advisory boards, and is incoming chair of DARPA ISAT. She is on the editorial boards of seven journals, including Communications of the ACM and Journal of the ACM. She received the CRA Distinguished Service Award in 2011.

She is a fellow of the American Academy of Arts and Sciences, American Association for the Advancement of Science, the Association for Computing Machinery (ACM), and the Institute of Electrical and Electronic Engineers (IEEE).

Huayi Wu

Dr. Huayi Wu is a Distinguished Professor of the Chang Jiang Scholars Program in Cartography and Geographic Information Engineering. He is an associate director of the State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS). He obtained his B.Sc. and M.Sc. in 1988 and 1991 on Probability Theory and Mathematical Statistics, and his Ph.D. on Photogrammetry and Remote Sensing. His Ph.D. thesis was among the top 100 best thesis research in China in the year 2002. He was awarded the New Century Talent in University by the Ministry of Education, China. His research interest is geospatial information sharing and interoperability. He has served as PI for a series of projects supported by the Ministry of Science & Technology and the Ministry of Education. He has successfully organized several international academic meetings or sessions. He is a reviewer of several journals in this field, including International Journal of Geographical Information Science (IJGIS), Computers, Environment and Urban Systems (CEUS), and Computers & Graphics (C&G). He owns two patents and five software registrations in China. He has supervised more than 23 master students and 8 Ph.D. students. He published more than 100 peer-reviewed papers. He is a member of ISPRS, AGU, and AAG and chairs the ISPRS VI/1 working group.

Ming Wu

Ming Wu is a lead researcher in Systems Research Group at Microsoft Research Asia. His research interests include large-scale distributed storage and computation, transaction processing, parallel and distributed graph computation, distributed system diagnostics, and scheduling and resource management in large-scale data center clusters. Since joining Microsoft Research Asia in 2007, he has published many research papers in several top conferences in system research area, including OSDI, SOSP, NSDI, Eurosys, Usenix, FSE, and PPoPP. He received his BS in computer science from University of Science and Technology of China in 2002 and received Ph.D. in computer science from Institute of Computing Technology, Chinese Academy of Science in 2007.

Zheping Xu

Dr. Zhpeing Xu is a technique director and developer in the Center for Documentation and Information Management in the Institute of Botany, Chinese Academy of Sciences. Currently, Xu focuses on the biodiversity informatics, database, web GIS, and digital library. Xu has published more than 20 articles in biodiversity informatics, geology, computer sciences, digital library, and heritage tourism.

Dr. Xu is an assistant director of the NSII (National Specimen Information Infrastructure, 2014-), a member of PASTD (Preservation of and Access to Scientific and Technical Data in/for/with Developing Countries), a Task Group member of CODATA (2013–2014), the node manager of GBIF (Global Biodiversity Information Facility), a member of CAS (2013-), and a member of Young Workgroup of National Science & Technology Infrastructure (2013-).

Andrew Yao

Andrew Yao is currently the dean of the Institute for Interdisciplinary Information Sciences, at Tsinghua University, Beijing. He received his BS in Physics from National Taiwan University, PhD in Physics from Harvard University, and PhD in Computer Science from the University of Illinois. From 1975 onward, Yao served on the faculty at MIT, Stanford, UC Berkeley and, during 1986 to 2004, as William and Edna Macaleer Professor of Engineering and Applied Science at Princeton University. In 2004, he left Princeton to join Tsinghua University in Beijing. He is also a Distinguished Professor-at-Large at the Chinese University of Hong Kong.

Yao’s research interests are in the theory of computation and its applications to cryptography and quantum computing. In 2000, he was honored with the prestigious A.M. Turing Award for his contributions to the theory of computation, including pseudorandom number generation, cryptography, and communication complexity. He has received numerous other honors and awards, including the George Polya Prize, the Donald E. Knuth Prize, and several honorary degrees. He is a member of the US National Academy of Sciences, the American Academy of Arts and Sciences, and the Chinese Academy of Sciences.

Hwasoo Yeo

Hwasoo Yeo was born in Seoul, Korea in 1972. He received his B.S. degree in Civil Engineering from Seoul National University, Seoul, Korea in 1996 and his M.S. and Ph.D. degrees in Civil and Environmental Engineering from the University of California, Berkeley, United States, in 2008. Since 2009, he has been an assistant professor in the Department of Civil and Environmental Engineering at KAIST. His current research interests include theoretical and simulation studies on traffic flow and traffic operations, traffic safety, and intelligent transportation systems.

Wenjun Zeng

Wenjun Zeng is a principal researcher and research manager of the Internet Media Group at Microsoft Research Asia. Prior to joining Microsoft Research Asia, Wenjun was with the Computer Science Dept. of Univ. of Missouri (MU), most recently as a full professor. He worked for PacketVideo Corp., Sharp Labs of America, Bell Labs, and Panasonic Technology prior to joining MU in 2003. Wenjun has contributed significantly to the development of international standards (ISO MPEG, JPEG2000, and OMA), and has developed wireless video streaming products that have been widely used. He holds fifteen US patents. Wenjun received his B.E., M.S., and Ph.D. degrees from Tsinghua Univ., the Univ. of Notre Dame, and Princeton Univ., respectively. His current research interest includes mobile-cloud media computing, social network/media analysis, multimedia communications/networking, and content/network security.

He is/was an AE of IEEE Trans. on Circuits & Systems for Video Technology (TCSVT), IEEE Multimedia (currently an Associate EiC), IEEE Trans. on Info. Forensics & Security, and IEEE Trans. on Multimedia (TMM), and is/was on the Steering Committee of IEEE Trans. on Mobile Computing (current) and IEEE TMM (2009–2012). He served as the Steering Committee Chair of IEEE Inter. Conf. Multimedia and Expo (ICME) in 2010 and 2011, and has served as the TPC Chair/co-Chair of several IEEE conferences (e.g., ChinaSIP’15, WIFS’13, ICME’09, CCNC’07). He will be a general co-Chair of ICME2018. He is currently guest editing a TCSVT Special Issue on Visual Computing in the Cloud – Mobile Computing, and was a guest editor (GE) of ACM TOMCCAP Special Issue on ACM MM 2012 Best Papers, a GE of the Proceedings of the IEEE’s Special Issue on Recent Advances in Distributed Multimedia Communications (January 2008) and the lead GE of IEEE TMM’s Special Issue on Streaming Media (April 2004). He is a Fellow of the IEEE.

Jianwen Zhang

Jianwen joined the Machine Learning Group of Microsoft Research Asia in July 2011 after receiving his PhD degree from Tsinghua University. Jianwen is interested in theories and algorithms of machine learning and their applications in text understanding and information retrieval.

Feng Zhao

Dr. Zhao is an assistant managing director at Microsoft Research Asia, responsible for the hardware, mobile and sensing, software analytics, systems, and networking research areas. His own research has focused on wireless sensor networks, energy-efficient computing, and mobile systems. Prior to joining Microsoft Research Asia in 2009, he was a principal researcher at Microsoft Research Redmond (2004–2009), and founded the Networked Embedded Computing Group that has designed and deployed sensor networks at several Microsoft datacenters for environmental monitoring and energy optimization. He was a principal scientist at Xerox PARC 1997–2004, and founded PARC’s sensor network effort.

Dr. Zhao has championed the wireless sensor network and energy-efficient computing research in the past two decades. He was among the first to develop a suite of collaborative sensing and processing protocols for tracking problems by using networked sensors, including the IDSQ algorithm. He authored or co-authored more than 100 technical papers and books, including Wireless Sensor Networks: An Information Processing Approach, co-authored with Leonidas Guibas. He was the founding editor-in-chief of ACM Transactions on Sensor Networks (2003–2010), and founded the ACM/IEEE IPSN conference. In 2008, he helped start a new workshop, HotPower, focusing on the emerging topic of sustainable computing.

Dr. Zhao received a PhD in Computer Science from MIT, and a BS from Shanghai Jiaotong University. He taught at Ohio State University and Stanford University. An IEEE Fellow, Dr. Zhao received a Sloan Research Fellowship (1994) and NSF and ONR Young Investigator Awards (1994, 1997). His work has been featured in news media such as BBC World News, Businessweek, and Technology Review.

Yu Zheng

Dr. Yu Zheng is a lead researcher from Microsoft Research, passionate about using big data to tackle urban challenges. His research into urban computing has attracted a broad range of attention from the community, receiving four best paper awards at prestigious conferences (such as ICDE’13 and ACM SIGSPATIAL’11). He has been featured multiple times by influential journals, such as MIT Technology Review and New Scientist.

Zheng is a member of Editorial Advisory Board of IEEE Spectrum and a visiting chair professor at Shanghai Jiao Tong University. He has served as chair on 10 prestigious international conferences—most recently, as the program co-chair of ICDE 2014 (Industrial Track). He has been invited to give over 10 keynote speeches at international conferences and forums (for example, IE’14 and APEC 2014 Smart City Forum) and guest lectures in universities like Massachusetts Institute of Technology (MIT), Carnegie Mellon University (CMU), and Cornell. In 2013, he was named one of the Top Innovators Under 35 by MIT Technology Review (TR35) for his research on using data science to solve urban challenges. He was featured by Time Magazine due to his research on urban computing in November 2013.

Ming Zhou

Dr. Ming Zhou is a principal researcher and manager of the Natural Language Computing Group (NLC) at Microsoft Research. He graduated from Chongqing University in 1985. He received his PhD in Computer Science and Engineering from Harbin Institute of Technology in 1991. He was a post-doctorate researcher at Tsinghua University during 1991–1993, he then joined the faculty of Tsinghua University as an associate professor in 1993. He visited Kodensha Ltd., a famous machine-translation software maker in Japan during 1996–1999 to lead the R&D on Chinese-Japanese machine translation. Dr. Zhou joined Microsoft Research in 1999 as researcher and became the manager of the NLC Group in 2001. He concurrently was the manager of Speech Group in 2004. His primary research interests lie in the development of advanced and practical technologies of natural language processing (NLP) such as syntactic and semantic parser, text mining, machine translation, question-answering, chatbot, summarization, knowledge base, and computer poetry. He has also focused on applying developed NLP technologies to solve difficult problems in human-computer interaction, spoken translator, search engine, mobile assistant, online advertisement, and online education.

Dr. Zhou has published over 100 papers at top conferences (ACL, COLING, SIGIR, KDD, EMNLP, IJCAI, AAAI, WWW) and in journals, and served as an area chair and PC chair for many NLP conferences and a member of the editorial board of the Journal of Computational Linguistics, Journal of Machine Translation, and ACM Transactions on Asian Language Information Processing. As his PhD research topic at Harbin Institute of Technology, he invented the first Chinese-English machine translation system (CEMT) in China in 1989. During his visit at Kodensha Ltd., he designed the famous Chinese-Japanese machine translation software product, J-Beijing, which was shipped in Japan in 1999. It was also deployed in J-Server, a well-received popular machine translation service which later won the Makoto Nagao Award in 2008. He is the principal inventor and research leader of many products and technologies including the famous computer Chinese Couplets system, Chinese-English machine translation system, IME for Chinese and Japanese, Bing Dictionary (also known as Engkoo Dictionary), Engkoo Question-Answering System, and QuickView tweet text mining and search system. Under his leadership, the NLC group made outstanding contributions to Microsoft products including Windows, Bing, and Office with NLP technologies. Bing Dictionary received the Wall Street Journal Asian Innovation Award: Reader’s Choice in 2010. Dr. Zhou has profound collaboration with partners in many universities. He is a PhD supervisor at Harbin Institute of Technology, Tianjin University, Nankai University, and Shandong University. He was the co-director of the Microsoft-HIT Joint Lab on NLP and Speech from 2000 to 2008 and has been the co-director of the Microsoft-Tsinghua Joint Lab on Media and Network since 2008. He received the Ability Award from Microsoft CEO Satya Nadella in 2014 to recognize his outstanding contribution to the Kinect-based sign language translator, an influential collaboration with the China Academy of Sciences.

Conghui Zhu

Dr. Conghui Zhu, supervisor of master students, was awarded his doctoral degree in computer science from Harbin Institute of Technology in 2009. The same year, he joined the computer science and technology school as an assistant professor. His research focuses on natural language processing and machine translation. He has published several papers in ACL, COLING, and EMNLP. His research about pivot translation received support from the National Natural Science Foundation of China in 2012 and he visited the Japanese National Institute of Information and Communications Technology as a visiting scholar in 2013. In IWSLT2012 translation track Olympic task, his team got the first rank. In 2005, while still a PhD student, he visited Microsoft Research Asia for an internship and publish his first paper in ACL. As the main participant of the Chinese minority ethnic language translation projecthe releases some basic NLP toolkits to build high quality parallel sentence pairs and helps train Uygur students to grasp the machine translation method.

Jun Zhu

Dr. Jun Zhu is an associate professor in the Department of Computer Science and Technology at Tsinghua University. His principal research interests lie in the development of statistical machine learning methods for solving scientific and engineering problems arising from artificial and biological learning, reasoning, and decision-making in the high-dimensional and dynamic worlds. Prof. Zhu received his Ph.D. in Computer Science from Tsinghua University in 2009. Before joining Tsinghua in 2011, he did post-doctoral research in the Machine Learning Department at Carnegie Mellon University. His current work involves both the foundations of statistical learning, including theory and algorithms for probabilistic latent variable models, sparse learning in high dimensions, Bayesian nonparametrics, and large-margin learning; and the application of statistical learning in social network analysis, data mining, and multi-media data analysis.

Prof. Zhu has published over 50 peer-reviewed papers in the prestigious conferences and journals, including ICML, NIPS, KDD, JMLR, PAMI, etc. He is an associate editor for IEEE Trans. on PAMI. He served as Area Chair for approximately 10 top-tier conferences, including ICML (2014, 2015), IJCAI (2013, 2015), UAI 2014, and NIPS 2013. He was a local co-chair of ICML 2014. He is a recipient of the CCF Distinguished PhD Thesis Award (2009), Microsoft Fellowship (2007), IEEE Intelligent Systems “AI’s 10 to Watch” Award (2013), NSFC Excellent Young Scholar Award (2013), and CCF Young Scientist Award (2013). His work is supported by the “221 Basic Research Plan for Young Talents” at Tsinghua University.

Yanmin Zhu

Yanmin Zhu is an associate professor with the Department of Computer Science and Engineering at Shanghai Jiao Tong University. Prior to joining Shanghai Jiao Tong University, he was a research associate with the Department of Computing at the Imperial College London. He received his Ph.D. from the Department of Computer Science and Engineering at the Hong Kong University of Science and Technology (HKUST) in 2007, and earned his bachelor degree in Computer Science from Xi’an Jiao Tong University in 2002.

His research interests include wireless sensor networks, vehicular ad hoc networks, mobile computing, and participatory sensing. He has published over 100 papers in international conference and peer-reviewed journals, including prestigious conferences such as IEEE International Conference on Computer Communications (INFOCOM), IEEE International Conference on Distributed Computing Systems (ICDCS), ACM International Conference on Mobile Systems, Applications, and Services (MobiSys), and top journals such as IEEE Journal on Selected Topics on Communications (JSAC), IEEE Transactions on Mobile Computing (TMC), and IEEE Transactions on Parallel and Distributed Systems (TPDS). He is a recipient of two Best Paper Awards. He has served on program committees of many computer networking and communications conferences, such as INFOCOM, ICDCS, GlobeCom, and ICC. He is a member of IEEE and ACM.

Abstracts

Thursday, October 30, 2014

Computational Thinking in the Sciences and Beyond

Speaker: Jeannette Wing, Corporate Vice President, Microsoft Research

My vision for the twenty-first century: computational thinking will be a fundamental skill used by everyone in the world. To reading, writing, and arithmetic, we should add computational thinking to every child’s analytical ability. Computational thinking involves solving problems, designing systems, and understanding human behavior by drawing on the concepts that are fundamental to computer science. Thinking like a computer scientist means more than being able to program a computer. It requires the ability to abstract and thus to think at multiple levels of abstraction.

Computational thinking has already influenced many disciplines, from the sciences to the arts. In my talk, I will give examples from Microsoft Research of how computational thinking has changed the way research is conducted in different scientific disciplines. Computational thinking has also changed what we teach in colleges and universities today. I will speak about some recent educational efforts in the United States, the United Kingdom, and China on adopting computational thinking in education, especially at the K-12 level. Computational thinking can not only inspire future generations to enter the field of computer science—it can also benefit people in all fields.

The Demand for New Knowledge and Interdisciplinary Education at Yonsei University

Speaker: Kap-Young Jeong, President, Yonsei University

Yonsei University is leading change in Asia’s higher education by responding dynamically to educational and market trends and by serving as the vanguard in research, education, and industry ties. Interdisciplinarity is gaining momentum as a keyword because our complex, information-rich society requires flexible thinking and an ability to adapt to new input that depends on knowledge across disciplines and on an ability to process various different kinds of information. Although existing structures within universities can pose obstacles, Yonsei supports interdisciplinarity as the direction of the future and is promoting new programs in education, research, and campus infrastructures toward this end.

Interdisciplinarity poses challenges for universities because faculty and programs are configured along lines of existing departments, fields, and disciplines. Faculty and sometimes students can be resistant to programs that are unfamiliar or that change existing patterns of funding, research, or teaching. At Yonsei University, we are implementing institutional change that promotes interdisciplinarity. For one, we are promoting liberal arts education, which by nature promotes critical thinking and emphasizes tools over content, in the process deemphasizing majors or fields of study. Our innovative Residential College program for all freshmen at our International Campus, launched in 2014, includes a holistic education program that promotes the whole individual. Yonsei’s Underwood International College, which launched 10 years ago as Asia’s premier liberal arts college, is expanding its offerings of interdisciplinary majors across all disciplines.

On the research front, Yonsei University established the ICONS (Institute of Convergence Sciences) in 2013, which consolidated existing research centers and provided an incentive for the formation of interdisciplinary research terms drawing on faculty from diverse fields. The Institute for Convergence Technology, as well as its undergraduate, masters, and doctoral programs in the School of Integrated Technology, aims to produce a new kind of interdisciplinary-thinking young professional. On the administrative side, we are actively promoting information- and resource-sharing among our various campuses, including the main Shinchon campus, the Wonju campus, Severance Medical School, Gangnam Severance, and Songdo International campus.

Panel Discussion: Fostering Interdisciplinary Talents

We are used to segmenting a university by disciplines. When more academic problems require cross-disciplinary collaboration, we may have to reconsider the current system in higher education.

Panelists:

  • Professor Peng Gong, Professor of Tsinghua University, an ecologist
  • Professor Kap-Young Jeong, President of Yonsei University, an economist
  • Professor David S. Rosenblum, Professor of National University of Singapore, a computer scientist
  • Dr. Jeannette Wing, Corporate Vice President of Microsoft Research, a computer scientist

Moderator:

  • Dr. Tim Pan, University Relations Director of Microsoft Research Asia

Computer Vision: New and Renewed Opportunities

Speaker: Takeo Kanade, Professor, Carnegie Mellon University

The field of artificial intelligence has been working on computer vision—making computers able to see—since its inception. Although it is easy for humans, computerized visual recognition is much harder to achieve than originally thought. However, today computer vision technologies are expanding to many applications, some newly conceived and others with old goals but with an order of magnitude better performance. These range from applications used in daily life, such as wearable vision, to applications for medical, industrial, and scientific visual computing. Computer vision technologies are benefiting from recent advancements in microelectronics for vast processing, image sensors for capturing tiny signals, and fundamental algorithms to make sense out of visual data. Starting with some historical perspectives, the talk will discuss exciting opportunities in computer vision.

Hints and Principles for Computer System Design

Speaker: Butler W. Lampson, Technical Fellow, Microsoft Research

I have many hints that are often helpful in designing computer systems, and I also know a few principles. There are several ways to organize them:

  • Goals (what you want)—simple, timely, efficient, adaptable, dependable, yummy
  • Methods (how to get it)—approximate, increment, iterate, indirect, divide and conquer
  • Phases (when to apply them)—requirements, architecture, process, techniques

Of course the goals are in conflict, and engineering is the art of making tradeoffs, for instance among features, speed, cost, dependability, and time to market. Some simpler oppositions are:

  • For adaptable, between evolving and fixed, monolithic and extensible, scalable and bounded
  • For dependable, between deterministic and non-deterministic, reliable and flaky, consistent and eventual
  • For incremental, between indirect and inline, dynamic and static, experiment and plan, discover and prove

It also helps to choose the right coordinate system, just as center of mass coordinates make many dynamics problems easier. You can view the system state as a name→value map, or as an initial state and a sequence of operations that transform the state. You can view a function as code or as a table or as a sequence of partial functions. Notation, vocabulary, and syntax are other kinds of coordinates.

In the complex process of designing systems, both principles and hints can be justified only by examples of what has worked and what has not.

Computational Ideas and the Theory of Evolution

Speaker: Christos H. Papadimitriou, Professor, UC Berkeley

Covertly, computational ideas have influenced the Theory of Evolution from the very start. After providing a historical overview, I will discuss recent work on evolution that was inspired and informed by computational insights. Considerations about the performance of genetic algorithms led to a novel theory of the role of sex in evolution based on the concept of mixability, while the equations describing the evolution of a species can be reinterpreted as a repeated game between genes played through the multiplicative updates algorithm. Finally, a theorem on Boolean functions helps us understand better mechanisms for the emergence of novel traits.

Interdisciplinarity: A View from Theoretical Computer Science

Speaker: Andrew Yao, Professor, Tsinghua University

Computer science is generally regarded as an enabling science with wide applications to other scientific fields. Increasingly, the concepts and methods of computer science are being recognized as a source of great intellectual interest, injecting fresh ideas into other scientific disciplines. Through discourses and collaborations, exciting multidisciplinary areas are blossoming. We illustrate this phenomenon from the viewpoint of theoretical computer science.

Panel Discussion: Interdisciplinarity: the Future of Computer Science?

The field of computer science is undergoing a fundamental change. Traditional areas of computer science have been concerned with the efficiency, reliability, and scale of computer systems, attempting to make them more practical and useful—in short, to make them “work.” Traditional topics of computer science—operating systems, algorithms, databases, programming languages, and so forth—were the primary focus areas, meanwhile fully supported by theoretical computer science that developed the necessary mathematical and algorithmic foundations. Instead, modern computer science has put an increased emphasis on the processing and analysis of real-world data sets (big data) and interdisciplinary research, reaching out into areas such as economy, biology, physics, and social sciences.

Panelists:

  • Takeo Kanade, Professor, Carnegie Mellon University
  • Butler W. Lampson, Technical Fellow, Microsoft Research
  • Christos H. Papadimitriou, Professor, UC Berkeley
  • Andrew Yao, Professor, Tsinghua University

Moderator:

  • Thomas Moscibroda, Senior Researcher of Microsoft Research Asia and Chair Professor of Tsinghua University

Friday, October 31, 2014

Urban Science in the Cloud

Rapid global urbanization has generated great challenges, such as traffic congestion, noise, air pollution, and energy overconsumption. The field of Urban Science aims to help tackle these challenges, a task that seemed nearly impossible years ago given the complex and dynamic settings of cities. Data sensing technologies and social media have recently made it possible to accrue urban data from many sources, including human mobility, air quality, traffic patterns, and more geographical data. Cloud computing is now seen as a critical analysis tool for researchers in this field.

What can we do with environmental data? Why are we interested in human life patterns? How does cloud technology facilitate urban computing? In this session, we bring together researchers who are targeting different urban issues to discuss their ideas and discoveries. Microsoft researchers from Redmond will also share their latest efforts on the Lab of Things, a flexible platform for experimental research that uses connected devices and cloud services to monitor and update experiments and provide easy access to collected data.

Chair: Winnie Cui, Microsoft Research Asia

Speakers:

  • Yu Zheng, Microsoft Research Asia
  • Hwasoo Yeo, Korea Advanced Institute of Science and Technology
  • Victor Li, The University of Hong Kong
  • Yanmin Zhu, Shanghai Jiao Tong University
  • Takeshi Oishi, The University Of Tokyo
  • Guangzhong Sun, University of Science and Technology of China
  • Arjmand Samuel, Microsoft Research

Urban Computing: Using Big Data to Solve Urban Challenges

Speaker: Yu Zheng, Microsoft Research Asia

Urban computing is a process of acquisition, integration, and analysis of big and heterogeneous data generated by a diversity of sources in urban spaces to tackle the major issues that cities face, such as air pollution, energy consumption, and traffic congestion. Urban computing connects unobtrusive and ubiquitous sensing technologies, advanced data management and analytics models, and novel visualization methods to create win-win-win solutions that improve urban environment, human life quality, and city operation systems. In this talk, I will present our recent progress in urban computing, introducing the applications and technologies for integrating and deep mining heterogeneous data. Examples include fine-grained air quality inference throughout a city, city-wide estimation of gas consumption and vehicle emissions, and diagnosing urban noises with big data. The research has been published at prestigious conferences, such as KDD, and deployed in the real world. Learn more.

Real-Time Urban Travel Time Prediction Using KNN and Online Traffic Simulator in the Microsoft Cloud System

Speaker: Hwasoo Yeo, Korea Advanced Institute of Science and Technology

As the data from the roadway increases with the level of traffic congestion, prediction of travel time is emerging as the most wanted information for roadways users. It provides predicted travel times for each origin-destination pair and can suggest the best departure time to guarantee on-time arrival. In this research, we developed and implemented real-time systems to predict travel time by using the Microsoft Azure cloud. We adopted a data-driven approach that uses historic traffic sensor data to find the pattern that is most similar to the current real-time data, providing accurate prediction results with higher accuracy. The newly developed matching strategy provides a robust result with a longer horizon of prediction. We also developed a data-driven OD prediction methodology and online traffic simulator based on Cell Transmission Model, which can be used for the prediction of travel time for special cases of events with diverse scenarios. The research can be applied for the nation-scale system for travel time prediction and simulation.

Enabling Causality-Based Air Quality Monitoring with Urban Big Data

Speaker: Victor Li, The University of Hong Kong

Air quality has deteriorated rapidly in Hong Kong and China, with NO2 and PM2.5 levels frequently exceeding WHO safety guidelines. Although poor air quality has clear public health impacts, very few monitoring stations measure major air pollutants; there are only 13 monitoring stations in Hong Kong and 35 in Beijing. This severely limits evidence-based decision-making about air quality and leads to severe criticisms about the transparency and public relevance of the official Air Pollution Index.

Because air pollution is highly dependent on location, and monitoring stations are costly and bulky, a citywide air quality monitoring system would be prohibitively expensive. Urban big data can be used to fill this gap. By analyzing the causality between human dynamics data (such as vehicular traffic and points of interest data) and measured air quality, we can estimate air quality at locations not covered by monitoring stations. However, processing the massive volume of data poses another challenge. To overcome this challenge, we note that most of these data are spatially and temporally correlated. Our approach is to exploit such spatio-temporal (S-T) correlation to process “part” of the data instead of “all” of the data. We detect, measure, quantify, and visualize causalities between various urban dynamics data and air quality. Causalities can be expressed in a probabilistic manner spatially and temporally. Furthermore, we exploit parallel computing by separating and allocating relatively independent data blocks to different computing resources, based on causality measures. In this way, time efficiency and scalability can be achieved. Our approach will be illustrated by using data from Shenzhen, China.

To Feel the City’s Pulse with Mobile Crowd Sensing

Speaker: Yanmin Zhu, Shanghai Jiao Tong University

The city where we live is facing increasing challenges, such as pollution, traffic congestion, and noise. Taking the city’s pulse is to monitor the urban dynamics, and this enables people to live a better life in the city. Thanks to rapid development of the mobile Internet and various mobile devices such as smartphones, vehicles, and smart watches, mobile crowd sensing presents a new paradigm of large-scale sensing data collection. The salient features of mobile crowd sensing include the large number of data sources, large coverage, inherent node mobility, and low deployment cost. This talk discusses the basic approach of mobile crowd sensing for monitoring urban dynamics. Several mobile crowd-sensing examples will be discussed, including urban road traffic monitoring with floating vehicles, map updating with vehicular GPS traces, and urban noise monitoring with noise data from smartphones.

Environmental Modeling and Visualization System for Eco-Friendly Behavior in Urban Traffics

Speaker: Takeshi Oishi, The University Of Tokyo

To help reduce CO2 emission from road traffic, we have constructed a system that prompts people to adopt eco-friendly travel behavior by modeling and showing regional traffic. The traffic flow is modeled by using street-side cameras, and CO2 emissions in regional areas are estimated by traffic simulations. The CO2 emissions are visualized with VR/MR technologies and accordingly reduced by eco-friendly behaviors. Currently, we are developing 3D city modeling techniques for more accurate traffic simulations. In this presentation, we introduce our projects in urban scenes.

Build Smart Campus Based on Human Behavioral Data

Speaker: Guangzhong Sun, University of Science and Technology of China

In recent years, real-world data reflecting campus life has become widely available, including users’ smart card records, mobile phone signals, GPS traces, data from cameras, and data from several management information systems. As a result, we are ready to carry out real campus computing activities that lead to a better and smarter campus. By better sensing and understanding the users on campus, we are more likely to design effective strategies and intelligent systems for improving life in campus areas. In this talk, I will present some of our research and practical works on the campus of University of Science and Technology of China.

Deploying Connected Devices for Research

Speaker: Arjmand Samuel, Microsoft Research

An increasing number of research areas rely on collecting data from sensors and devices deployed where people live, work, and play. Researchers typically deploy sensors and devices in a few homes or workspaces, collect data, analyze the data, and make interesting inferences based on this data. Healthcare and energy management are two examples of such areas. To have confidence in the research findings, it is desirable to collect sufficient data from a large numbers of locations and in a variety of different situations and locales. However, doing so requires major investment in engineering expertise and technology infrastructure—both not readily available to the academic community.

The Microsoft Research Lab of Things aims to provide such an infrastructure to facilitate at-scale in-situ research in a number of research areas. After its initial release in July 2013 and subsequent updates, Lab of Things is now being used in a variety of research domains. In this session, we will introduce the design philosophy behind the Lab of Things, and provide an overview of its current deployments. This session is aimed at academic researchers from diverse research areas, including healthcare, energy management, sensor design, data analysis and visualization, privacy, and system architecture design.

Computing in Science

The sciences are currently undergoing a fundamental transition due to the avalanche of data that is generated by instruments, simulations, online archives, and social media. The impact of this data revolution is seen in every discipline. Cloud computing was invented to manage the big data challenges of Internet companies, but it is now seen as a critical tool for many research communities. Cloud computing makes it much easier to accrue data from many sources and to make it available for analysis by large communities.

This session will feature academic researchers who have used cloud computing for science research projects. We highlight five projects from around the Asia region. We will also look into science research tools, new tools for machine learning, and data analysis in the cloud that we have recently made available to the community.

Chair: Miran Lee, Microsoft Research Asia

Speakers:

  • Zheping Xu, Chinese Academy of Sciences
  • Tai-Quan Peng, Nanyang Technological University
  • Huayi Wu, Wuhan University
  • Hyunju Lee, Gwangju Institute of Science and Technology
  • Jun Zhu, Tsinghua University
  • Junsheng Hao, Shanghai Yungoal Info Tech Co., Ltd.

Biodiversity Monitoring Based on Cloud Environment and Citizen Science

Speaker: Zheping Xu, Chinese Academy of Sciences

We are experiencing the sixth mass extinction of plants and animals, and an effort is needed to protect the biodiversity of our planet. In addition to the information available from specimens and observations, there is a significant amount of information about the temporal distribution of species that can be extracted and processed from scientific literatures. However, this requires a high-performance environment to store and process the huge amounts of data, including more than 100 million records on 40 million pages. More real-time biodiversity data can be obtained from the websites of journals, news, botanical gardens, protected areas, and the communities of citizen science. This information should be integrated, analyzed, and displayed in a cloud environment that enables external users to interact with it. There are also some new techniques that should be introduced, including machine learning, natural language processing, and GIS.

Visual Analysis of Topic Coopetition on Social Media

Speaker: Tai-Quan Peng, Nanyang Technological University

Big data is of the people, by the people, and for the people. But data could not speak for itself. The interdisciplinary collaboration between computer scientists and social scientists helps restore silent data into dynamic interaction between social topics. This project aims to examine how social topics cooperate and compete with each other to gain public attention, and to uncover what kind of factors will affect the cooperation and competition (jointly called “coopetition”) between social topics. Building on classical agenda-setting theory in communication research, the project proposes a visual analytics system that can facilitate panoramic and in-depth analysis of topic coopetition on social media. We model the complex interaction among topics as a combination of carry-over, coopetition recruitment, and coopetition distraction effects. The mathematical model provides a close functional approximation of the coopetition process by depicting how different groups of influential users (that is, topic leaders) affect coopetition. We also design EvoRiver, a time-based visualization, which allows users to explore coopetition-related interaction and to detect dynamically evolving patterns, as well as their major causes. We test our model and demonstrate the efficiency of our system based on two Twitter datasets (social topics data and business topics data).

Collaborative Exercitation of Geography Course Supported by Geospatial Service Web

Speaker: Huayi Wu, Wuhan University

With the advancement of sensors and information technologies, a large amount of geographical information resources (GIRs)—including geodata, algorithms, application, and models—have become available on the Internet for public use. However, the heterogeneous nature and complexity of the Internet environment make it a challenge for people to discover distributed online GIRs efficiently and utilize them intuitively. GeoSquare is collaborative GeoProcessing framework designed to tackle this urgent problem by adopting Microsoft technologies. Through building a platform with integrated functions (for example, GIRs publishing and GeoProcessing orchestration), GeoSquare can help researchers and teachers share and utilize online GIRs in an efficient, harmonious way. Specifically: (1) Rich Internet Applications (RIA) technologies enrich web user interaction, (2) Azure-based cloud platform provides elastic and unlimited computing and storage resources, and facilitates global load-balancing, and (3) web service composition and scientific workflow technologies enable the online GeoProcessing orchestration and help integrate dispersed GIS functions collaboratively.

DigSee: Text Mining for Identifying Disease-Gene-Biological Events Relationships

Speaker: Hyunju Lee, Gwangju Institute of Science and Technology

This talk presents an extended version of DigSee, a disease gene search engine with evidence sentences. Biological events such as gene expression, regulation, phosphorylation, localization, and protein catabolism play important roles in the development of diseases. Understanding the association between diseases and genes can be enhanced with the identification of biological events involved in this association.

Biological knowledge has been accumulated in several databases and can be accessed over the web, but there is no specialized web tool that enables a query into the relationships among diseases, genes, and biological events. For this task, we developed DigSee to search Medline abstracts for evidence sentences describing that `genes’ are involved in the development of ‘disease’ through `biological events.’ Previously, DigSee supported only cancer; now we are working to extend it to all diseases. The number of abstracts to be processed increased from 2,056,082 for cancer to 17,282,190 for all diseases, and the components that require major computational resources include crawling from PubMed, gene symbol extraction, gene normalization, and event extraction. In this talk, we will focus on extending DigSee to all diseases, including nervous system disease and cardiovascular diseases, by using Microsoft Azure. DigSee is available at gcancer.org/digsee.

Social Media Mining with Machine Learning Methods

Speaker: Jun Zhu, Tsinghua University

The growth of social media over the last decade has revolutionized the way humans interact and industries conduct business. Social media appears in many forms, including blogs, micro-blogs, forums and message boards, social networking sites, wikis, social bookmarking, tagging and news, writing communities, photo/video-sharing sites, and instant messaging. Machine learning techniques provide researchers and practitioners with the tools they need to analyze large, complex, and frequently changing data. In this talk, I will give a brief overview of social media mining, an interdisciplinary field that applies machine learning tools to social media data. I will highlight some illustrative examples done in my group, including social behavior analysis, social link prediction, and large-scale social topic graph visualization.

The Power of Azure Machine Learning

Speaker: Junsheng Hao, Shanghai Yungoal Info Tech Co., Ltd.

Machine learning–training computer systems with historical data to predict future trends or behavior–is used in diverse applications, and more applications are being devised every day. Search engines, online recommendations, ad targeting, virtual assistants, demand forecasting, fraud detection, spam filters—machine learning enables all these modern services.

In this presentation we will:

  1. Understand the power of Azure cloud-based predictive analytics through a short case study on language auto-detection.
  2. Demonstrate how to create a simple experiment by using Microsoft Azure Machine Learning Studio.
  3. Walk through the overall process of developing a predictive solution by using Microsoft Azure Machine Learning.

New Age of Interaction: Computer and Human

Computers play a major part in almost every aspect of our lives today, from the controls that let us drive our cars to our interactions with friends through social networks to health monitoring on smartphones. Sensors are now more capable, computation is cheaper and more powerful, and user interfaces are more sophisticated. Such advances have developed new human and computer interaction technologies such as the Microsoft Kinect sensor. When we look at the education space, such new technologies advance us to the next level of productivity in study and work. Meanwhile, black-boxed technology raises a new challenge, in that fewer students today are interested in computers and programming.

This session will invite academic researchers to introduce their cutting-edge research in the field of Human Computer Interaction (HCI), such as tele-manipulation and tele-operation, second language learning, and minority language translation—providing us with some insight into the next frontier of HCI-related research. The second part of this session focuses more on educational aspects. We will introduce an interesting story of the universe of computing, new trends of programming, and a powerful authoring tool of MOOCs type of contents.

Chair: Noboru Kuno, Microsoft Research Asia

Speakers:

  • Jeha Ryu, Gwangju Institute of Science and Technology
  • Sangyoun Lee, Yonsei University
  • Hiroyuki Kajimoto, University of Electro-Communications
  • Hao-Chuan Wang, National Tsing Hua University
  • Conghui Zhu, Harbin Institute of Technology
  • Darren Edge, Microsoft Research Asia
  • Kangping Liu, Microsoft Research Asia
  • Judith Bishop, Microsoft Research

Visual-Haptic Interactive Telepresence

Speaker: Jeha Ryu, Gwangju Institute of Science and Technology; Sangyoun Lee, Yonsei University

Telepresence is humanity’s long dream. Imagine that your child is studying in a foreign country, or that you are busy working at the office but your elderly parent is in a hospital bed or is at home waiting for your visit. You want to see your child or parent, and want to hear his or her voice. As a very close family member, you may even want to touch your child’s face, or hold your parent’s hand.

These desires encourage us to develop a truly interactive telepresence technology that involves real people over networks. The dream can be realized by using many recent technological advances, including very fast Internet that can connect anybody, anytime, anywhere in the world. This talk will present and demonstrate a tele-immersive environment that takes into account both haptic handshaking and visual eye contact. The environment has been created by developing a physical human-like avatar that has a handshaking robotic arm/hand and an accurate face pose correction algorithm with multiple cameras. The handshaking robotic arm/hand can provide various haptic sensations, such as shaking forces, hand grip pressures, and temperature while handshaking over any networks by developing a robust haptic tele-manipulation technique that can overcome time-varying natures and uncertainties in the networks and humans. In addition, to achieve realistic eye contact, an accurate face pose estimation algorithm was developed, and the texture of face was then reconstructed and rendered based on the estimated pose information. In the talk, a live demo of the system will be provided between two different locations, in China and South Korea.

Whole-Body Haptic Interaction

Speaker: Hiroyuki Kajimoto, University of Electro-Communications

Recent advances of the natural user interface facilitate the use of the whole body as a canvas for haptic interaction. This talk focuses on three major topics of the whole-body haptic interactions: how whole-body haptics enrich reality, how they affect feeling of presence and emotion, and how they induce real motion or feelings related to motion.

Using Kinect to Study the Role of Hand Gestures During Conversations

Speaker: Hao-Chuan Wang, National Tsing Hua University

Human communication is more than speaking, and it often involves the use of multiple communication channels, both verbal and nonverbal. A scalable and reliable method to capture and analyze hand gestures as part of communication can help advance the research of interpersonal communication and the design of communication tools. In this project, we propose a way, including experimental setup and analytical techniques, to leverage the skeleton tracking capability of Kinect for studying the role of hand gestures during conversations. We demonstrate the utility of our approach through a media comparison study, showing that we can verify how different communication media (face-to-face, video, audio) affect the number of gestures that people produce and the similarity between interlocutors’ gestures. We foresee broad applications, including fast usability testing of new communication tools in the field and investigation of communication processes in situations where nonverbal behaviors may play a more salient role, such as cross-lingual communication and language tutoring.

Building Communication Bridges for Chinese Minority Ethnic Languages: An Efficient Translation Framework Based on Microsoft Translator Hub

Speaker: Conghui Zhu, Harbin Institute of Technology

Asymmetry of information interactions is one of the most important determining factors in economic and cultural imbalance in different areas. In China, there are 56 ethnic groups, more than 80 languages, and about 30 different characters. Most languages have not been supported by major translation providers yet. This limits the access that Chinese minority ethnic groups have to global information and knowledge.

Chinese minority ethnic languages present several additional problems compared with the current Chinese-English statistical machine translation (SMT) methods. First, SMT is a data-driven method, while most of these languages do not have enough training data, not to mention the high-quality parallel corpus. Second, there are almost no related basic NLP (natural language processing) toolkits supported. Last, the training progress of a practical SMT system needs huge computation that a small laboratory can’t handle. We want to build a simple but efficient translation framework for Chinese minority ethnic languages that can build a complex SMT system in an easy way.

With help of Microsoft Research Asia, we found Microsoft Translator Hub, which meets our requirement exactly. Its minimum input is just parallel sentences, which don’t need any processing of NLP basic toolkits. By using Microsoft Translator Hub, you can build an easy translation system as long as you annotate parallel sentence pairs. Furthermore, all computation (training, testing, and deploying) is carried out on a Microsoft server, so even a mobile phone can finish the operations of building an SMT system fluently.

To train a more efficient system, many tiny but useful things need to be done. For example, Translator Hub is designed for general language translation, and there are some conflicts between minority ethnic languages and Translator Hub that must be solved. We will need to redevelop some basic NLP toolkits of minority ethnic languages to produce high-quality parallel data. Our goal is to smoothly translate various minority ethnic languages into English, and vice versa. Uygur is the first language supported by our platform, and the performance of the Uygur-Chinese translation system based on Translator Hub is comparable to famous open source translation software. We hope that more people will join us as we develop more and better Chinese minority ethnic languages translation systems.

Speaker Support: Activity-Based Tools for Presentation Authoring and Language Learning

Speaker: Darren Edge, Microsoft Research Asia

Many activities of work and life are mediated by interpersonal communication. Some forms of communication, however, are sufficiently demanding that they require significant levels of advance planning and preparation. Two examples of such auxiliary activities are preparing to deliver a presentation and learning to speak a second language. In this talk, I will show how research projects from the Microsoft Research Asia HCI research group have transformed both of these activities for the better, by helping people resume their chosen activity more easily, use their preparation time more efficiently, and learn to communicate more effectively.

Office Mix: Online Lessons Made Simple

Speaker: Kangping Liu, Microsoft Research Asia

The availability of high-quality education is widely acknowledged as the pathway to success in modern society. In the past few years, there has been a tremendous interest in the use of MOOCs, SPOCs, flipped classrooms, and blended-learning to provide more scalable and affordable models for student learning. However, it is still hard to author interactive online lessons, and only a small fraction of faculty members create or use them. This session will introduce Office Mix, a brand new offering from Microsoft that dramatically simplifies the creation of such online lessons, including their publishing and sharing, and associated analytics. Office Mix builds on the familiarity of faculty and students with PowerPoint to create such lessons, enabling them to use the slide decks that they already have. We will also discuss use cases beyond online learning, such as sharing and communication of academic research.

The Software and Data Challenges of Games for Coding

Speaker: Judith Bishop, Microsoft Research

When learners perceive it as fun, learning to code is more effective and sustainable. Code Hunt uses puzzles that players explore by means of clues presented as test cases. Players iteratively modify their code to match the functional behavior of secret solutions. Through a sequence of puzzles of increasing difficulty, players can learn to code or improve their coding skills. Code Hunt can also be used for contests; it was part of Microsoft Beauty of Programming in the GCR 2014. Code Hunt is used by hundreds of thousands of people, and at such a scale, the game presents challenges in keeping puzzles refreshed, analyzing statistics, and ensuring fairness. In this talk I’ll discuss the architecture of Code Hunt and present figures of usage across different kinds of puzzles and their effect on player retention and success. Finally, I’ll show encouraging figures that the game is indeed attractive for both genders.

DemoFest

 

Booth Title and Description Presenters
1 Exploiting Mobile Crowd Sensing for Fine-Grained Urban Noise Mapping

This fine-grained noise mapping service allows users to access the noise level of any physical location in an urban environment at any time. This is valuable for proactive reduction of exposure to excessive noise. This demonstration will feature a fine-grained urban noise mapping service that is built on mobile crowd sensing. An urban environment is divided into virtual grids, and mobile smartphones are distributed in the urban area to sample environmental noises. The sampled noise data are gathered at the noise-mapping server that resides in the cloud. By aggregating the noise samples of the smartphones following the same grid, we estimate the noise level of the grid. A mobile app has been developed for measuring environmental noises with the smartphone microphone. The salient features of this noise mapping approach include low deployment cost, wide coverage, fine granularity, and real-time update.

Yanmin Zhu, Shanghai Jiao Tong University
2 Smart Campus Building in USTC

Our vision is to build a smart campus that is powered by big data. This demo shows how we utilized different sources of campus data, as well as students’ footprints on a social network, to provide humanity care to students at the University of Science and Technology of China (USTC). By analyzing shopping and check-in records captured by smart card, we detect students who are poor to provide them a monthly subsidy. Combining this data with school email, library data, and data from social networks, we can reconstruct an individual student’s lifestyle, such as when they sleep and whether they have breakfast regularly. We built a website to show personal statistics and life data and to provide specific recommendations to students. We also developed a series of cross-platform mobile applications, such as campus map and bus schedule, to help freshmen quickly get used to university life.

Guangzhong Sun, University of Science and Technology of China
3 Detecting Urban Black Holes from Traffic Data

The traffic flow on urban road networks and subway systems can be modeled as a spatio-temporal graph (STG). An STG is a directed graph in which vertices and edges are associated with spatio-temporal properties. In this poster, we detect interesting phenomena, titled black holes and volcanos, from an STG. Specifically, a black hole is a subgraph (of an STG) that has the overall inflow greater than the overall outflow by a threshold, while a volcano is a subgraph with the overall outflow greater than the overall inflow by a threshold. In our method, we build an STG index to maintain the spatio-temporal properties of an STG. Based on the index, we propose a two-step black hole detection algorithm. The first step identifies a set of candidate grid cells to start from, and the second step expands an initial edge in a candidate cell to a black hole and prunes other candidate cells after a black hole is detected. Then, we adapt this detection algorithm to a continuous black hole detection scenario. We evaluate our method based on real GPS trajectories of 33,000 taxis and the Beijing road network, finding traffic anomalies and regular travel patterns in the city.

Lei Zou, Peking University
4 BIGKDD: Big Data Analytics on the Cloud

In the era of big data, the explosion of data raises many challenges and brings plenty of opportunities for data-driven research and applications. In this project, we investigate BigKDD, a comprehensive web-based platform for conducting scalable data analytics on the cloud. It includes most features offered by popular data mining packages, like WEKA and Mahout. Further, all the services are cloud-based, thus eliminating the need for expensive resources such as data storage and powerful machines. Through BigKDD, users can upload their data to the cloud (even via URLs), execute several preprocessing techniques, and perform sophisticated data analytics and visualization for finding meaningful patterns. At the backend, the algorithms from the WEKA library are used to process small-scale data sets, while Mahout with Hadoop-based distributed computing architectures is used for large-scale data analytics.

Steven C.H. Hoi, Singapore Management University
5 Large-Scale 3D City Reconstruction from Photographs

This demo shows our most recent approach to large-scale 3D reconstruction of cities for 3D mapping applications. The demonstrated results are fully automatically computed through a cluster of personal computers given the intensive computational resources required.

Long Quan, Hong Kong University of Science and Technology
6 msMission: A Mobile-Based Spatial Crowdsourcing Platform

In this demo, we will introduce msMission, a mobile-based spatial crowdsourcing platform. The platform features a collection of novel techniques, including geographic sensing, worker tracking, task recommendation, and answer aggregation. This project is supported by grant from Microsoft Research Asia.

Lei Chen, Hong Kong University of Science and Technology
7 Sensing, Crowdsourcing, and Analyzing, iBump: Crowdsourcing-Based Road Monitoring System

The clustering algorithms are applied on the crowdsourced data to identify the location of the road anomalies. By this means, it is possible to achieve pervasive road pavement monitoring with low deployment cost. The demo is presented in the form of a video that demonstrates a test run on the NCTU campus. The video shows four subscreens, including ground truth, anomaly map, bumping sensor, and oscillation waveform. The ground truth window shows the field-trial driving environment. The anomaly map window shows the detected anomalies on the digital map. The bumping sensor window shows the GPS and vibration data, and the last detected bumping event. The vibration waveform window shows the waveform of vertical acceleration components calculated g-sensor data.

Chris Peng, National Chiao Tung University
8 Real-Time Traffic Prediction

Real Traffic, short for Real-Time Traffic Prediction, is a real-time highway traffic prediction model with Microsoft Azure. This model predicts six hours ahead of time by using highway sensor data—such as Dedicated Short-Range Communications, Vehicle Detection System, and Toll Collection System—over the range of the Korean highway network, with total length of 1,800 km.

Real Traffic has three applications. The first is prediction of speed and travel time at five-minute intervals, to inform both drivers and highway managers, by using Multi-level k-Nearest Neighbors method. The second is highway demand prediction over 0.2 million pairs of origin and destination tollgates to observe the dynamics of movement on a highway, by using Scaling k-Nearest Neighbors method. The last is traffic simulation, which provides a basis for traffic control, with Modified Cell Transmission Model. This predicts highway performance under various accident and traffic control scenarios and helps determine highway management strategies for the optimal system performance.

Hwasoo Yeo, Korea Advanced Institute of Science and Technology
9 Environmental Modeling and Visualization System for Eco-Friendly Behavior in Urban Traffics

To help reduce CO2 emission from road traffic, we have constructed a system that prompts people to adopt eco-friendly travel behavior by modeling and showing regional traffic. The traffic flow is modeled by using street-side cameras, and CO2 emissions in regional areas are estimated by traffic simulations. The CO2 emissions are visualized with VR/MR technologies and accordingly reduced by eco-friendly behaviors. Currently, we are developing 3D city modeling techniques for more accurate traffic simulations. In this presentation, we introduce our projects in urban scenes.

Takeshi Oishi, The University of Tokyo
10 Implementation of via Hole and Multi-Layered Circuit with Instant Inkjet Circuit

Prototyping is a very important in designing electronic circuits. For a long time, engineers have been using breadboard for rapid prototyping. Although breadboard is convenient on a small scale, it can become entangled and time consuming for more complex circuits. To eliminate these challenges, at the University of Tokyo we have established our own unique designing method. We have succeeded in printing electrical circuits on flexible materials such as paper and PET film, by using a regular household inkjet printer and commercial silver nanoparticle ink manufactured by Mitsubishi Paper Mills Ltd. In one minute, we have a neat and clean printed electronic circuit. Currently, we are also working on prototyping of a multi-layered circuit on paper. Starting with a double-sided circuit, we are developing a process to fabricate via hole for an instant inkjet circuit. This via hole can be made by laser cutter or specially designed needles. In the future, we will implement a method to fabricate multi-layered circuit by using silver nanoparticle ink and an inkjet printer.

Ta Duc Tung, The University of Tokyo
11 Microsoft Research Asia Talent Program

At Microsoft Research Asia, we are creating technologies not only for tomorrow, but also for the day after tomorrow. Microsoft Research supports innovative projects to advance state-of-the-art research and teaching in computer science and computational science around the world. We recognize and support top talent as interns, fellows, and scholars who are invited to work at Microsoft Research labs worldwide. The Microsoft Research Asia fellowship program and Young Faulty program support outstanding students and early-career faculty to help advance computer science and computational sciences in academia. Our internship program supports students who are considering careers in research.

Jennifer Cao, Microsoft Research Asia
12 Code Hunt: Programming by Solving Codes

Code Hunt is an educational coding game that runs in a browser. The game consists of a series of worlds and levels that get more challenging. In each level, the player has to discover a secret algorithm and write code for it. The game has sounds and a leaderboard to keep users engaged. Code Hunt targets teachers and students from introductory to advanced programming or software engineering courses. In addition, Code Hunt can be used by seasoned developers to hone their programming skills or by companies to evaluate job candidates. It has also been used in contests such as Beauty of Programming and Imagine Cup. At the core of the game experience is an automated program analysis and grading engine that is based on symbolic execution, Pex. The engine spots errors in the code and detects any differences between the code and the secret algorithm. Code Hunt was developed by the Research in Software Engineering (RiSE) group in collaboration with Microsoft Research Outreach at Microsoft Research.

Judith Bishop, Microsoft Research
13 Azure Machine Learning: Language Auto-Detection

In machine learning, classification is the problem of identifying to which of a set of categories a new observation belongs, by using a classification model that has been trained by using a set of observations whose category membership is known.

This demo will show how Azure ML can be used for language auto-detection:

  • Importing the dataset
  • Processing the data into training and evaluation datasets
  • Training the language detection model by using cross validation
  • Scoring the language detection model
  • Evaluating the language detection model
Junsheng Hao, Shanghai Yungoal
14 Lab of Things: A Research Platform for the Internet of Things

An increasing number of research areas rely on collecting data from sensors and devices that are deployed where people live, work, and play. Researchers typically deploy sensors and devices in a few homes or workspaces, collect data, analyze the data, and make interesting inferences based on this data.

Healthcare and energy management are two examples of such areas. This hands-on demo of the Lab of Things uses off-the-shelf sensors and cameras. We will also demonstrate features that allow device deployments based on the Lab of Things to scale up in geographically dispersed locations.

Arjmand Samuel, Microsoft Research
15 Intelligent and Scalable Monitoring/Control Platform for Home Energy Management

Most smart home applications today are either ad hoc or closed/monolithic—so it is critical to study novel software architecture/frameworks that are open and that connect multiple heterogonous devices and multiple networks. These frameworks need to support multiple concurrent applications, enable reliable data/command delivery among home gateway and cloud/smartphone, and provide easy-to-develop third-party service business applications. After investigating existing software solutions and standards, we propose a service framework for the smart home that combines HomeOS, MQTT, and Azure cloud. Several new drivers and applications have been developed on top of HomeOS for building a smart home gateway. MQTT is used for reliable and scalable message delivery between gateway and cloud, and push notification to Android devices. We also develop simple multi-tenant mechanism based on the Azure platform.

Lanshun Nie, Harbin Institute of Technology
16 Facial Beautification on Microsoft Azure

In this demo, we present a system of facial beautification that is deployed on the Microsoft Azure cloud platform. Facial beautification is a novel computational photography technique to enhance the aesthetic appeal of an image of a human face while maintaining high similarity to the original. The system uses a new adaptive region-aware masks generation method, together with other image processing technologies such as image layers decomposition, facial landmarks detection, data-driven facial image synthesis, and fusion. The result is an effective, convenient, and flexible tool and a fantastic way for specific facial beautification in terms of skin smoothness, shape beautification, lighting, and color enhancement. We will also present a local version of this system that runs on Windows in case there is limited Internet network bandwidth or access.

Lianwen Jin, South China University of Technology
17 Cloud-Based Massive Open Online Research (MOOR)

In engineering, experiment classes are essential for project-based learning that fosters a student’s problem-solving skills and creativity. This project aims to extend our cloud-based MOOC platform to support large-scale online virtual experiment activities. We introduce a cloud-based software framework to implement online lab services by virtualizing real lab facilities and enabling remote access to these lab resources. Based on the framework, we are developing multiple virtual lab courseware in conjunction with our pilot efforts of creating video-rich MOOC courseware.

Wenjun Wu, Beihang University
18 Sea Ice Data Portal 2.0: Facilitating the Intercomparison of the Climate Model Output and the Satellite Observation Data

Sea Ice Data Portal 2.0 is a prototype system that facilitates the archive, discovery, and intercomparison of sea ice data produced by climate model outputs and satellite observation. It is a big challenge to intercompare the 1.5 petabytes of climate model outputs, including the sea ice data, produced during the international Coupled Model Intercomparison Project Phase 5 (CMIP 5). Further intercomparison of these model outputs with the observation data to assess where they are similar and where they diverge is critical when evaluating the accuracy of these models. Based on the previous efforts, we further enriched our Sea Ice Data Portal 1.0 to enable the model-observation intercomparison. Different types of Azure resources, such as Azure Storage and Virtual Machine, are linked together to establish an integrated Sea Ice Data Portal 2.0.

Yuqi Bai, Tsinghua University
19 Biodiversity Monitoring Based on Cloud Environment and Citizen Science

We are experiencing the sixth mass extinction of plants and animals, and an effort is needed to protect the biodiversity of our planet. In addition to the information available from specimens and observations, there is a significant amount of information about the temporal distribution of species that can be extracted and processed from scientific literatures. However, this requires a high-performance environment to store and process the huge amounts of data, including more than 100 million records on 40 million pages. More real-time biodiversity data can be obtained from the websites of journals, news, botanical gardens, protected areas, and the communities of citizen science. This information should be integrated, analyzed, and displayed in a cloud environment and that enables external users to interact with it. There are also some new techniques that should be introduced, such as machine learning, natural language processing, and GIS.

Zheping Xu, Chinese Academy of Sciences
20 Collaborative Geoprocessing on Microsoft Azure for Education and Research

With the advancement of sensors and information technologies, a large amount of geographical information and resources (GIRs, including geodata, algorithms, and models) have become available on the Internet. However, the heterogeneous nature and the complexity of the Internet make it a challenge for GIS researchers and teachers to discover and utilize demanded online GIRs. Getting the distributed online GIRs to working collaboratively for research and teaching has become an urgent problem.

We designed GeoSquare, a collaborative GeoProcessing framework based on Azure. Through GIRs sharing and GeoProcessing orchestration, GeoSquare can help researchers and teachers search for and utilize online resources in an efficient, harmonious way. GeoSquare was implemented based on web technologies such as the enterprise web portal, Rich Internet Applications, Java User Interface toolkits, and workflow engines. Most of these technologies are built on open source standards to ensure the delivery of content-rich and cross-platform applications.

Huayi Wu, Wuhan University
21 Disease Gene Search Engine (DigSee): Text Mining for Identifying Disease-Gene-Biological Events Relationships

This demo presents a new version of DigSee, a disease gene search engine with evidence sentences. This new version allows searching genes related to nervous system diseases and cardiovascular diseases as well as cancer. The main benefit of using DigSee compared to other search engines in the biomedical domain is that it allows a query for searching Medline abstracts describing that `genes’ are involved in the development of ‘disease’ through `biological events.’ Understanding the association between diseases and genes can be enhanced with the identification of involved biological events, such as gene expression, regulation, phosphorylation, localization, and protein catabolism.

Hyunju Lee, Gwangju Institute of Science and Technology
22 Intelligent Sustainable Navigation Services

This study emphasizes the eco-efficiency of urban passenger transportation, which can be defined as the production of maximum benefits to society with minimized environmental impacts from the use of energy and materials. Conventionally, the measure of traffic and transportation eco-efficiency has mainly been considered as minimizing parameters such as primary energy per passenger-km, or grams of carbon dioxide or other vehicle pollutants such as nitrogen oxides or carbon monoxide, per vehicle-km. To design the next generation navigation system, we must consider how user behavior can help maximize eco-efficiency rather than keeping the focus on the traditional aspects such as emission. This is possible only with the support of pervasive computing technologies and big data computations in the cloud. Requirement: No special.

Yingqing Xu, Tsinghua University

 

Stephen Jia Wang, Monash University

23 Building Communication Bridges for Chinese Minority Ethnic Languages: An Efficient Translation Framework Based on Microsoft Translator Hub

Asymmetry of information interactions is one of the most important determining factors in economic and cultural imbalance in different areas. In China, there are 56 ethnic groups, more than 80 languages, and about 30 different characters. Most languages have not been supported by major translation providers yet. This limits the access that Chinese minority ethnic groups have to global information and knowledge. We want to build a simple but efficient translation framework for Chinese minority ethnic languages that can build a complex SMT system in an easy way.

Conghui Zhu, Harbin Institute of Technology
24 Using Kinect to Study the Role of Hand Gestures During Conversations

In the research of communication, studying how people use hand gestures during conversations is challenging. Common methods such as video taping and manual coding can be expensive, unreliable, and unscalable. In this demo, we showcase our approach of using Kinect’s skeleton tracing capability to capture hand movements during conversations and to derive key metrics such as number of gesture used by individuals, and we look at the interpersonal similarity of gestures between interlocutors. The approach supports the study of the non-verbal aspects of conversation and enables new possibilities for interaction and communication design, such as evaluating new communication tools in the field and using feedback to shape communication processes based on the quantitative metrics of gestures.

Hao-Chuan Wang, National Tsing Hua University
25 Visual-Haptic Interactive Telepresence

This demo will show a tele-immersive system that includes both remote haptic handshaking and interactive visual face tracking. The proposed system has a physical human-like avatar with a handshaking robotic arm/hand and an accurate face pose correction algorithm with multiple cameras. The handshaking robotic arm/hand can provide various haptic sensations, such as shaking forces, hand grip pressures, and temperature, while handshaking over any networks by using a robust haptic tele-manipulation technique that can overcome time-varying natures and uncertainties in the networks and humans. In addition, realistic eye contact is made by an accurate face pose estimation algorithm, and the texture of the face is reconstructed and rendered based on the estimated pose information. A live demo of the system will be provided between two different locations in China and South Korea.

Jeha Ryu, Gwangju Institute of Science and Technology

 

Sangyoun Lee, Yonsei University

26 HamsaTouch: Visual to Tactile Conversion Using Smartphone and Electrotactile Display

We developed a tactile vision substitution system that is composed of an electro-tactile display, optical sensors beneath each electrode, and a smartphone with a camera and an LCD. The smartphone acquires the surrounding view, conducts image processing, and displays the image on the LCD. The image is captured by the optical sensors and converted to a tactile image by the electro-tactile display. Combining the commonly available mobile device and electro-tactile display enables a low-cost yet powerful and compact system.

Hiroyuki Kajimoto, University of Electro-Communications
27 Design Systems for Origami

Origami, which is the construction of an object by folding a single sheet of paper, has been studied in the fields of mathematics and engineering for long time. Although we can make only a developable surface by bending a nonstretch flat material, adding folds expands its possible shapes. Many origami artists create amazing works; some are based on trial-and-error processes, and some are based on mathematical theories. Because of its geometrical constraints, origami presents an interesting challenge for developing a design system. We have studied several approaches for origami design in view of computational geometry. We will introduce some design systems that we developed in our research. Most of them have an interactive user interface, and we can see the folded shape and its crease patterns, with the lines to be folded, all at the same time. These systems help explore the wonder of the origami world.

Jun Mitani, University of Tsukuba

Videos

Panel Discussion: Fostering Interdisciplinary Talents Link description

Panel Discussion: Fostering Interdisciplinary Talents

Date

October 30, 2014

Speakers

Tim Pan, Peng Gong, David S. Rosenblum, Jeong Kap-Young, and Jeannette Wing

Affiliation

MSRA, Tsinghua University, National University of Singapore, Yonsei University, MSR