Microsoft Research Blog

The Microsoft Research blog provides in-depth views and perspectives from our researchers, scientists and engineers, plus information about noteworthy events and conferences, scholarships, and fellowships designed for academic and scientific communities.

Latest recipients of Windows Azure for Research Awards announced

January 16, 2014 | Posted by Microsoft Research Blog

Microsoft Research’s Windows Azure for Research program, which features a continuing series of Windows Azure cloud training events and a program of Windows Azure research grants, has been going strong since its launch in September 2013. As the December 15, 2013, deadline for the second round of grant proposals approached, we braced ourselves for a barrage of creative ideas. We weren’t disappointed, receiving proposals from every continent (well, except Antarctica). The response was particularly strong from such countries as Brazil and China, where our recent training events gave researchers an excellent, hands-on view of the capabilities of Windows Azure.

Forty-five proposals selected from researchers around the world

Several strong research themes that had emerged in the first round of proposals continued in the second round. Specifically, the life sciences and the emerging field of urban science were abundantly represented. Both themes can be thought of as big data topics, but they are really part of what we call the fourth paradigm of science, which is about discovering new scientific principles through deep analysis of massive amounts of data.

Urban science, which can be described as an interdisciplinary mash-up of computer science and social science, is becoming an important tool for city planners. By using the real-time data that a typical modern city generates, they can gain a better understanding how to improve life for the city’s inhabitants. The cloud is ideally suited to collecting, filtering, analyzing, and sharing these data.

A set of related topics that came on strong in the second-round proposals involved environmental science, ecology, and geosciences. Again, the common theme is using Windows Azure on the Microsoft cloud for data collection, analysis, and dissemination. In addition to such fourth-paradigm ideas, we received a large number of excellent computer science proposals that rely on the scale of the cloud to experiment with new algorithms and database topics.  

Selecting the winning proposals was extremely difficult, as we can fund only a fraction of the submissions. Nonetheless, we persevered and winnowed the proposals down to the grant recipients listed, by lead author and project title, at the bottom of this blog. The order might appear random, but trust me, there’s a logic to it (hint: take a look at the alphabetical order of the country names). You can review abstracts for these proposals at Windows Azure for Research.

As a reminder, the next deadline for proposals is February 15, 2014. We encourage potential applicants to attend one of our training events or, if that’s not possible, to study the training material we’ve posted online. You can find a schedule of upcoming training events and the aforementioned training materials at Cloud Research Projects.

Dennis Gannon, Director of Cloud Research Strategy, Microsoft Research Connections

Learn more

Second-round Windows Azure for Research Award recipients:

  • Jian Zhang, University of Technology, Sydney, Australia
    Friends Recommendation Based on Graph Correlation
  • Yuedong Yang, Griffith University, Australia
    Cloud-based Platform for Genome-scale Prediction of Protein Functional Complex Structures at Experimental Quality    
  • Altigran Soares da Silva, UFAM, Brazil
    Keyword-based System for Relational Database    
  • Carmem Satie Hara, Federal University of Parana, Brazil
    RING Project    
  • Fernando da Fonseca de Souza, Universidade Federal de Pernambuco, Brazil
    Cloud Databases: A model to guarantee data consistency    
  • Luiz André Portes Paes Leme, Universidade Federal Fluminense, Brazil
    Assessing Recommendation Approaches for Dataset Interlinking    
  • Marcelo Valadares Galdos, Brazilian Bioethanol Science and Technology Laboratory (CTBE) / Brazilian Center of Research in Energy and Materials (CNPEM), Brazil   
    Using Azure to run an integration of process-based environmental models and geographic information systems    
  • Marta Mattoso, Federal University of Rio de Janeiro, Brazil
    User-Steering Phylogenetic Workflows in the Cloud
  • Milton Cezar Ribeiro, Sao Paulo State University, Brazil
    Integrating phonological, landscape, fauna movement and remote sensing massive data and processing throughout e-Science and Cloud computing
  • Rafael Duarte Coelho dos Santos, INPE – Brazilian National Institute for Space Research, Brazil
    Prototype Deployment of a Data Server for the Brazilian Weather and Climate Virtual Observatory    
  • Ricardo da Silva Torres, Institute of computing, University of Computing, Brazil
    Big Image Data Management on the Cloud for e-Science Applications    
  • Guangjun Zhang, Peking University, China
    Machine learning – parameter estimation for groundwater flow and transport models based on Windows Azure Cloud    
  • Huayi Wu, Wuhan University, China
    Collaborative Geoprocessing on Windows Azure
  • Jitao Sang, Chinese Academy of Sciences, China
    Cyber-Physical Footprint Association: Cloud Storage and Computing    
  • Junjie Wu, Beihang University, China
    A System for Heterogeneous Social Media Big Data Analytics in Azure Cloud    
  • Lei Zou, Peking University, China
    Graph Data Management in Urban Computing
  • Xinbo Gao, School of Electronic Engineering, China
    Videos analysis and recommendation for online learning    
  • Yan Xu, Beihang University, China
    Large-scale histopathology image analysis for colon cancer in Azure
  • Yuan Juli, Zou Hengming, Shanghai Jiao Tong University, China
    A Distributed Algorithm for File Distribution and Replication on Cloud Platform
  • Andres M. Pinzon, Center for Bioinformatics and Computational Biology of Colombia, Colombia
    A cloud-based system for the integration of molecular data and biodiversity information for Colombian species    
  • Frederic Magoules, Ecole Centrale Paris, France
    Advanced Linear Algebra Libraries for the Cloud    
  • Jean-Charles Régin, University Nice-Sophia Antipolis, France
    Using Windows Azure for High Performance Computing    
  • Liliana Pasquale, University of Limerick, Ireland
    Minority Report: Using the Cloud to Enable Proactive Digital Forensic Investigations
  • Tony Tung, Kyoto University, Japan
    Life Maps    
  • Hwasoo Yeo, Korea Advanced Institute of Science and Technology, Korea
    Cloud Sensing based Urban Travel Time Prediction with Online Traffic Simulator
  • Hyunju Lee, Gwangju Institute of Science and Technology, Korea
    Text mining for identifying disease-gene-biological relationships    
  • Joon Heo, Yonsei University, Korea
    Does ‘Gangnam Style’ really exist? – Answers from data science perspective    
  • Muhammad Bilal Amin, Kyung Hee University, Korea
    Enabling Data Parallelism for large-scale Biomedical Ontology Matching over Multicore Cloud Instances
  • Grigor Aslanyan, University of Auckland, New Zealand
    Studying Very Early Universe Physics with Cosmic Microwave Background Anomalies
  • Marek Stanislaw Wiewiorka, Warsaw University of Technology, Poland
    Towards an interactive secondary analysis of RNA sequencing data service in Widows Azure cloud with Apache Spark framework
  • Heiko Schuldt, University of Basel, Switzerland
    ADAM+ – A Large-Scale Distributed Image and Video Retrieval System
  • Blesson Varghese, University of St Andrews, United Kingdom
    Real-time Catastrophe Risk Management on Windows Azure    
  • Julio Hernandez-Castro, David Barnes, University of Kent, United Kingdom
    ChessWitan: Mining chess data to distinguish human from computer play
  • Nadarajen Veerapen, University of Stirling, United Kingdom
    Automated Bug Fixing
  • Vassilis Glenis, Newcastle University, United Kingdom
    Modelling Flood Risk in Urban Areas    
  • A. Lucas Stephane, Florida Institute of Technology, United States
    Life-Critical Interactive Glass Wall Integration    
  • Alexander Vyushkov, University of Notre Dame, United States
    Modeling Malaria Transmission on Windows Azure    
  • David Hazel, University of Washington, United States
    AMADEUS – Azure Marketplace of Applications for Diverse Environmental Use as a Service
  • Dhruv Batra, Virginia Tech, United States
    CloudCV: Large-Scale Distributed Computer Vision as a Cloud Service    
  • Hanspeter Pfister, Harvard University, United States
  • Kelly Smith, University Corporation for Atmospheric Research (UCAR), United States
    The Unidata Integrated Data Viewer (IDV) as a Cloud Service
  • Richard Dana Loft, National Center for Atmospheric Research, United States
    AzurePlanet: A cloud-based system providing access to weather and climate information
  • Susan Borda, California Digital Library, United States   
  • Tanya Berger-Wolf, University of Illinois at Chicago, United States
    Computational Behavioral Ecology on the Cloud    
  • Yuejie Chi, The Ohio State University, United States
    Online Distributed Inference of Large-Scale Data Streams in the Cloud   

Back to blog