About

My homepage has moved to GitHub: https://diwangbruce.github.io/

My research interests span the areas of AI/machine learning/deep learning, computer systems, computer architecture, VLSI design,  energy-efficient systems design and sustainable computing. Specifically, I have applied my expertise on these topics to the areas of computer vision, datacenters, IoT, storage systems, fault tolerant systems and electronics design automation tools. Recently, I have been working on combining systems, intelligence and analytics to create new experiences and capabilities in the era of IoT.

I received my Ph.D. in Computer Science and Engineering from Penn State University in 2014, M.S. in Computer Systems Engineering from Technical University of Denmark (DTU) in 2008 and B.E. in Computer Science and Technology from Zhejiang University in 2005.

 

Other

Program Committee

  • European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD), 2019
  • IEEE International Conference on Autonomic Computing (ICAC), 2019.
  • ICDCS’18 Vice-Chair of “Distributed Green Computing and Energy Management” track
  • ICDCS’17, ICAC’17, ICCCN’17
  • ICDCS’16, ICAC’16, ICCCN’16, EDCS’16 (collocated with ISCA’16)

Past Intern Students

  • Dimitrios Stamoulis (‘18 CMU): ECMLPKDD’19, ODML-CDNNR’19 Best Paper Award (collocated with ICML’19)
  • Mengting Wan (’16,’17 UCSD): WWW’17, CIKM’18
  • Iyswarya Narayanan (’15 Penn State): Systor’16 Best Student Paper Award, Sigmetrics’16 Poster
  • Yang Li (’14 CMU): HPCA’16

Phd Thesis Committee

  • Neda Nasiriani, Penn State University, Cloud Provider’s Energy-efficient Operation and Effective Pricing Design, thesis defense date: May 4th, 2018.
  • Dimitrios Stamoulis, CMU

Publications

2019

  • Dimitrios Stamoulis, Ruizhou Ding, Di Wang, Dimitrios Lymberopoulos, Bodhi Priyantha, Jie Liu, Diana Marculescu, “Single-Path NAS: Designing Hardware-Efficient ConvNets in less than 4 Hours”, in Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2019 (ECML PKDD’19) , arXiv link: http://arxiv.org/abs/1904.02877; codebase: https://github.com/dstamoulis/single-path-nas
  • Dimitrios Stamoulis, Ruizhou Ding, Di Wang, Dimitrios Lymberopoulos, Bodhi Priyantha, Jie Liu and Diana Marculescu, “Single-Path NAS: Device-Aware Efficient ConvNet Design”, Joint Workshop on On-Device Machine Learning & Compact Deep Neural Network Representations (ODML-CDNNR), colocated with ICML, 2019 (Best Paper Award).

2018

  • Mengting Wan, Di Wang, Jie Liu, Paul Bennett, Julian McAuley, “Representing and Recommending Shopping Baskets with Complementarity, Compatibility, and Loyalty”, to appear in Proc. of 2018 ACM Conference on Information and Knowledge Management (CIKM’18), Turin, Italy, Oct. 2018.
  • N. Nasiriani, G. Kesidis, D. Wang, Public Cloud Differential Pricing Design Under Provider and Tenants Joint Demand Response , in Proceedings of the Ninth ACM International Conference on Future Energy Systems (e-Energy), 2018.
  • A. Mamun, I. Narayanan, D. Wang, A. Sivasubramaniam, H. K. Fathy, A Stochastic Optimal Control Approach for Exploring Tradeoffs between Cost Savings and Battery Aging in Datacenters Demand Response, in IEEE Transactions on Control Systems Technology, 26(1):360-367, January 2018
  • Yuanyuan Shi, Bolun Xu, Di Wang, Baosen Zhang, Using Battery Storage for Peak Shaving and Frequency Regulation: Joint Optimization for Superlinear Gains, in IEEE PES Transactions on Power Systems, May, 2018.

2017

  • Iyswarya Narayanan, Di Wang, Abdullah-al Mamun, Anand Sivasubramaniam, Hosam Fathy, Sean James, Evaluating Energy Storage for a Multitude of Uses in the Datacenter, in the Proceedings of IEEE International Symposium on Workload Characterization (IISWC), 2017.
  • Neda Nasiriani, George Kesidis, Di Wang, Optimal Peak Shaving Using Batteries at Datacenters: Characterizing the Risks and Benefits, in Proceedings of the IEEE 25th International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS) 2017 (Best Paper Award).
  • Iyswarya Narayanan, Bikash Sharma, Di Wang, Sriram Govindan, Laura Caulfield, Anand Sivasubramaniam, Aman Kansal, Jie Liu, Badriddine Khessib and Kushagra Vaid, Rain or Shine? – Making Sense of Cloudy Reliability Data, in Proceedings of the 37th IEEE International Conference on Distributed Computing (ICDCS), 2017.
  • Mengting Wan, Di Wang, Matt Goldman, Matt Taddy, Justin Rao, Jie Liu, Dimitrios Lymberopoulos, Julian McAuley, Modeling Consumer Preferences and Price Sensitivities from Large-Scale Grocery Shopping Transaction Logs, in Proceedings of World Wide Web Conference (WWW), 2017.

2016

  •  Y. Shi, B. Xu, B. Zhang, D. Wang, “Leveraging Energy Storage to Optimize Data Center Electricity Cost in Emerging Power Markets”, in Proceedings of the 7th ACM International Conference on Future Energy Systems (e-Energy), 2016.
  •  I. Narayanan, D. Wang, M. Jeon, B. Sharma, L. Caulfield, A. Sivasubramaniam, B. Cutler, J. Liu, B. Khessib, K. Vaid, SSD Failures in Datacenters: What, When and Why? , in Proceedings of the 9th ACM International Systems and Storage Conference (Systor), 2016. (Best Student Paper Award)
  •  Yang Li, Di Wang, Saugata Ghose, Jie Liu, Sriram Govindan, Sean James, Eric Peterson, John Siegler, Rachata Ausavarungnirun, Onur Mutlu, “SizeCap: Coordinating Energy Storage Sizing and Power Capping for Fuel Cell Powered Data Centers”, in the 22nd Intl. Symp. on High Performance Computer Architecture (HPCA), 2016. Acceptance ratio: 53/240 (22%).
  •  Iyswarya Narayanan, Di Wang, Myeongjae Jeon, Bikash Sharma, Laura Caulfield, Anand Sivasubramaniam, Ben Cutler, Jie Liu, Badriddine Khessib, Kushagra Vaid, “: SSD Failures in Datacenters: What, When and Why?”, ACM SIGMETRICS/IFIP Performance (Poster), 2016.
  • Abdullah-al Mamun, Iyswarya Narayanan, Di Wang, Anand Sivasubramaniam, Hosam K. Fathy, “Battery health-conscious online power management for demand response in datacenters with stochastic power demand”, IEEE Control Systems Society Conference Management, 2016.
  • Li Zhao, Jacob Brouwer, Sean James, Eric Peterson, Di Wang, and Jie Liu, Fuel Cell Powered Data Centers: In-Rack DC Generation, The Electrochemistry Society Transactions, 71(1): 131-139, 2016.
  • Mark Gottscho, Mohammed Shoaib, Sriram Govindan, Bikash Sharma, Di Wang, and Puneet Gupta, Measuring the Impact of Memory Errors on Application Performance, IEEE Computer Architecture Letters, 2016.
  • A. Mamun, I. Narayanan, D. Wang, A. Sivasubramaniam, H. K. Fathy, “Multi-objective Optimization of Demand Response in a Datacenter with Lithium-ion Battery Storage”, J. Energy Storage, Vol. 7, pp. 258-269, 2016.

2015

  • D. Wang, Variability Aware Statistical Timing Modeling Using SPICE Simulations, Lambert Academic Publishing, ISBN 978-3-659-40553-2, 2015.
  • A. Mamun, D. Wang, I. Narayanan, A. Sivasubramaniam, H. Fathy, Physics-based simulation of the impact of demand response on lead-acid emergency power availability in a datacenter, Journal of Power Sources 275, 516-524, Feb, 2015.
  • A. Mamun, I. Narayanan, D. Wang, A. Sivasubramaniam, H. Fathy, Multi-objective Optimization to Minimize Battery Degradation and Electricity Cost for Demand Response in Datacenters, ASME Dynamic Systems and Control Conference, 2015.

2014

  • Iyswarya Narayanan, Di Wang, Abdullah-Al Mamun, Anand Sivasubramaniam, and Hosam K. Fathy, “Should We Dual-Purpose Energy Storage in Datacenters for Power Backup and Demand Response?” in Workshop on Power-Aware Computing and Systems (HOTPOWER), 2014.
  • Di Wang, Sriram Govindan, Anand Sivasubramaniam, Aman Kansal, Jie Liu and Badriddine Khessib, “Underprovisioning Backup Power Infrastructure for Datacenters”, in Proceedings of Internatonal Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), Salt Lake City, UT. March 2014.

2013

2012

2011 and Previous years

Thesis

  • Di Wang, “Provisioning and Harnessing Energy Storage in Datacenters”, Ph.D. Dissertation, The Pennsylvania State University, Aug. 2014.
  • Di Wang, “Variability Aware Statistical Timing Modelling Using SPICE Simulations”, M.S. Thesis, Technical University of Denmark, Feb. 2008.

Talks

  • Keynote Speaker, Dec 2018, IoT Data Analytics Workshop (Collocated with IEEE Big Data Conference). Title: DNN Inference Optimization across the System Stack for Edge and IoT Enabled Applications
  • Colloquium Talk, Nov 2018, Penn State, Electrical Engineering and Computer Science. Title: DNN Inference Optimization across the System Stack
  • Guest Lecture/Seminar Talk, Nov 2018, CMU, Electrical and Computer Engineering. Title: DNN Inference Optimization across the System Stack
  • Invited Talk, May 2018, Computer Literacy Seminars, Department of Information Technology University of Washington, Tacoma. Title: Data Fusion in IoT Applications
  • Invited Speaker, Jan 2017, Microsoft-University of Washington Fuel Cell Workshop. Title: Co-optimization of datacenter loads and fuel cell systems
  • Invited Talk, Oct 2015, University of Washington, Department of Electrical Engineering. Title: Leveraging Energy Storage Towards Cost Effective Datacenters

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