Hai "Helen" Li

Professor in the Department of Electrical and Computer Engineering

 

Hai “Helen” Li is the Clare Boothe Luce Professor and Department Chair of the Electrical and Computer Engineering Department at Duke University. She received her B.S. and M.S. from Tsinghua University and her Ph.D. from Purdue University. Her research interests include neuromorphic circuits and systems for brain-inspired computing, machine learning acceleration and trustworthy AI, conventional and emerging memory design and architecture, and software and hardware co-design. Dr. Li served/serves as the Associate Editor for multiple IEEE and ACM journals. She was the General Chair or Technical Program Chair of numerous IEEE/ACM conferences and the Technical Program Committee members of over 30 international conference series. Dr. Li is a Distinguished Lecturer of the IEEE CAS Society (2018-2019) and a Distinguished Speaker of ACM (2017-2020). Dr. Li is a recipient of the NSF Career Award, DARPA Young Faculty Award, TUM-IAS Hans Fischer Fellowship from Germany, ELATE Fellowship, nine best paper awards and another nine best paper nominations. Dr. Li is a fellow of ACM and IEEE.

 

Appointments and Affiliations

  • Professor in the Department of Electrical and Computer Engineering
  • Chair of the Department of Electrical and Computer Engineering
  • Professor of Computer Science

Contact Information

  • Office Location: #407 Wilkinson Building, 534 Research Drive, Durham, NC 27701
  • Office Phone: +1 919 660 1373
  • Email Address: hai.li@duke.edu
  • Websites:

Education

  • Ph.D. Purdue University, 2004

Research Interests

Neuromorphic computing systems
Machine learning acceleration and trustworthy AI
Emerging memory technologies, circuit and architecture
Low power circuits and systems

Awards, Honors, and Distinctions

  • Fellow, Executive Leadership in Academic Technology, Engineering and Science (ELATES). Drexel University. 2022
  • Fellow. Institute of Electrical and Electronics Engineers (IEEE). 2018
  • Distinguished Member. Association for Computing Machinery (ACM). 2018
  • Best Paper Award for the paper titled “Classification Accuracy Improvement for Neuromorphic Computing Systems with One-level Precision Synapses”. Asia and South Pacific Design Automation Conference (ASPDAC). 2017
  • Fulton C. Noss Faculty Fellow. University of Pittsburgh. 2016
  • Best Paper Award for the paper titled “Quantitative Modeling of Racetrack Memory - A Tradeoff among Area, Performance, and Power”. Asia and South Pacific Design Automation Conference (ASPDAC). 2015
  • Air Force Summer Faculty Fellowship Program Award (AF-SFFP). AFRL/RITC. 2015
  • Best Paper Award for the paper titled “A Weighted Sensing Scheme for ReRAM-based Cross-point Memory Array”. IEEE Computer Society Annual Symposium on VLSI (ISVLSI). 2014
  • Best Paper Award for the paper titled “Coordinating Prefetching and STT-RAM based Last-level Cache Management for Multicore Systems”. Proceedings of the 23rd ACM International Conference on Great Lakes Symposium on VLSI (GLSVLSI). 2013
  • Air Force Visiting Faculty Research Program (VFRP) Fellowship. AFRL/RIB. 2013
  • DARPA Young Faculty Award. Defense Advanced Research Projects Agency (DARPA). 2013
  • NSF Career Award. National Science Foundation (NSF). 2012
  • Air Force Summer Faculty Fellowship Program Award (AF-SFFP). AFRL/RITC. 2011
  • Best Paper Award for the paper titled “Combined Magnetic- and Circuit-level Enhancements for the Nondestructive Self-Reference Scheme of STT-RAM”. ACM/IEEE International Symposium on Low Power Electronics and Design (ISLPED). 2010
  • Best Paper Award for the paper titled “Design Margin Exploration of Spin-Torque Transfer RAM (SPRAM)”. the 9th International Symposium on Quality Electronic Design (ISQED). 2008

Courses Taught

  • ECE 891: Internship
  • ECE 661: Computer Engineering Machine Learning and Deep Neural Nets
  • ECE 550D: Fundamentals of Computer Systems and Engineering
  • ECE 494: Projects in Electrical and Computer Engineering
  • ECE 493: Projects in Electrical and Computer Engineering

In the News

Representative Publications

  • Li, S., Y. Wang, E. Hanson, A. Chang, Y. Seok Ki, H. Li, and Y. Chen. “NDRec: A Near-Data Processing System for Training Large-Scale Recommendation Models.” IEEE Transactions on Computers 73, no. 5 (May 1, 2024): 1248–61. https://doi.org/10.1109/TC.2024.3365939.
  • Wang, B., M. Lin, T. Zhou, P. Zhou, A. Li, M. Pang, H. Li, and Y. Chen. “Efficient, Direct, and Restricted Black-Box Graph Evasion Attacks to Any-Layer Graph Neural Networks via Influence Function.” In WSDM 2024 - Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 693–701, 2024. https://doi.org/10.1145/3616855.3635826.
  • Yang, X., Z. Wang, X. S. Hu, C. H. Kim, S. Yu, M. Pajic, R. Manohar, Y. Chen, and H. H. Li. “Neuro-Symbolic Computing: Advancements and Challenges in Hardware-Software Co-Design.” IEEE Transactions on Circuits and Systems II: Express Briefs 71, no. 3 (March 1, 2024): 1683–89. https://doi.org/10.1109/TCSII.2023.3336251.
  • Parhi, Keshab K., Hai Li, Krishnan Kailas, Harish Krishnaswamy, Massimo Alioto, and Maciej Ogorzalek. “Editorial: Special Issue for the 75th Anniversary of the IEEE Circuits and Systems Society [Editorial].” IEEE Circuits and Systems Magazine 24, no. 2 (2024): 3–3. https://doi.org/10.1109/mcas.2024.3384522.
  • Kim, B., and H. Li. “Monolithic 3D stacking for neural network acceleration.” Nature Electronics 6, no. 12 (December 1, 2023): 937–38. https://doi.org/10.1038/s41928-023-01098-5.