
Marie Foote Reel E'46 Distinguished Professor of Electrical and Computer Engineering
Hai (Helen) Li is the Marie Foote Reel E’46 Distinguished 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-in-Chief and 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 member of over 30 international conference series. Dr. Li is a Distinguished Lecturer of the IEEE CAS Society and a Distinguished Speaker of ACM. Dr. Li is a recipient of the IEEE Edward J. McCluskey Technical Achievement Award, Ten Year Retrospective Influential Paper Award from ICCAD, TUM-IAS Hans Fischer Fellowship from Germany, ELATE Fellowship, ten best paper awards, and another ten best paper nominations. Dr. Li is a fellow of ACM, IEEE, and NAI.
Appointments and Affiliations
- Marie Foote Reel E'46 Distinguished Professor of Electrical and Computer Engineering
- 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
- 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 (NAI). National Academy of Inventors. 2024
- Fellow, Executive Leadership in Academic Technology, Engineering and Science (ELATES). Drexel University. 2022
- Distinguished Member. Association for Computing Machinery (ACM). 2018
- Fellow. Institute of Electrical and Electronics Engineers (IEEE). 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 899: Special Readings in Electrical Engineering
- ECE 891: Internship
- ECE 661: Computer Engineering Machine Learning and Deep Neural Nets
- ECE 550D: Fundamentals of Computer Systems and Engineering
In the News
- Duke Researchers at the Forefront of the Next Generation of Wireless (Apr 8, 20…
- Duke Honors 31 New Distinguished Professors (Mar 25, 2025 | Duke Today)
- Two Pratt Faculty Receive Top Honor for Inventors (Jan 8, 2025 | Pratt School o…
- Taking Academic Leadership to the Next Level (Jul 18, 2023 | Office of Faculty …
- Putting the SE Back in Silicon Electronics (Mar 7, 2023 | Pratt School of Engin…
- Co-Designing Tomorrow's Computers (Sep 27, 2021 | Pratt School of Engineering)
- Training Enormous AI Models in Health Care While Protecting Data Privacy (Sep 7…
- Bringing Radar Down From the Clouds to the City Streets (May 11, 2021 | Pratt S…
- On Security's Frontiers: Trustworthy Computing (Oct 12, 2020 | Duke ECE Magazin…
- Duke-Led Team to Develop Privacy-Minded AI Health Learning Platform: NSF Conver…
Representative Publications
- Kim, B., H. H. Li, and Y. Chen. “Emerging Computing Mechanisms for Edge AI.” IEEE Nanotechnology Magazine 19, no. 2 (January 1, 2025): 25–37. https://doi.org/10.1109/MNANO.2025.3533804.
- Molom-Ochir, T., B. Taylor, H. Li, and Y. Chen. “Advancements in Content-Addressable Memory (CAM) Circuits: State-of-the-Art, Applications, and Future Directions in the AI Domain.” IEEE Transactions on Circuits and Systems I: Regular Papers, January 1, 2025. https://doi.org/10.1109/TCSI.2025.3527309.
- Guo, C., F. Cheng, Z. Du, J. Kiessling, J. Ku, S. Li, Z. Li, et al. “A Survey: Collaborative Hardware and Software Design in the Era of Large Language Models.” IEEE Circuits and Systems Magazine 25, no. 1 (January 1, 2025): 35–57. https://doi.org/10.1109/MCAS.2024.3476008.
- Pan, Jingyu, Chen-Chia Chang, Zhiyao Xie, Yiran Chen, and Hai Helen Li. “EDALearn: A Comprehensive RTL-to-Signoff EDA Benchmark for Democratized and Reproducible ML for EDA Research.” In Proceedings of the 43rd IEEE/ACM International Conference on Computer-Aided Design, 1–8. ACM, 2024. https://doi.org/10.1145/3676536.3697116.
- Li, Ziru, Qilin Zheng, Jonathan Ku, Brady Taylor, and Hai Li. “TFSRAM: A 249.8TOPS/W Timing-to-First-Spike Compute-in-Memory Neuromorphic Processing Engine With Twin-Column SRAM Synapses.” IEEE Transactions on Circuits and Systems for Artificial Intelligence 1, no. 1 (September 2024): 26–36. https://doi.org/10.1109/tcasai.2024.3452649.