Hai "Helen" Li

Clare Boothe Luce Professor of Electrical and Computer Engineering

Research Interests:

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

Appointments and Affiliations

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

Contact Information

• Office Location: Rm130 Hudson Hall, 100 Science Dr., Durham, NC 27701
• Office Phone: (919) 660-1373
• Email Address: hai.li@duke.edu
• Websites:
  • Google Scholar
  • Personal page

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

• 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

• COMPSCI 350L: Digital Systems
• ECE 292: Projects in Electrical and Computer Engineering
• ECE 350L: Digital Systems
• ECE 550D: Fundamentals of Computer Systems and Engineering
• ECE 590: Advanced Topics in Electrical and Computer Engineering
• ECE 891: Internship
• ECE 899: Special Readings in Electrical Engineering

In the News

• Hai Helen Li: New Pratt Professor Models the Future of Computing After the Human Brain (Jan 3, 2017)

Representative Publications

• Zhang, S; Zhang, GL; Li, B; Li, HH; Schlichtmann, U, Lifetime Enhancement for RRAM-based Computing-In-Memory Engine Considering Aging and Thermal Effects, Proceedings 2020 Ieee International Conference on Artificial Intelligence Circuits and Systems, Aicas 2020 (2020), pp. 11-15 [10.1109/AICAS48895.2020.9073995] [abs].
• Li, B; Doppa, JR; Pande, PP; Chakrabarty, K; Qiu, JX; Li, HH, 3D-ReG: A 3D ReRAM-based Heterogeneous Architecture for Training Deep Neural Networks, Acm Journal on Emerging Technologies in Computing Systems, vol 16 no. 2 (2020) [10.1145/3375699] [abs].
• Li, B; Mao, M; Liu, X; Liu, T; Liu, Z; Wen, W; Chen, Y; Li, HH, Thread batching for high-performance energy-efficient GPU memory design, Acm Journal on Emerging Technologies in Computing Systems, vol 15 no. 4 (2019) [10.1145/3330152] [abs].
• Chen, F; Wen, W; Song, L; Zhang, J; Li, HH; Chen, Y, How to obtain and run light and efficient deep learning networks, Ieee/Acm International Conference on Computer Aided Design, Digest of Technical Papers, Iccad, vol 2019-November (2019) [10.1109/ICCAD45719.2019.8942106] [abs].
• Zhang, S; Zhang, GL; Li, B; Li, HH; Schlichtmann, U, Aging-aware Lifetime Enhancement for Memristor-based Neuromorphic Computing, Proceedings of the 2019 Design, Automation and Test in Europe Conference and Exhibition, Date 2019 (2019), pp. 1751-1756 [10.23919/DATE.2019.8714954] [abs].