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
• 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

• ECE 292: Projects in Electrical and Computer Engineering
• ECE 391: Projects in Electrical and Computer Engineering
• ECE 493: Projects in Electrical and Computer Engineering
• ECE 590: Advanced Topics in Electrical and Computer Engineering
• ECE 661: Computer Engineering Machine Learning and Deep Neural Nets
• 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

• Hu, W; Chang, CH; Sengupta, A; Bhunia, S; Kastner, R; Li, H, An Overview of Hardware Security and Trust: Threats, Countermeasures, and Design Tools, Ieee Transactions on Computer Aided Design of Integrated Circuits and Systems, vol 40 no. 6 (2021), pp. 1010-1038 [10.1109/TCAD.2020.3047976] [abs].
• Joardar, BK; Doppa, JR; Pande, PP; Li, H; Chakrabarty, K, AccuReD: High Accuracy Training of CNNs on ReRAM/GPU Heterogeneous 3-D Architecture, Ieee Transactions on Computer Aided Design of Integrated Circuits and Systems, vol 40 no. 5 (2021), pp. 971-984 [10.1109/TCAD.2020.3013194] [abs].
• Kim, B; Hanson, E; Li, H, An Efficient 3D ReRAM Convolution Processor Design for Binarized Weight Networks, Ieee Transactions on Circuits and Systems Ii: Express Briefs, vol 68 no. 5 (2021), pp. 1600-1604 [10.1109/TCSII.2021.3067840] [abs].
• Yang, Q; Li, H, BitSystolic: A 26.7 TOPS/W 2b8b NPU with Configurable Data Flows for Edge Devices, Ieee Transactions on Circuits and Systems I: Regular Papers, vol 68 no. 3 (2021), pp. 1134-1145 [10.1109/TCSI.2020.3043778] [abs].
• Chen, F; Song, L; Li, HH; Chen, Y, RAISE: A Resistive Accelerator for Subject-Independent EEG Signal Classification, Proceedings Design, Automation and Test in Europe, Date, vol 2021-February (2021), pp. 340-343 [10.23919/DATE51398.2021.9473993] [abs].