Hai Li

Professor in the Department 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
• Acting 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: (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

• 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 292: Projects in Electrical and Computer Engineering
• ECE 391: Projects in Electrical and Computer Engineering
• ECE 493: Projects in Electrical and Computer Engineering
• ECE 494: Projects in Electrical and Computer Engineering
• ECE 550D: Fundamentals of Computer Systems and 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

• Co-Designing Tomorrow's Computers (Sep 27, 2021 | Duke Engineering News)
• Duke and Pitt Train Enormous AI Models in Health Care, While Protecting Data Privacy (Sep 7, 2021 | Duke Engineering News)
• Duke Engineers are Using Machine Learning and Radar to Detect Drones in Complex Urban Settings (May 11, 2021 | Duke Engineering News)
• On Security's Frontiers: Trustworthy Computing (Oct 12, 2020 | Duke Engineering News)
• Duke-Led Team to Develop Privacy-Minded AI Health Learning Platform: NSF Convergence Accelerator Award (Sep 17, 2020 | Duke Engineering News)
• Detecting Backdoor Attacks on Artificial Neural Networks (Dec 23, 2019 | Duke Engineering News)
• Hai "Helen" Li Elected a Fellow of the IEEE (Dec 13, 2018 | Duke Engineering News)
• Hai Helen Li: New Pratt Professor Models the Future of Computing After the Human Brain (Jan 3, 2017)

Representative Publications

• Hanson, E; Li, S; Li, HH; Chen, Y, Cascading Structured Pruning: Enabling High Data Reuse for Sparse DNN Accelerators, Proceedings International Symposium on Computer Architecture (2022), pp. 522-535 [10.1145/3470496.3527419] [abs].
• Mao, J; Yang, Q; Li, A; Nixon, KW; Li, H; Chen, Y, Toward Efficient and Adaptive Design of Video Detection System with Deep Neural Networks, Acm Transactions on Embedded Computing Systems, vol 21 no. 3 (2022) [10.1145/3484946] [abs].
• Li, HH; Alameldeen, AR; Mutlu, O, Guest Editors' Introduction: Near-Memory and In-Memory Processing, Ieee Design & Test, vol 39 no. 2 (2022), pp. 46-47 [10.1109/MDAT.2021.3124742] [abs].
• Chen, Y; Li, H, SMALE: Enhancing Scalability of Machine Learning Algorithms on Extreme Scale Computing Platforms (2022) [10.2172/1846568] [abs].
• Hanson, E; Li, S; Qian, X; Li, H; Chen, Y, DyNNamic: Dynamically Reshaping, High Data-Reuse Accelerator for Compact DNNs, Ieee Transactions on Computers (2022) [10.1109/TC.2022.3184272] [abs].