Overview
Hai “Helen” Li is the Marie Foote Reel E'46 Distinguished Professor and chair of Electrical & Computer Engineering at Duke.
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.
She received her B.S. and M.S. degrees from Tsinghua University, and her Ph.D. from Purdue University. 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.
Current Appointments & Affiliations
Recent Publications
Advancements in Content-Addressable Memory (CAM) Circuits: State-of-the-Art, Applications, and Future Directions in the AI Domain
Journal Article IEEE Transactions on Circuits and Systems I: Regular Papers · January 1, 2025 — Content-Addressable Memory (CAM) circuits, distinguished by their ability to accelerate data retrieval through a direct content-matching function, are increasingly crucial in the era of AI and increasing data computation. With the rise of AI models, hard ... Full text CiteA Survey: Collaborative Hardware and Software Design in the Era of Large Language Models
Journal Article IEEE Circuits and Systems Magazine · January 1, 2025 The rapid development of large language models (LLMs) has significantly transformed the field of artificial intelligence, demonstrating remarkable capabilities in natural language processing and moving towards multi-modal functionality. These models are in ... Full text CiteEmerging Computing Mechanisms for Edge AI
Journal Article IEEE Nanotechnology Magazine · January 1, 2025 The aspiration of mimicking the human brain's efficiency and smartness has brought notable progress in artificial intelligence (AI). While algorithms stemming from neural networks have successfully demonstrated their high performance across diverse applica ... Full text CiteRecent Grants
Center of Neuromorphic Computing under Extreme Environments
ResearchPrincipal Investigator · Awarded by University of Southern California · 2024 - 2029DoD Center of Excellence in Advanced Computing and Software (COE-ACS)
ResearchCo-Principal Investigator · Awarded by Georgia State University · 2023 - 2028PARTNER: Neuro-Inspired AI for the Edge at UTSA (NAIAD)
ResearchPrincipal Investigator · Awarded by The University of Texas at San Antonio · 2023 - 2027View All Grants