Hai (Helen) Li

Short CV

Hai (Helen) Li received her bachelor’s and master’s degrees from Tsinghua University, China, and her Ph.D. degree from Purdue University, USA. She is Clare Boothe Luce Professor and Associate Chair of the Electrical and Computer Engineering Department at Duke University. Before that, she was with Qualcomm Inc., San Diego, CA, USA, Intel Corporation, Santa Clara, CA, Seagate Technology, Bloomington, MN, USA, the Polytechnic Institute of New York University, Brooklyn, NY, USA, and the University of Pittsburgh, Pittsburgh, PA, USA. Her research interests include neuromorphic computing systems, machine learning and deep neural networks, memory design and architecture, and cross-layer optimization for low power and high performance. She has authored or co-authored more than 250 technical papers in peer-reviewed journals and conferences and a book entitled Nonvolatile Memory Design: Magnetic, Resistive, and Phase Changing (CRC Press, 2011). She received 9 best paper awards and an additional 9 best paper nominations from international conferences. Dr. Li serves/served as an Associate Editor of a number of IEEE/ACM journals. She was the General Chair or Technical Program Chair of multiple IEEE/ACM conferences. 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 (YFA), TUM-IAS Hans Fischer Fellowship from Germany, and ELATE Fellowship (2020). Dr. Li is an IEEE fellow and a distinguished member of the ACM.

Selected Awards

• 2021, Distinguished Research Award from IEEE Computer Society Technical Committee on VLSI (TCVLSI)
• 2021, Outstanding Leadership Award from IEEE Technical Committee on Secure and Dependable Measurement (TCSDM), for dedicated and exemplary leadership in proactively promoting technologies for security and reliability of intelligent systems and fostering a culture of inclusion and diversity
• 2020, ELATES Fellow
• 2019, Fellow of IEEE for Contributions to Neuromorphic Computing Systems
• 2018-2019, IEEE Circuits and Systems (CAS) Distinguished Lecturer
• 2017-2021, Clare Boothe Luce Faculty Fellowship, Duke University
• 2017-2020, Distinguished Speaker of the Association for Computing Machinery (ACM)
• 2017-2020, TUM-IAS Hans Fischer Fellowship, Technische Universität München, Germany
• 2017, Distinguished Member of the Association for Computing Machinery (ACM) for Scientific Contribution to developing novel computing and storage systems with emerging memories
• 2013, Defense Advanced Research Projects Agency (DARPA) Young Faculty Award (YFA)
• 2012, National Science Foundation (NSF) Career Program, 2012.
• Nine Best Paper Awards (ASPDAC 2021, ICMLA 2019, ASPDAC 2018, ASPDAC 2017, ASPDAC 2015, ISVLSI 2014, GLSVLSI 2013, ISLPED 2010, and ISQED 2008)

Research Interests

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

Selected Publications

• Huanrui Yang, Jingyang Zhang, Hongliang Dong, Nathan Inkawhich, Andrew Gardner, Andrew Touchet, Wesley Wilkes, Heath Berry and Hai Li, “DVERGE: Diversifying Vulnerabilities for Enhanced Robust Generation of Ensembles,” the 17th Annual Conference on Neural Information Processing Systems (NeurIPS), December 2020, arXiv:2009.14720.
• W. Wen, C. Wu, Y. Wang, Y. Chen, and H. Li, “Learning Structured Sparsity in Deep Neural Networks,” the 13th Annual Conference on Neural Information Processing Systems (NeurIPS), December 2016.
• X. Wang, H. Xi, Y. Chen, H. Li and D. V. Dimitrov, “Spintronic Memristor through Spin Torque Induced Magnetization Motion”, IEEE Electron Device Letters (EDL), volume 30, issue 3, March 2009, pages 294-297.
• M. Hu, H. Li, Y. Chen, Q. Wu, G. Rose, and W. Linderman, “Memristor Crossbar Based Neuromorphic Computing System: A Case Study,” IEEE Transactions on Neural Network and Learning System (TNNLS), vol. 25, no 10, pp. 1864-1878, Oct. 2014.