Research Interests
AI Hardware; Neuromorphic Computing; Non-volatile Memories; Emerging Nanoelectronic Devices.
Biography
Can Li’s research aims to explore and build the next-generation computing hardware based on post-CMOS emerging devices, e.g. memristors. Before joining HKU, Dr. Li worked at Hewlett Packard Labs in California, USA. He obtained his bachelor’s degree from Peking University and his Ph.D. from the University of Massachusetts Amherst. In recent years, he has published 82 peer-reviewed publications, including 19 research papers in Nature series journals. Based on his research achievements, after joining HKU, he has received the National Natural Science Foundation of China Excellent Young Scientist Fund, the Hong Kong Research Grants Council Early Career Award, and the Croucher Tak Wah Mak Innovation Awards.
Publications
2023
- Efficient combinatorial optimization by quantum-inspired parallel annealing in analogue memristor crossbarJiang, Mingrui and Shan, Keyi and He, Chengping and Li, CanNature CommunicationsJ.
- ReRAM-based graph attention network with node-centric edge searching and hamming similarityMao, Ruibin and Sheng, Xia and Graves, Catherine and Xu, Cong and Li, Can2023 60th ACM/IEEE Design Automation Conference (DAC)C.
2022
- Experimentally validated memristive memory augmented neural network with efficient hashing and similarity searchMao, Ruibin and Wen, Bo and Kazemi, Arman and Zhao, Yahui and Laguna, Ann Franchesca and Lin, Rui and Wong, Ngai and Niemier, Michael and Hu, X Sharon and Sheng, Xia and othersNature communicationsJ.
- An efficient synchronous-updating memristor-based Ising solver for combinatorial optimizationJiang, Mingrui and Shan, Keyi and Sheng, Xia and Graves, Cat and Strachan, John Paul and Li, Can2022 International Electron Devices Meeting (IEDM)C.
2020
- Analog content-addressable memories with memristorsLi, Can and Graves, Catherine E and Sheng, Xia and Miller, Darrin and Foltin, Martin and Pedretti, Giacomo and Strachan, John PaulNature communicationsJ.