Learning in Energy-Efficient Neuromorphic Computing: Algorithm and Architecture Co-Design
暫譯: 能源效率神經形態計算中的學習：算法與架構共同設計

NAN ZHENG, PhD, received a B. S. degree in Information Engineering from Shanghai Jiao Tong University, China, in 2011, and an M. S. and PhD in Electrical Engineering from the University of Michigan, Ann Arbor, USA, in 2014 and 2018, respectively. His research interests include low-power hardware architectures, algorithms and circuit techniques with an emphasis on machine-learning applications.

PINAKI MAZUMDER, PhD, is a professor in the Department of Electrical Engineering and Computer Science at The University of Michigan, USA. His research interests include CMOS VLSI design, semiconductor memory systems, CAD tools and circuit designs for emerging technologies including quantum MOS, spintronics, spoof plasmonics, and resonant tunneling devices.

於2011年獲得中國上海交通大學資訊工程學士學位，並於2014年和2018年分別在美國密西根大學安娜堡校區獲得電機工程碩士及博士學位。他的研究興趣包括低功耗硬體架構、演算法和電路技術，特別強調機器學習應用。

是美國密西根大學電機工程與計算機科學系的教授。他的研究興趣包括CMOS VLSI設計、半導體記憶體系統、CAD工具以及針對新興技術的電路設計，包括量子MOS、自旋電子學、偽等離子體技術和共振隧道裝置。