Fengbin Tu (Member, IEEE) received the B.S. degree in electronic science and technology from the Beijing University of Posts and Telecommunications, Beijing, China, in 2013, and the Ph.D. degree in electronic science and technology from Tsinghua University, Beijing, in 2019.

He is currently working for Tsinghua University as a Joint-Program Researcher and University of California at Santa Barbara, Santa Barbara, CA, USA, as a Post-Doctoral Researcher. His research interests include computer architecture, deep learning, VLSI design and approximate computing.

Dr. Tu’s dissertation “Energy-Efficient Neural Network Accelerator Design” won the Tsinghua Excellent Dissertation Award. He also serves as the reviewer for the IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS TCAD. He is also the main designer of the reconfigurable neural network processor “Thinker,” the main contributor to a popular online survey named “Neural Networks on Silicon,” and the winner of the 2017 Association for Computing Machinery (ACM)/IEEE International Symposium on Low Power Electronics and Design (ISLPED’17) Contest.
Research Manuscript
AI/ML System Design
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