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Chen BAI, Ph.D. student |
I am currently a second-year Ph.D. student at the Department of Computer Science and Engineering of The Chinese University of Hong Kong under the supervision of Prof. Bei Yu and co-supervised by Prof. Martin D.F. Wong. Previously, I received my B.Eng. from The University of Electronic Science and Technology of China (UESTC) in 2020.
Design Space Exploration
Software & Hardware Co-design
Ph.D. Computer Science and Engineering, The Chinese University of Hong Kong, Aug. 2020 -
B.Eng. Software Engineering, The University of Electronic Science and Technology of China, Sep. 2016 - Jul. 2020
[C6] Ziyi Wang, Chen Bai, Zhuolun He, Guangliang Zhang, Qiang Xu, Tsung-Yi Ho, Bei Yu, Yu Huang, “Functionality Matters in Netlist Representation Learning”, ACM/IEEE Design Automation Conference (DAC), San Francisco, CA, Jul. 10–14, 2022.
[C5] Qi Sun, Chen Bai, Tinghuan Chen, Hao Geng, Xinyun Zhang, Yang Bai, Bei Yu, “Fast and Efficient DNN Deployment via Deep Gaussian Transfer Learning”, IEEE International Conference on Computer Vision (ICCV), Oct. 11-17, 2021. (paper) (slides) (poster)
[C4] Zhuolun He, Ziyi Wang, Chen Bai, Haoyu Yang, Bei Yu, “Graph Learning-Based Arithmetic Block Identification”, IEEE/ACM International Conference on Computer-Aided Design (ICCAD), Nov. 1–4, 2021. (paper) (slides)
[C3] Chen Bai, Qi Sun, Jianwang Zhai, Yuzhe Ma, Bei Yu, Martin D.F. Wong, "BOOM-Explorer: RISC-V BOOM Microarchitecture Design Space Exploration Framework", IEEE/ACM International Conference on Computer-Aided Design (ICCAD), Nov. 1–4, 2021. (William J. McCalla Best Paper Award) (paper) (slides)
[C2] Jianwang Zhai, Chen Bai, Binwu Zhu, Yici Cai, Qiang Zhou, Bei Yu, “McPAT-Calib: A Microarchitecture Power Modeling Framework for Modern CPUs”, IEEE/ACM International Conference on Computer-Aided Design (ICCAD), Nov. 1–4, 2021. (paper) (slides)
[C1] Qi Sun, Chen Bai, Hao Geng, Bei Yu, "Deep Neural Network Hardware Deployment Optimization via Advanced Active Learning", IEEE/ACM Proceedings Design, Automation and Test in Europe (DATE), Feb. 01–05, 2021. (paper)(slides)
[J1] Jianwang Zhai, Chen Bai, Binwu Zhu, Yici Cai, Qiang Zhou, Bei Yu, “McPAT-Calib: A RISC-V BOOM Microarchitecture Power Modeling Framework”, accepted by IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD). (paper)
Huawei Hong Kong Research Center, Hong Kong SAR, Jul. 2021 - Apr. 2022
Research Intern, HiSilicon CPU design team
Topic: CPU design space exploration & Power modeling
SenseTime, Beijing, P.R. China, Oct. 2019 - Apr. 2020
Research Intern, Intelligent Video Generation Group
Topic: Deep Learning for Talking Face
Intel Asia-Pacific R. & D. Center, Shanghai, P.R. China, Feb. 2019 - Jul. 2019
Engineering Intern, Web Runtime Optimization Group
Topic: Optimization of Chrome for IA (i.e., Intel Architecture) Chromebooks
Visiting Student, University of Maryland, Washington, D.C., U.S.A., Jul. 2018 - Aug. 2018
Topic: Participate leadership-related courses, School of Public Policy
2020 Fall: ENGG1110E Problem Solving By Programming
William J. McCalla ICCAD Best Paper Award, The IEEE Council on Electronic Design Automation (CEDA) and the ACM Special Interest Group on Design Automation (ACM SIGDA), 2021
Full Postgraduate Scholarship, The Chinese University of Hong Kong, 2020 - 2024
Outstanding Graduate, The Education Department of Sichuan Province, 2020
Excellent Thesis Award, The University of Electronic Science and Technology of China, 2020
National Scholarship, Ministry of Education, 2017 - 2018
National Scholarship, Ministry of Education, 2016 - 2017
Meritorious Winner of Interdisciplinary Contest on Modeling (ICM), COMAP, INFORMS, SIAM, MAA, ASA, AMS, 2018