Zehua Pei
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Ph.D. Student |
I am currently a second-year PhD student at Department of Computer Science and Engineering, The Chinese University of Hong Kong, supervised by Prof. Bei Yu and co-supervised by Prof. Sinno Jialin Pan since 2023 Fall. I am also under the Huawei PhD Fellowship Program, co-supervised by a Huawei professional Dr. Huiling Zhen. Prior to that, I obtained my B.S. degree in Mathematics at The Chinese University of Hong Kong in 2022.
Recent News
May/2024: Congratulation! Our work on LLM on Verilog generation is accepted by International Conference on Machine Learning (ICML)! See you in Vienna!
Jul/2023: Congratulation! Our work on logic synthesis is accepted by IEEE/ACM International Conference on Computer-Aided Design (ICCAD)!
Jul/2023: Congratulation! Our work on quantization is accepted by IEEE Transactions on Neural Networks and Learning Systems (TNNLS)!
Research Interests
My research interests include
Machine Learning
Electronic Design Automation
Model Compression
Selected Preprints
“FuseGPT: Learnable Layers Fusion of Generative Pre-trained Transformers”. (arXiv)
“SoLA: Solver-Layer Adaption of LLM for Better Logic Reasoning”. (arXiv)
Publications
Conference Papers
[C6] Zehua Pei, Hui-Ling Zhen, Mingxuan Yuan, Yu Huang, Bei Yu, “BetterV: Controlled Verilog Generation with Discriminative Guidance”, International Conference on Machine Learning (ICML), Vienna, Austria, Jul. 21–27, 2024. (arXiv)
[C5] Fangzhou Liu, Zehua Pei, Ziyang Yu, Haisheng Zheng, Zhuolun He, Tinghuan Chen, Bei Yu, “CBTune: Contextual Bandit Tuning for Logic Synthesis”, IEEE/ACM Proceedings Design, Automation and Test in Europe (DATE), Valencia, Spain, Mar. 25–27, 2024.
[C4] Haisheng Zheng, Zhuolun He, Fangzhou Liu, Zehua Pei, Bei Yu, “LSTP: A Logic Synthesis Timing Predictor”, IEEE/ACM Asian and South Pacific Design Automation Conference (ASPDAC), South Korea, Jan. 22–25, 2024. (paper)
[C3] Zehua Pei, Fangzhou Liu, Zhuolun He, Guojin Chen, Haisheng Zheng, Keren Zhu, Bei Yu, “AlphaSyn: Logic Synthesis Optimization with Efficient Monte Carlo Tree Search”, IEEE/ACM International Conference on Computer-Aided Design (ICCAD), San Francisco, Oct. 29–Nov. 02, 2023. (paper)
[C2] Guojin Chen, Zehua Pei, Haoyu Yang, Yuzhe Ma, Bei Yu, Martin Wong, “Physics-Informed Optical Kernel Regression Using Complex-valued Neural Fields”, ACM/IEEE Design Automation Conference (DAC), San Francisco, Jul. 09–13, 2023. (paper)
[C1] Zehua Pei, Wenqian Zhao, Zhuolun He, Bei Yu, “Bit-Level Quantization for Efficient Layout Hotspot Detection”, International Symposium of EDA (ISEDA), May 9–11, 2023. (paper)
Journal Papers
[J2] Juncheng Li, Zehua Pei, Wenjie Li, Guangwei Gao, Longguang Wang, Yingqian Wang, and Tieyong Zeng, “A Systematic Survey of Deep Learning-based Single-Image Super-Resolution”, ACM Computing Surveys (ACM COMPUT SURV).
[J1] Zehua Pei, Xufeng Yao, Wenqian Zhao, Bei Yu, “Quantization via Distillation and Contrastive Learning”, IEEE Transactions on Neural Networks and Learning Systems (TNNLS).
Experience
Researcher | Shanghai AI Lab, AI4EDA
Oct. 2022 - Jun. 2023
Intern | SmartMore, Hong Kong
Dec. 2021 - Sep. 2022
Research Intern | The Chinese University of Hong Kong, CMAI
Advisor: Prof. Tieyong Zeng
Jan. 2021 - Jul. 2021
Teaching duty
For CUHK students in the course that I am the TA, feel free to contact me with the email address: zhpei23@cse.cuhk.edu.hk
AIST2010 (2023T1) ECLT5830 (2023T1) AIST3110 (2023T2) CMSC5743 (2024T1)