Yu Zhang Ph.D. student Department of Computer Science and Engineering The Chinese University of Hong Kong Email:yuzhang712@link.cuhk.edu.hk

Biography

I am currently a final-year Ph.D. candidate at the Department of Computer Science and Engineering, The Chinese University of Hong Kong (CUHK), under the supervision of Prof. Bei Yu. I also work as a research intern at NVIDIA’s Deep Learning Efficiency Research Group. My research interests are efficient LLM training/inference, software/hardware co-design, and LLM reasoning. Besides research, I love swimming and hiking in my spare time.

Research Directions

My research directions include:

• LLM Efficiency and Reasoning: [C9, C10, C11]

• Mathematical Optimization: [C4, C6, C7, C8]

• Federated Learning: [C5, J1]

• Green Energy: [C1, C2, C3]

Publications

Conference Papers

• [C11] Yu Zhang, Hui-Ling Zhen, Mingxuan Yuan, Bei Yu, “MOSS: Efficient and Accurate FP8 LLM Training with Microscaling and Automatic Scaling”.

• [C10] Yu Zhang, Mingzi Wang, Lancheng Zou, Wulong Liu, Hui-Ling Zhen, Mingxuan Yuan, Bei Yu, “MixPE: Quantization and Hardware Co-design for Efficient LLM Inference”.

• [C9] Yu Zhang, Hui-Ling Zhen, Zehua Pei, Yingzhao Lian, Lihao Yin, Mingxuan Yuan, Bei Yu, “DiLA: Enhancing LLM Tool Learning with Differential Logic Layer”, , SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), Jeju, Korea, Aug. 9–13, 2026.

• [C8] Yu Zhang, Hui-Ling Zhen, Mingxuan Yuan, Bei Yu, “DiffSAT: Differential MaxSAT Layer for SAT Solving”, IEEE/ACM International Conference on Computer-Aided Design (ICCAD), New Jersey, Oct. 27–31, 2024.

• [C7] Yuan Pu, Fangzhou Liu, Yu Zhang, Zhuolun He, Kai-Yuan Chao, Yibo Lin, Bei Yu, “Lesyn: Placement-aware Logic Resynthesis for Non-Integer Multiple-Cell-Height Designs”, ACM/IEEE Design Automation Conference (DAC), San Francisco, Jun. 23–27, 2024.

• [C6] Yu Zhang, Yuan Pu, Fangzhou Liu, Peiyu Liao, Kai-Yuan Chao, Keren Zhu, Yibo Lin and Bei Yu, “Multi-Electrostatics Based Placement for Non-Integer Multiple-Height Cells”, International Symposium on Physical Design (ISPD), March 12–15, 2024.

• [C5] Yu Zhang, Wei Lin, Sisi Chen, Qingyu Song, Jiaxun Lu, Yunfeng Shao, Bei Yu and Hong Xu, “Fed2Com: Towards Efficient Compression in Federated Learning”, International Conference on Computing, Networking and Communications (ICNC), Feb. 19–22, 2024.

• [C4] Yu Zhang*, Yifan Chen*, Zhonglin Xie, Hong Xu, Zaiwen Wen, Yibo Lin and Bei Yu, “LRSDP: Low-rank SDP for Triple Patterning Lithography Layout Decomposition”, Design Automation Conference (DAC), July 09–13, 2023. (* represents equal contribution)

• [C3] Xudong Wang, Guoming Tang, Yi Wang, Srinivasan Keshav, Yu Zhang, “Evsense: A robust and scalable approach to non-intrusive ev charging detection”, ACM International Conference on Future Energy Systems (e-Energy).

• [C2] Yu Zhang, Guoming Tang, Qianyi Huang, Yi Wang, Hong Xu, Xudong Wang, “More Behind Your Electricity Bill: a Dual-DNN Approach to Non-Intrusive Load Monitoring”, IEEE International Conference on Cyber, Physical and Social Computing (CPSCom), Aug. 22–25, 2022.

• [C1] Yu Zhang, Guoming Tang, Qianyi Huang, Kui Wu, Yangjing Wu, Yi Wang, “Investigating Low-Battery Anxiety of Mobile Users”, IEEE International Conference on Cyber, Physical and Social Computing (CPSCom), Aug. 22–25, 2022.

Journal Papers

• [J1] Yu Zhang, Guoming Tang, Qianyi Huang, Yi Wang, Kui Wu, Keping Yu, Xun Shao, “FedNILM: Applying Federated Learning to NILM Applications at the Edge”, IEEE Transactions on Green Communications and Networking (TGCN), Apr. 14, 2022.

Patent

• “一种基于模型松弛的大模型新微调方法”, 92056131CN01.

Experiences

• Research Intern, NVIDIA Research, Santa Clara, U.S., Sep 2025 - Present
  Topic: Efficient Large Language Model, LLM Hallucination Detection

• Research Intern, Huawei Noah's Ark Lab, HKSAR, Aug 2023 - Aug 2024
  Topic: Hardware/software co-design for efficient LLM inference; Differential solver layer for LLM

• Research Assistant, The Chinese University of Hong Kong, HKSAR, Nov 2021 - Jul 2022
  Topic: Communication-efficient and convergence fast federated learning

• Research Intern, Microsoft Research Asia, Beijing, P.R. China, Jan 2021 - Aug 2021
  Topic: AISimulator

Education

• Ph.D. Computer Science and Engineering, The Chinese University of Hong Kong, Aug 2022 - present

• B.S. Statistics, Central South University, Sept 2015 - Jun 2019

Professional Service

Journal Reviewer

• TNNLS, TCAD, TODAES, TGCN, VLSIJ

Conference Reviewer

• ISPD, KDD