Yifan Shi Ph.D. Candidate Department of Computer Science and Engineering The Chinese University of Hong Kong Supervisor: Prof. Bei Yu Email: i.yifan [AT] link.cuhk.edu.hk

Biography

I am currently a third-year Ph.D. student at the Department of Computer Science and Engineering, The Chinese University of Hong Kong, supervised by Prof. Bei Yu since Fall 2024. Prior to that, I obtained my B.S. degree at the School of Information from Renmin University of China (RUC), class of 2024.

Research Interests

• Electronic Design Automation (EDA)

• Computer Organization and Architecture

• Large Language Models (LLM)

Publications

• Chaofan Wang, Ziyang Yu, Su Zheng, Zixiao Wang, Yifan Shi, Bei Yu, “Moreau-ILT: Efficient Inverse Lithography Exploiting Weak Convexity,” IEEE/ACM International Conference on Computer-Aided Design (ICCAD), San Jose, Nov. 08–12, 2026.

• Yuhao Ji, Jiaxi Jiang, Siting Liu, Yifan Shi, Yuntao Lu, Peng Xu, Xinyun Zhang, Ziyi Wang, Yibo Lin, Bei Yu, “LibTimer: Addressing Library Evolution in Pre-Routing Timing Prediction via Continuous Library Representation,” accepted by IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD).

Selected Awards

Postgraduate Scholarship	The Chinese University of Hong Kong	2024
National Scholarship for Undergraduates	Education Ministry of PRC	2022

Internship Experience

China Mobile (Hong Kong) Innovation Research Institute Limited	Aug 2025 - Dec 2025
Ph.D. Intern, Hong Kong
Worked on LLM-based think-tank and report-generation agents, including multi-agent workflows and RAG-based content generation. Designed argument and discourse graph planning components, evaluation metrics, and patent materials. Explored KG-based search-agent optimization for complex research and question-answering tasks.
Institute of Electronic Design Automation, Peking University	Jul 2024 - Sep 2024
Ph.D. Intern, EDA Backend Group, Wuxi, Jiangsu Province
Supervised by Prof. Yibo Lin and Dr. Zuodong Zhang
Conducted early-stage research for DiffPDN, including IR-drop and PDN optimization literature review. Explored differentiable physical modeling for power delivery network resizing and relocation. Prepared backend EDA experiment settings and supporting analysis.

Project Experience

Assisted Project: Physics-aware CPU Timing Prediction

• Huawei Hong Kong Research Center collaboration

• Assisted development and documentation of a GNN/GCN-based timing prediction flow using netlist and layout features, timing-endpoint masks, CNN layout encoding, and STA-aware prediction.

Teaching Experience

• Teaching Assistant, CSCI1130: Introduction to Computing Using Java, Fall 2024

• Teaching Assistant, CENG3420: Computer Organization & Design, Spring 2025

• Teaching Assistant, CENG3420: Computer Organization & Design, Spring 2026

Skills

• Programming Languages: C/C++, Python, Java, SQL, Verilog/SystemVerilog

• Languages: Mandarin (native speaker), English (proficient), Français (DELF A2), Cantonese (practical)

• Tools: LaTeX, Wolfram Mathematica, PyTorch, CUDA

• Hobbies: Clarinet, Travelling, Table Tennis, Photography, and so much more