Hi , I am
Weikai Li .

Computer Science Ph.D. Student

About Me

Hi! I am Weikai Li (李伟楷). I am a PhD student at the Computer Science Department, UCLA, where I am fortunate to be advised by Prof. Yizhou Sun. I also closely work with Prof. Jason Cong. I obtained my bachelor's degree at the Department of Computer Science and Technology, Tsinghua University. During my undergraduate, I was fortunate to be advised by Prof. Jie Tang, Prof. Yuxiao Dong, and Prof. Juanzi Li. My email address is weikaili@cs.ucla.edu.

My research interest broadly lies in graph neural networks (GNNs), large language models (LLMs), and their applications, especially their intersection with electronic design automation (EDA). Specifically, I have research experience in designing GNN models, developing GNN benchmarks, studying AI for EDA, analyzing the limitations of LLMs' in-context learning, and knowledge locating and editing of LLM.

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education

Aug. 2013 - Jun. 2019

Middle School and High School

Tsinghua University High School

Beijing, China

Aug. 2019 - Jun. 2023

Bachelor of Engineering

Tsinghua University

Beijing, China

Computer Science and Technology

GPA ranking: Top 10 out of 195

Outstanding Graduate of Tsinghua University

Sep. 2023 - Present

Ph.d. Student

University of California, Los Angeles (UCLA)

California, USA

Computer Science Department

Advisor: Professor Yizhou Sun

Intern Experience

  • Jul. 2022 - Oct. 2022

    Research Intern

    UCLA Computer Science Department

    California, USA

    Advised by Prof. Yizhou Sun

Publications

Hierarchical Mixture of Experts: Generalizable Learning for High-Level Synthesis

Weikai Li, Ding Wang, Zijian Ding, Atefeh Sohrabizadeh, Zongyue Qin, Jason Cong, Yizhou Sun

Arxiv, 2024
[ Paper]
Learning to Compare Hardware Designs for High-Level Synthesis

Yunsheng Bai, Atefeh Sohrabizadeh, Zijian Ding, Rongjian Liang, Weikai Li, Ding Wang, Haoxing Ren, Yizhou Sun, Jason Cong

MLCAD 2024
[ Paper]
Efficient Task Transfer for HLS DSE

Zijian Ding, Atefeh Sohrabizadeh, Weikai Li, Zongyue Qin, Yizhou Sun, Jason Cong

ICCAD 2024
[ Paper]
Fast Inference of Removal-Based Node Influence

Weikai Li, Zhiping Xiao, Xiao Luo, Yizhou Sun

WWW 2024
When does In-context Learning Fall Short and Why? A Study on Specification-Heavy Tasks

Hao Peng*, Xiaozhi Wang*, Jianhui Chen*, Weikai Li, Yunjia Qi, Zimu Wang, Zhili Wu, Kaisheng Zeng, Bin Xu, Lei Hou, Juanzi Li

ArXiv, 2023
[ Paper]
KoLA: Carefully Benchmarking World Knowledge of Large Language Models

Jifan Yu*, Xiaozhi Wang*, Shangqing Tu, Shulin Cao, Daniel Zhang-Li, Xin Lv, Hao Peng, Zijun Yao, Xiaohan Zhang, Hanming Li, Chunyang Li, Zheyuan Zhang, Yushi Bai, Yantao Liu, Amy Xin, Nianyi Lin, Kaifeng Yun, Linlu Gong, Jianhui Chen, Zhili Wu, Yunjia Qi, Weikai Li, Yong Guan, Kaisheng Zeng, Ji Qi, Hailong Jin, Jinxin Liu, Yu Gu, Yuan Yao, Ning Ding, Lei Hou, Zhiyuan Liu, Bin Xu, Jie Tang, Juanzi Li

ICLR 2024
[ Paper] [Code]
Rethinking the Setting of Semi-supervised Learning on Graphs

Ziang Li*, Ming Ding*, Weikai Li, Zihan Wang, Ziyu Zeng, Yukuo Cen, Jie Tang

IJCAI 2022
[Paper] [Code]

Selected Awards

Academic Services

Conference reviewer: ICLR 2024, ICML 2024, ACMMM 2024, NeurIPS 2024, LoG 2024, AAAI 2025, ICLR 2025
Journal reviewer: IEEE TBD 2024, PLOS ONE 2024

Teaching Assistant

2024 Summer: CS 97 (Introduction to Data Science) for high school students, UCLA
2024 Fall: CS 31 (Introduction to Computer Science I), UCLA
2024 Winter: CS 31 (Introduction to Computer Science I), UCLA