Hi, I'm Fang WU!

Welcome to my personal web page! I am a Ph.D. student at Stanford Computer Science and a Graduate Fellow at Stanford HAI, advised by Yejin Choi and Jure Leskovec. I have had the great fortune to work with James Zou and Brian Trippe. Previously, I was a research engineer at Tsinghua University, advised by Jinbo Xu. I obtained my Master's degree at Columbia University, advised by Dragomir Radev. It is a profound loss for me to lose Prof. Radev on March 29, 2023 (in memoriam). My present research focuses on LLMs, agent systems, and AI4Science.

                
Email: fangwu97 [at] stanford [dot] edu
Address: Palo Alto, CA, USA
Last update time: 2026.09

News and Highlights

   [2026/08] Two co-author papers are accepted by EMNLP 2026.
   [2026/07] One co-author paper is published at Patterns.
   [2026/07] One co-author paper is accepted by COLM 2026.
   [2026/05] Three papers (one Oral) are accepted by KDD 2026 AI4Science Track.
   [2026/05] Four papers are accepted by ICML 2026.
   [2026/04] One paper on d-peptide design is accepted by IEEE JBHI.
   [2026/01] Three papers (one Oral) are accepted by ICLR 2026.
   [2025/09] One corresponding-author paper is accepted by NeurIPS 2025.
   [2025/05] One paper is accepted by KDD 2025.
   [2025/05] Two papers are accepted by ACL 2025.
   [2025/04] One collaborated paper is accepted by ICML 2025. Congrats to Arthur Deng!
   [2025/02] One paper on mutant effect prediction is accepted by TMLR.
   [2024/12] One paper on dynamic surface modeling is accepted by AAAI 2025.
   [2024/11] One collaborated paper on protein-ligand docking is accepted by Nature Communications.
   [2024/09] One paper on semi-supervised learning is accepted by NeurIPS 2024.
   [2024/03] One paper on GNN bottleneck is accepted by IEEE TKDE.
   [2024/03] One paper is accepted by ICML 2024 and another paper is accepted by IJCAI 2024.
   [2023/10] One paper is accepted by Nature Communications.
   [2023/09] One paper is accepted by NeurIPS 2023.
   [2023/06] One paper is accepted by Communications Biology.
   [2023/04] One paper and another co-authored paper are accepted by ICML 2023.
   [2023/02] One work on molecular domain adaptation is accepted by Cell Patterns.
   [2022/12] Two papers are accepted by AAAI 2023.
   [2022/10] One work on 3D pretraining is accepted by Advanced Science.

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Research Summary

* represents equal contribution and co-first authorship. † denotes the corresponding author(s).

Invited Talks

• Jun 2026

  Gave a closing talk on Proteo-R1 at Compound Research Day: BioML Frontiers in San Francisco.

• Jun 2026

  Gave a talk on Proteo-R1 at the Mila Multiomics Reading Group.

• May 2026

  Gave a talk on Proteo-R1 at the Machine Learning for Protein Engineering Seminar.

• Oct 2025

  Gave a talk on reinforcement learning with verifiable rewards for LLM reasoning at the Stanford Graph Learning Workshop.

• Jan 2023

  Gave a talk on ProtMD at the M2D2 Seminar, invited by Mila and Valence Discovery.

Education

   Stanford University
   2024 — Present
   • Ph.D. in Computer Science

   Columbia University
   2019 — 2021
   • Master of Science; GPA: 3.51/4.0

   Central University of Economics and Finance
   2015 — 2019
   • Bachelor of Science; GPA: 3.85/4.0

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Industry Experience

   Research Scientist Intern (2025.06)
   • Bytedance Research
   • Led by Quanquan Gu

   Machine Learning Research Scientist (2023.06-2024.06)
   • BioMap
   • Led by Le Song

   AI Researcher (Intern) (2022.01-2022.07)
   • MindRank
   • Led by Zhangming Niu

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Research Experience

Before joining Stanford University, I feel fortunate to be a research assistant/engineer advised by Jinbo Xu and Stan Z. Li, and received guidance as a visiting student from Huajun Chen, Xiang Bai and Danny Lan.

   Research Student (2024.09-2024.12)
   • Arc Institute
   • Advised by Brian Hie

   Research Engineer (2022.08-2023.05)
   • MoleculeMind & Tsinghua University
   • Advised by Jinbo Xu

   Research Assistant (2021.11-2022.07)
   • Westlake University
   • Advised by Stan Z. Li

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Professional Services

Conference Reviewer: NeurIPS 2023-2026, ICLR 2024-2027, ICML 2025-2026, COLM 2026, ACL-ARR 2025-2026, CVPR 2025, ICCV 2025, WACV 2026, ACM MM 2025-2026, ACM MM Asia 2025, KDD 2025-2026, WWW 2026, AAAI 2026-2027, AISTATS 2025-2026, IJCAI 2025, MLHC 2023-2026, ML4H 2025-2026

Journal Reviewer: Advanced Science, Patterns, Cell Reports Physical Science, Scientific Reports, IEEE TNNLS, TMLR, Bioinformatics, WIREs Computational Molecular Science, Discovery Artificial Intelligence, ACM TKDD

Teaching: CS224N: Natural Language Processing with Deep Learning (Winter 2024, Winter 2025)