Zifeng Wang
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Zifeng Wang 王子丰 | How to pronounce? Contact
Email: zifengw2 [at] illinois (dot) edu201 North Goodwin Avenue MC 258 Urbana, IL 61801-2302 |
Hi, this is Zifeng. I am currently pursuing a PhD in Computer Science at Sunlab@UIUC, advised by Prof. Jimeng Sun.
I develop AI to accelerate scientific discovery in medicine, specifically:
Our research was featured by: Nature, NIH News, NIH Director's Blog, POLITICO, AUA News, Azure Government, Editors' Highlights at Nat. Commun.
Since 2023, we've been building Keiji.AI, a startup focusing on AI for clinical trials. We've partnered with leading pharmaceutical companies using AI to optimize eligibility criteria, streamline trial document drafting, and analyze real-world data.
News
- [Nov 2024] Our paper TrialGPT for patient-trial matching has been accepted by Nature Communications! Featured as Editors' Highlights.
- [Nov 2024] Our perspective paper on adapting generalist AI to medicine has been released!
- [Nov 2024] Our paper on LLMs for clinical data science code generation has been released!
- [June 2024] Two our research papers on clinical trial foundation model and LLM pipeline for clinical evidence synthesis have been released!
- [Mar 2024] Our research on AI for clinical trials is reported by Nature: How AI is being used to accelerate clinical trials.
- [Feb 2024] Our research in patient-trial matching is reported by AUANews: Connecting Patients to Clinical Trials With Artificial Intelligence.
Education
Ph.D. Student, Computer Science, University of Illinois Urbana-Champaign, 2021 - Present
Supervised by Prof. Jimeng Sun.
M.S., Data Science, Tsinghua University, 2018 - 2021
Supervised by Prof. Shao-Lun Huang & Prof. Khalid M. Mosalam.
Award: Outstanding MS graduate of Tsinghua University; National scholarship of graduate student
B.S., Engineering, Tongji University, 2014 - 2018
Experience
Research Intern, AWS, Amazon, May-Aug. 2023.
Topic: AI for Drug Discovery.
Mentor: Zichen Wang.
Research Intern, Medidata, Dassault Systèmes, Feb-May. 2023.
Topic: Synthetic Data Generation for Clinical Trials.
Mentor: Mandis Beigi.
Research Intern, Amplitude, May-Aug. 2022.
Topic: Multi-treatment Causal Inference.
Mentor: Cao Xiao.
Research Intern, Jarvis Lab, Tencent , Dec. 2019-Jun. 2021.
Topics: Graph DL for Clinical Diagnosis; Lifelong Learning Diagnostic AI; Information-theoretic DL.
Mentor: Yefeng Zheng.
Activity & Award
News coverage by National Institutes of Health: NIH-developed AI algorithm matches potential volunteers to clinical trials, 2024
News coverage by Nature: How AI is being used to accelerate clinical trials, 2024
News coverage by AUANews: Connecting Patients to Clinical Trials With Artificial Intelligence, 2024
Yee Memorial Fellowship, 2023
NeurIPS Scholar Award, 2022
Service
PC Member/Reviewer for ICML'[25], NeurIPS'[22,23,24], EMNLP'[22,23], IJCAI'[22,23,24], AAAI'[22,24,25], NAACL'24, COLM'[24,25], ICLR'24, ACL'23, KDD'23, NLPCC'24, ICIP'21, RECOMB'25, ICASSP'21.
Reviewer for TPAMI, JAIR, JAMIA, Bioinformatics, ACM Computing Surveys.
Teaching Experience
Spring 2022, TA for CS598 Deep Learning for Healthcare in UIUC, given by Prof. Jimeng Sun.
Summer 2020, TA for Optimization Models and Applications, given by Prof. Laurent El Ghaoui.
Spring 2020, TA for Bayesian Learning and Data Analysis, given by Prof. Ercan E. Kuruoglu.
Fall 2019, TA for Learning from Data, given by Prof. Yang Li.
Invited Talk
Aug, 2025, Invited talk: "Large Language Models for Clinical Trial Search, Recruitment, and Design", in Invited Program@Takeda in JSM'25.
Jan, 2025, Invited talk: "Large language models for clinical trial participant recruitment", in IT Roundtable of Clinical Research Forum.
Mar, 2024, Bridging Biomedical Foundation Models, invited by Xuegong Lab@Tsinghua University.
Oct, 2023, Bridging Biomedical Foundation Models, invited by AI4Science@ByteDance.
Oct, 2023, Automate clinical trial design with large language models, invited by Medidata.
Aug, 2023, Medical Vision-Language Modeling, invited by Prof. Lee@UToronto.
July, 2023, Medical Vision-Language Modeling, invited by Stanford MedAI Group.
July, 2023, Unifying Large Language Models and Knowledge Graphs, invited by Amazon Titan Lab.
Apr, 2023, Medical Vision-Language Modeling from Unpaired Images and Texts, invited by National Center for Biotechnology Information (NCBI-NLM-NIH).
Feb, 2023, Advances in Transfer Learning for Tabular Prediction (CN), invited by AI Time.
Nov, 2022, How to do transfer learning and zero-shot learning on the tabular domain? (CN), invited by AI Time
April, 2022, Understanding Deep Learning via Information in Weights, invited by AI Time.
March, 2022, PAC-Bayes Information Bottleneck, invited by ReadPaper.
