Zifeng Wang

Hi, this is Zifeng. I am the co-founder and head of AI at Keiji.AI. Before that, I did my PhD in Computer Science at Sunlab@UIUC, advised by Prof. Jimeng Sun. I develop AI to accelerate scientific discovery in medicine, specifically:

Literature research: accelerating the study search, screening, and data extraction from the literature to generate novel hypotheses and clinical evidence [1, 2]

Data science research: streamlining the data science hypothesis generation and validation based on medical and biomedical data via the collaboration of researchers and AI assistants [3]

Clinical research: developing AI models and workflows to enhance the design, execution, and analysis of clinical trials [4, 5, 6]

Our research was featured by: Nature, NIH News, NIH Director's Blog, POLITICO, AUA News, Azure Government, Editors' Highlights at Nat. Commun.

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.

Recent Talks

AI for health webinar

@ Sunlab, UIUC

Invited Talk

@ MedAI, Stanford University

Invited Talk (Chinese)

@ HIT Webinar

Mar, 2025, "Medical scientific discovery in the era of large language models", in HIT Webinar.

Mar, 2025, "Medical scientific discovery in the era of large language models", in Zuozhu's Lab@Zhejiang University.

Mar, 2025, "Large language models for clinical trial design, execution, and analysis", in AI for Health Webinar.

Jan, 2025, "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.

[Show more]

Honors & Awards

[2024] Research featured in Nature: How AI is being used to accelerate clinical trials

[2024] Research featured by NIH: AI algorithm matches potential volunteers to clinical trials

[2023] Yee Memorial Fellowship, University of Illinois Urbana-Champaign

[2022] NeurIPS Scholar Award, Neural Information Processing Systems Conference

[2022] Yunni & Maxine Pao Memorial Fellowship, University of Illinois Urbana-Champaign

[2021] Best Student Paper Award, Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD)

Zifeng's Homepage

Zifeng Wang 王子丰 How to pronounce?

News

Recent Talks

Honors & Awards