AI for Health Webinar

Join us for the AI4health webinar featuring conversations with industry and academic leaders pioneering AI in healthcare and biomedical applications. We'll explore recent breakthroughs, discuss real-world implementations, and address the challenges and ethical considerations of AI in medicine. This webinar aims to accelerate AI adoption in healthcare, improve patient outcomes, and offer valuable insights for healthcare professionals, researchers, and technology enthusiasts alike. This webinar is organized by Prof. Jimeng Sun from University of Illinois Urbana-Champaign.

AI for Health is preparing a new season, with webinars every two weeks featuring a mix of industry and academic leaders. Dates, speakers, and session times will be announced as they are confirmed.

Join the mailing list for announcements and Zoom links, and follow Jimeng Sun on LinkedIn for updates.

2026 program

These are historical program listings. Visit the Videos page for available recordings. Speaker affiliations below reflect the original program.

March 25, 2026 — Ying Ding, UT Austin
Chatbot: Empowering Medical Communication using AI

February 18, 2026 (3–4 p.m. ET) — Andreas Schick, FDA
Q&A with FDA: A Discussion of AI Applications and the Adoption of AI from FDA’s Perspective

February 11, 2026 — Ronald Summers, NIH
The AI revolution in multimodal radiology informatics

January 28, 2026 — Qi Long, University of Pennsylvania
Advancing Responsible Statistical and AI/ML Methods for Harnessing the Power of Electronic Health Records

Scheduling updates: The previously listed February dates for Kim Branson and Nicholas Tatonetti were superseded. New-season participation and dates will be announced after reconfirmation. Zhiyong Lu’s April 29, 2026 session was cancelled.

2025 program

November 5 (3–4 p.m. ET) — Mark Gerstein, Yale

AI Methods for Biomedicine

October 29 — Casey Greene, University of Colorado

October 1 (3–4 p.m. ET) — Connor Coley, MIT

September 24 — Edward Choi, KAIST (special time: 11 a.m.–12 p.m. ET)

September 3 — Yun Liu, Google Health

August 27 — David Page, Duke University
Making Neural Nets More Causally Accurate for Clinical Applications

May 28 — David Sontag, MIT
Towards Precision Oncology: A Predictive, Causal, and LLM Lens

May 21 — Hua Xu, Yale
Large Language Models for Biomedical Applications

May 14 — Aaron Lee, University of Washington
Building biomedical datasets for the future of AI

May 7 — Tristan Naumann, Microsoft Research
Biomedical NLP in the Age of GenAI

April 30 — Emily Alsentzer, Stanford
Knowledge-Enhanced Machine Learning for Healthcare

April 23 — Joyce Ho, Emory University
Beyond EHRs: Bridging Clinical Records and External Knowledge for Better Patient Outcomes

April 9 — PyHealth Clinical Predictive Modeling Panel

April 2 — Sanmi Koyejo, Stanford University

March 26 — Jimeng Sun, Chufan Gao, Jathurshan Pradeepkumar and Trisha Das, UIUC
Panel discussion on trial outcome prediction benchmark [paper, website]

March 19 — Faisal Mahmood, Harvard University
Multimodal, Generative and Agentic AI for Pathology

March 12 — Zifeng Wang, UIUC
Large language models for clinical trial design, execution, and analysis

February 26 — James Zou, Stanford University
AI agents for biomedicine and healthcare

February 19 — Jenna Wiens, University of Michigan
White Coat, Black Box — Navigating Pitfalls in Using AI to Augment Diagnostic Decision Making

February 12 — Sheng Wang, University of Washington
Generative AI for Multimodal Biomedicine: applications in pathology and retinal imaging

February 5 (special time: 1–2 p.m. ET) — Marzyeh Ghassemi, MIT
Taking the Pulse of Ethical ML in Health

January 29 — Brian Martin, AbbVie
Providing Rare Hope for Even Rarer Diseases: How AI can enable broad mining of knowledge and data to power drug repurposing for rare diseases

2024 program

October 9 — Bradley Malin, Vanderbilt University
Baking Responsibility into the AI for Health Lifecycle

September 25 — Pranav Rajpurkar, Harvard University
The Generalist Medical AI Will See You Now (special time: 12:30–1:30 p.m. CT)

September 18 — Hoifung Poon, Microsoft Research
Multimodal Generative AI for Precision Health

September 11 — Parminder Bhatia, Chief AI Officer, GE HealthCare
Unleashing the power of Medical Imaging Foundation Models

May 22 — Lucas Glass, SVP, IQVIA
Getting past the academics of AI to generate financial value: Case studies in AI for Clinical Trials

May 1 — Pengtao Xie, Assistant Professor, UC San Diego
Foundation Models and Generative AI for Medical Imaging Segmentation in Ultra-Low Data Regimes

April 24 (3–4 p.m. ET) — Vera Mucaj, Chief Scientist, Datavant
AI and the healthcare data logistics problem