About Event
Artificial intelligence (AI) is rapidly transforming how we understand, diagnose, and treat cancer by expanding the boundaries of what is possible in our research. By harnessing Silicon Valley's incredible power and expertise, Stanford is uniquely positioned to forge technological innovations in cancer science. Recognizing the landscape of AI and prioritizing cross-disciplinary partnerships will enable us to be at the forefront of scientific advancements that define the future of cancer diagnosis and treatment.
On November 4, 2025, we held our inaugural AI and Cancer Research Symposium. The event brought together over 180 in-person and 115 virtual participants, including researchers, clinicians, engineers, and data scientists, who gathered to explore the transformative role of AI in cancer research and care.
The symposium featured dynamic discussions on AI applications in drug design, basic science, clinical care, and translational research. From improving diagnostics to accelerating drug discovery, the sessions underscored how AI is catalyzing meaningful progress across the cancer research spectrum.
Thank you to all speakers, attendees, and organizers who made this event a success. Stanford is leading the way in using AI to advance cancer care. Photos from the event can be viewed here.
- Agenda
- Speakers
- Event Organizers
- Registration
- Poster Session
- Travel Information
- FAQ's
8:00 - 8:30 a.m.
Registration & continental breakfast
8:30 - 8:50 a.m.
Welcome Remarks
Lloyd Minor, MD
Carl and Elizabeth Naumann Dean of the Stanford University School of Medicine
Steven Artandi, MD, PhD
Laurie Kraus Lacob Director, Stanford Cancer Institute
Chief Cancer Officer, Stanford Medicine – Health Care
Senior Associate Dean for Cancer Programs, Stanford Medicine
Jerome and Daisy Low Gilbert Professor of Medicine and Biochemistry
Sylvia Plevritis, PhD
William M. Hume Professor in the School of Medicine
Professor of Biomedical Data Science and of Radiology
Chair, Department of Biomedical Data Science
Associate Director, Cancer AI for the Stanford Cancer Institute
Director, Biomedical Informatics NLM Training Program
8:50 - 9:30 a.m.
Keynote speaker
Michelle Mello, JD, PhD
Professor of Law and of Health Policy
AI in Prior Authorization and Cancer Drug Coverage Decisions
9:30 - 10:50 a.m.
Session 1: AI and Drug Discovery and Design
Moderator: James Occean, Cancer Biology PhD Student, Department of Genetics
Ron Dror, PhD
Cheriton Family Professor of Computer Science
AI for Structure-Based Drug Design
Possu Huang, PhD
Assistant Professor of Bioengineering
Targeting Diseases through Intracelluar Antigens for All Patients Using AI-Driven Protein Design
Russ Altman, MD, PhD
Kenneth Fong Professor of Bioengineering, of Genetics, of Medicine, of Biomedical Data Science
Using Transformer Attention to Understand Protein Function
James Zou, PhD
Associate Professor of Biomedical Data Science
AI Agents for Automating Biomedical Discoveries
10:50 - 11:05 a.m.
Break
11:05 - 11:45 a.m.
Session 2: AI and Basic Science
Moderator: Rachel Gleyzer, Graduate Student, Department of Cancer Biology
Mengdi Wang, PhD
Professor of Electrical and Computer Engineering and the Center for Statistics and Machine Learning, Princeton University
LabOS: The AI-Scientist that Sees and Works Together with Humans
Olivier Gevaert, PhD
Associate Professor of Medicine (Biomedical Informatics) and of Biomedical Data Science
Multi-omics Modeling with Graph Neural Networks for Drug Target Interaction Discovery
11:45 a.m. - 1:00 p.m.
Poster session and lunch
1:00 - 2:20 p.m.
Session 3: AI and Clinical Science
Moderator: Jake Chang, Graduate Student, Department of Biomedical Data Science
Jason Fries, PhD
Research Engineer
Advancing Tumor Boards with EHR Foundation Models
Roxana Daneshjou, MD, PhD
Assistant Professor of Biomedical Data Science and Dermatology
Reenvisioning Skin Cancer Care: the Role of Computer Vision
Akshay Chaudhari, PhD
Assistant Professor of Radiology and Biomedical Data Science
Multi-Modal Foundation Models for Radiology
Sylvia Plevritis, PhD
William H. Hume Professor in the School of Medicine, Professor of Biomedical Data Science and of Radiology
AI Pathology and Spatial Biology: A New Lens on the Tumor Microenvironment
2:20 - 2:35 p.m.
Break
2:35 - 3:45 p.m.
Session 4: AI and Translational Science and Study Design
Moderator: Susie Avagyan, PhD Student, Department of Biomedical Data Science
Zina Good, PhD
Assistant Professor of Medicine (Immunology and Rheumatology)
Artificial Intelligence Systems for Data-Driven T Cell Therapy Design
Christina Curtis, PhD, MSc
RZ Cao Professor of Medicine, Genetics and Biomedical Data Science
Generative AI for Improved Digital Pathology Model Predictions and Interpretability
Manisha Desai, PhD
Kim and Ping Li Professor of Medicine, Biomedical Data Science, and (by courtesy) Epidemiology and Population Health
The Promise and Challenge of Integrating AI for the Design and Analysis of Cancer Research
3:45 - 4:00 p.m.
Closing remarks
4:00 - 5:00 p.m.
Networking Reception
