Stanford Computational Medicine Research Colloquium | AI in Oncology

​Zoom livestream: https://stanford.zoom.us/j/97887596012?pwd=bGVpbG1uL2ZBdEd2cHQzcVJMR3p6UT09

​Webinar ID: 978 8759 6012 | Passcode: 420642

​KEY INFO

​When: Thursday, October 22, 2026, 12:00-1:00 p.m. Pacific

​Where: Tapao Hall, 3180 Porter Drive, rooms B107 and B136, Palo Alto, CA 94304, or online via Zoom

​Lunch will be served during talk | Q&A will follow

​AFTER THE TALK

​Recordings are posted on the ARISE podcast page within a week: https://www.arise-ai.org/podcast

​SPEAKERS

​Jakob Nikolas Kather, MD, MSc.

​Hopp Foundation Professor of Artificial Intelligence in Medicine & Founding Director, Institute for Medical AI (IMAI) at Heidelberg University Hospital

​Since 1 October 2026, Professor Jakob Nikolas Kather has held the Hopp Foundation Professorship for “Artificial Intelligence in Medicine” at the Faculty of Medicine at Heidelberg University. He is founding director of the Institute for Medical AI (IMAI) at Heidelberg University Hospital and remains affiliated with TU Dresden. He is board-certified in internal medicine and holds a master's degree in Medical Physics.

​His research focuses on the development of artificial intelligence methods for clinical oncology, with an emphasis on AI-based biomarkers from histopathology, swarm learning, and autonomous clinical AI agents.

​He is the principal investigator of the ERC Starting Grant NADIR and leads research projects funded by the European Union, the German Cancer Aid, and the German Federal Ministry for Research, Technology and Space (BMFTR). He has authored more than 300 peer-reviewed publications and has received the Felix Burda Award, the Thannhauser Prize, and the Heinz Maier-Leibnitz Prize.

​THE TALK

​“AI in Oncology”

​Artificial intelligence (AI) is rapidly transforming cancer research and oncology. This talk will highlight two key areas where AI is making a major impact. First, it will discuss how AI can extract meaningful, quantitative insights from medical data, including, but not limited to, histopathology images. AI tools can help predict cancer outcomes, treatment responses, genetic alterations, and gene expression, using data that is already routinely collected. These approaches have the potential to reduce the workload for clinicians, improve consistency in reporting, and reveal patterns that were previously hidden.

​Second, it will explore the emerging role of large language models (LLMs) and AI agents. LLMs can now reason, plan, and act – allowing them to perform complex, multi-step tasks with minimal human input. When used as agents, they can interact with external software or databases, and even help design drugs or recommend treatment strategies. These capabilities go beyond traditional AI systems and are opening up new possibilities in both research and clinical care.

​HOST & MODERATOR

​Hosted by the Stanford Division of Computational Medicine. Moderated by Jonathan H. Chen, MD, PhD, PI at Stanford ARISE.

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