photo of fireworks

Gautam Machiraju and Alex Derry lead team for paper accepted for publication in the 2024 International Conference on Machine Learning in Vienna, Austria

A team led by senior BMI PhD students, Gautam Machiraju and Alex Derry, is excited to announce a new paper accepted for publication in the 2024 International Conference on Machine Learning (ICML) in Vienna, Austria. This work advances new modes of inference for Foundation Models, allowing them to efficiently and accurately identify class-specific features in various data modalities (sequences, images, graphs). This work was advised by multiple Stanford-based faculty including Parag Mallick, Christopher Ré, James Zou, and Russ Altman. Congrats to the team!

Poster with agenda for VC panel

Generative AI and Healthcare VC panel

You’re invited to attend a VC panel on Generative AI and Healthcare on May 17th at 3:00PM.  The panel will feature 5 Venture Capitalists and will focus on the latest trends, challenges and success factors with AI in healthcare startups. This panel is open to all faculty, graduate students and postdocs.  It is sponsored by DBDS and the course BIODS 295 Generative AI in Healthcare.


When: May 17th, 3:00-4:30pm Panel; 4:30-5:30 Reception
Where: Chem H Building Room E153

  • Jay Rughani, a16z
  • Fern Mandelbaum, Emerson Collective
  • Cheryl Cheng, Vive Collective
  • Rafic Makki, Mubadala Capital
  • Eric Chen, OVO Fund
  • Moderator: Karen Matthys, Executive Director, DBDS
Nigam Shah/logo for Grand Rounds podcast

DBDS’ Nigam Shah on AI Grand Rounds podcast

In this episode of the AI Grand Rounds podcast, Dr. Nigam Shah, a distinguished Professor of Medicine at Stanford University and inaugural Chief Data Scientist for Stanford Health Care, shares his journey from training as a doctor in India to becoming a leading figure in biomedical informatics in the United States. He discusses the transformative impact of computational tools in understanding complex biological systems and the pivotal role of hashtagArtificialIntelligence in advancing health care delivery, particularly in improving efficiency and addressing systemic challenges. Dr. Shah emphasizes the importance of real-world integration of AI into clinical settings, advocating for a balanced approach that considers both technological capabilities and the systemic considerations of hashtagAIinMedicine. The conversation with NEJM AI Deputy Editors Arjun Manrai, PhD, and Andrew Beam, PhD, also explores the democratization of medical knowledge, why open-source models are under-researched in medicine, and the crucial role of data quality in training AI systems.

Listen to the full episode: