Speaker Profile
PMWC LUMINARY AWARD
Ph.D., Nobel laureate, Director, U. of Washington
Biography
David Baker is a Nobel laureate, professor of biochemistry, HHMI investigator, and director of the Institute for Protein Design at the University of Washington. His lab develops software for protein design and uses it to create molecules that address challenges in medicine, technology, and sustainability. Recent work includes the development of machine learning methods for generating functional proteins.
David is also an adjunct professor of genome sciences, bioengineering, chemical engineering, computer science, and physics at the University of Washington. He has published more than 650 scientific papers, been awarded over 100 patents, and co-founded 21 biotechnology companies. More than 100 of his trainees have gone on to independent faculty positions.
He is the recipient of numerous awards, including the 2024 Nobel Prize in Chemistry “for computational protein design.” He is an elected member of the National Academy of Sciences, National Academy of Engineering, and National Academy of Inventors. David was also included on TIME’s inaugural list of the 100 Most Influential People in health.
David received his PhD in biochemistry with Randy Schekman at the University of California, Berkeley, and conducted postdoctoral research in biophysics with David Agard at UCSF.
Session Abstract – PMWC 2027 Silicon Valley
Track Chair:
Alex Morgan, Khosla Ventures and Gad Getz, Broad Institute
PMWC Award Ceremony
• Steve Wozniak, Apple
• Greg Brockman, OpenAI
Fireside Chat
• Vinod Khosla, Khosla Ventures
• Greg Brockman, OpenAI
Target Discovery: Beyond Genomics – Revealing Hidden Layers of Biology with AI
• Chair: Cindy Lawley, Olink
• Aritro Nath, City of Hope
• John Quackenbush, Harvard
• Massa Shoura, Phinomics
• Omar Serang, DNAnexus
Foundation Models of Human Cancer Biology to Predict Clinical Outcomes
• Ron Alfa, Noetik
Mechanistic Modeling of the Human Immune System: A Data-Integrated Approach to Target and Biomarker Discovery
• Liat Dassa, CytoReason
Biological Foundation Models: Harmonizing Data to Accelerate Drug Discovery
• Vitalay Fomin, Numenos
From Prediction to Translation: AI and In Vivo Validation to Improve Drug Development Success
• Gabriel Musso, BioSymetrics
Interpretable AI for Biomarker Discovery: Accelerating Drug Development and Advancing Precision Medicine
• Chair: Shivanni Kummar, PATHOMIQ
• Dale Muzzey, Myriad Genetics
• Sanoj Punnen, University of Miami
• Mark Burkard, UI
Can AI Really Create the Next Blockbuster Drug? Closing the Loop from Drug Discovery to Development
• Chair: Amar Das, Guardant Health
• Dina Katabi, Emerald/MIT
• Andrei Georgescu, Vivodyne
• James Zou, Stanford
Gemini Digital Twins Accelerate Precision Medicine
• Collin Hill, Aitia
Scaling Rare Disease Discovery with AI: From Genomic Data to Therapeutic Insights
• Lisa Gurry, GeneDx
Limited Sample Models for Faster Lead Discovery, High Accuracy, and Regulatory Grade AI
• Lalin Theverapperuma, Expert Intelligence
Enabling Targeted Precision Drug & Gene Delivery with Predictive AI
• Andre Watson, Ligandal
Is AI the New Drug or the New Therapeutic Modality
• Chair: Alex Morgan, Khosla Ventures
• Michael J. Kahana, Nia Therapeutics
• Marc Tessier-Lavigne, Xaira
• Achal Achrol, Magnus Medical
