2024 PQG Conference: AI for Genomics and Health

Thursday, October 17, 2024

8:30-9:00 am Registration & Breakfast | Joseph B. Martin Conference Center, 3rd Floor Rotunda

9:00-9:05 Opening Remarks

SESSION 1:  AI for Genomics
Moderators: Kyle Vogan

* last 5 minutes of all session talks reserved for questions and discussion

9:05-9:55
John Marioni, | KEYNOTE SPEAKER
Genentech
Single Cell Genomics: Past, Present, Future

9:55-10:25
Caroline Uhler | MIT
Multimodal Data Integration: From Biomarkers to Mechanisms

10:25-10:40
Farhad Hormozdiari | Abstract Winner Platform Talk I
Applying multimodal AI to electrophysiological waveforms improves genetic prediction of cardiovascular traits

10:40-11:00  BREAK

11:00-11:30
Mo Lotfollah | Sanger Institute
Generative machine learning to model cellular perturbations

11:30-12:00
Emma Lundberd | Stanford University
Decoding human cell and tissue architectures – from spatial proteomics to whole cell modelling

12:00-1:15  LUNCH

SESSION 2: AI for Precision/Translational Medicine and Healthcare
Moderators: Bo Wang

1:15-2:05
David Blumenthal | KEYNOTE SPEAKER
Harvard T.H. Chan School of Public Health
The Regulation of Clinical Artificial Intelligence

2:05-2:35
Olivier Elemento | Cornell University
Genomes, Avatars and AI: The Future of Personalized Medicine

2:35-3:05
Trey Ideker | UC San Diego
Digital tumors for precision oncology

3:05-3:30 BREAK

3:30-3:45
Ruth Johnson | Abstract Winner Platform Talk II
Unified Clinical Vocabulary Embeddings for Advancing Precision Medicine

3:45-4:15
Tianxi Cai | Harvard School of Public Health, Harvard Medical School
Crowdsourcing with Multi-institutional EHR to Improve Reliability of Real World Evidence –Opportunities and Challenges

4:15-6:00  Poster Session and Reception | 2nd floor lounge

Friday, October 18, 2024

8:30-9:00 am  Breakfast | Joseph B. Martin Conference Center, 3rd Floor Rotunda

SESSION 3: Emerging topics in generative AI (broader and ethical aspects)
Moderators: Marinka Zitnik

9:00-9:50
Jim Collins | KEYNOTE SPEAKER
MIT
Deep Learning for Antibiotic Discovery and Synthetic Biology

9:50-10:20
Shekoofeh Azizi | Google DeepMind
Generalist Biomedical AI

10:25-10:40
Yongju Lee | Abstract Winner Platform Talk III
sCContrast : Compressed Single-cell Transcriptome Foundation Model as the building block for multi-modal foundation model

10:40-11:00  BREAK

11:00 – 11:30
Sergey Ovchinnikov | MIT
Inverting structure prediction models for protein design

11:30 -12:15    PANEL DISCUSSION
Moderator: Marinka Zitnik, HMS
Panelists:
Marzyeh Ghassemi, MIT
Hoda Heidari, Carnegie Mellon University
Marinka Zitnik, HMS
James Zou, Stanford University

12:15-12:30  Closing Remarks and  Stellar Abstract Awards