About

For centuries, the method of discovery—the fundamental practice of science that scientists use to explain the natural world systematically and logically—has remained largely the same. Artificial intelligence (AI) and machine learning (ML) hold tremendous promise in having an impact on the way scientific discovery is performed today at the fundamental level. However, to realize this promise, we need to identify priorities and outstanding open questions for the cutting edge of AI going forward. We are particularly interested in the following topics:

Attendance

We welcome people with diverse background and level of experience to attend our workshop. The attendance is not contingent upon paper submission. Consider to apply for a travel award.

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Please follow us on Twitter and LinkedIn for the latest news, or join us on the Slack for active discussions.

Invited Talks (In alphabetical order)

David Baker

David Baker
UW
AI, Biology

Weinan E

Weinan E
Princeton and PKU
AI, Applied Mathematics

Tess Smidt

Tess Smidt
MIT
AI, Physical Sciences

Shuiwang Ji

Shuiwang Ji
TAMU
AI, Chemistry

Jimeng Sun

Jimeng Sun
UIUC
AI, Health

Maria Schuld

Maria Schuld
Xanadu
AI, Quantum Computing

Panel: Landing of AI for Science and future of AI for Science in industry

Peter Lee

Peter Lee
Microsoft Research & Incubations

Sara-Jane Dunn

Sara-Jane Dunn
DeepMind

Arvind Rajpal

Arvind Rajpal
Genetech

Alexander Rives

Alexander Rives
New York University, Facebook AI Research

Max Welling (Moderator)

Max Welling (Moderator)
University of Amsterdam, Microsoft Research

Schedule

08:00 AM – 06:00 PM (Central Time), Dec 2, 2022

Event   Time
Openning Remarks Organizing Team 8:00-8:15am
Invited Talk Weinan E 8:15-9:10am
Invited Talk Shuiwang Ji 9:10-10:05am
Coffee Break - 10:05-10:15am
Invited Talk Maria Schuld 10:15-11:10am
Invited Talk David Baker 11:10-12:05pm
Poster Session   12:05pm-13:00pm
Contributed Talk DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking 13:00-13:10pm
Contributed Talk An “interpretable-by-design” neural network to decipher RNA splicing regulatory logic 13:10-13:20pm
Contributed Talk FALCON: Fourier Adaptive Learning and Control for Disturbance Rejection Under Extreme Turbulence 13:20-13:30pm
Contributed Talk Structural Causal Model for Molecular Dynamics Simulation 13:30-13:40pm
Contributed Talk Structure-Inducing Pre-training 13:40-13:50pm
Panel Discussion Panelists: Peter Lee, Sara-Jane Dunn, Arvind Rajpal, Alexander Rives, Matt Welborn
Moderator: Max Welling
13:55-14:55pm
Coffee Break - 14:55-15:10pm
Invited Talk Jimeng Sun 15:10-16:05pm
Invited Talk Tess Smidt 16:05-17:00pm
Closing Remarks Organizing Team 17:00-17:10pm
Poster Session   17:10-18:00pm

Important Dates (Anywhere on Earth)

Submissions

Please submit your paper in Openreview. Our workshop is nonarchival, the accepted papers will be posted on our website.

Organizers and Contact

Organizers are in the alphabetical order. For any question, please contact ai4sciencecommunity@gmail.com.

Student Organizers (alphabetical order)

Daisy Yi Ding

Daisy Yi Ding
Stanford
AI for Multiomics

Yuanqi Du

Yuanqi Du
Cornell
AI for Science

Chenru Duan

Chenru Duan
MIT
AI for Chemistry

Tianfan Fu

Tianfan Fu
Gatech
AI for drug design and development

Hanchen Wang

Hanchen Wang
Cambridge/Caltech
AI for Medical Science

Senior Organizers

Anima Anandkumar

Anima Anandkumar
Caltech, NVIDIA

Yoshua Bengio

Yoshua Bengio
MILA, Université de Montréal

Aviv Regev

Aviv Regev
MIT, Genentech

Max Welling

Max Welling
University of Amsterdam, Microsoft Research