Since AlphaFold2 was open sourced and predicted 98.5% of human protein structures in one go, AI for Science has become a hot research trend.

2024/06/2904:21:32 science 1102

Since AlphaFold2 was open sourced and predicted 98.5% of human protein structures in one go, AI for Science has become a hot research trend.

On the one hand, data-driven is hailed as the next paradigm in scientific research. On the other hand, scientific research applications are also seen as a new battlefield for AI implementation.

will hold the third Workshop with the theme of AI for Science at the latest NeurIPS 2022.

This workshop will review the major achievements of AI for Science in various fields and discuss the next development direction of AI for Science.

Invited guests include many industry leaders.

has the same name as AlphaFold, the author of RoseTTAFold, David Baker of the University of Washington.

and E Weinan, an academician of the Chinese Academy of Sciences who just gave a one-hour speech at the International Mathematicians Conference .

Workshop topic

In this workshop, the topics of focus are:

Solving major challenges in structural biology
Expanding molecular simulation modeling to the million particle level
Visualization of black holes
Integrating physical priors into Artificial Intelligence The model
Accelerating Drug Discovery

Workshop will be held on December 3, and you can participate online/offline.

can still submit papers until September 18th.

Friends who are interested in AI for Science can click on the address below to submit a paper~

https://ai4sciencecommunity.github.io

In addition, attendance at the seminar is not conditional on submitting a paper. People with different backgrounds and experience levels are welcome to participate. .

has a luxurious organizational lineup.

The organizers of this Workshop have a luxurious lineup, including one of the Big Three, Yoshua Bengio and other big shots.

and Du Yuanqi from Shenzhen Technology will soon enter Cornell University to study for a PhD. Their research interests are deep generative models and AI for Science.

Georgia Tech PhD student Tianfan Fu, whose research direction is drug discovery

Cambridge University PhD student Hanchen Wang, now mainly researches AI+ functional genomics and synthetic biology

Stanford PhD student Ding Yi, she studies Biomedical Informatics

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