AI4Science Beijing Meetup 2025

Organizer:THU & PKU
Time:June 28th, 2025

AI4Science Beijing Meetup 2025

 

Learned Partial Differential Equations (PDEs)

28th June 2025, Tsinghua University

 

Registration (Limited Places!): https://www.wjx.cn/vm/YQocgt0.aspx#

 

Overview

 

Partial Differential Equations (PDEs) are fundamental to modelling a wide range of physical, biological, and engineered systems. With recent advances in machine learning, researchers have begun to explore how data-driven methods can learn and approximate PDEs directly from observations, offering new tools for scientific discovery.

 

This meetup will highlight recent developments in the learned PDEs using AI techniques. We will discuss foundational methods such as neural operators and physics-informed neural networks (PINNs), explore applications across disciplines, and examine the open challenges in interpretability, generalization, and scalability. The session aims to provide attendees with both a theoretical understanding and practical insights into this emerging area.

 

After attending this meetup, participants will be able to:
● understand how machine learning can be used to model and solve PDEs
● gain an overview of key methods like PINNs and neural operators
● explore real-world applications in fluid dynamics, materials science, and more
● identify challenges and research opportunities in learned PDEs


 

General Chairs

 

- Angelica Aviles-Rivero (YMSC, Tsinghua University)

- Bin Dong (Peking University)

 

Co-Organising Committee

 

- Chun-Wun Cheng (University of Cambridge)

- Yanqi Cheng (University of Cambridge)

- Haixu Wu (Tsinghua University)

 

Keynote Speakers:

 

— Zhengyu Huang, Peking University

— Paris Perdikaris, University of Pennsylvania

— Hao Sun, Renmin University of China

— Chuang Wang, Chinese Academicy of Science

 

Flash Talks and Beyond!

More information: https://math-ml-x.github.io/AI4ScienceTHU/

 

Poster: AI4Science Beijing Meetup 2025.pdf