AI4Science Beijing Meetup 2025
Learned Partial Differential Equations (PDEs)
28th June 2025, Tsinghua University
Sponsors
🔥 Registration Link: 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
Co-Organising Committee
Alphabetic Order
University of Cambridge
University of Cambridge
Tsinghua University
Keynotes
Alphabetic Order
Peking University
University of Pennsylvania
Renmin University of China
Chinese Academy of Sciences
Beihang University
Flash Talks
Alphabetic Order
University of Cambridge
Tsinghua University
Chinese Academy of Sciences
