BIMSA >
Seminar on Control Theory and Nonlinear Filtering
Correct the misspecified physics model by using the physics informed neural network
Correct the misspecified physics model by using the physics informed neural network
Organizer
Speaker
Time
Wednesday, October 9, 2024 8:30 PM - 9:00 PM
Venue
Online
Abstract
In many applied and engineering scenarios, prior of model is not fully understood. In this talk, we shall discuss how to correct physics model by applying noisy data. PINN, as a popular deep learning technique, has great advantages to handle hybrid problem. Here the key point is to choose suitable ansatz of solution and unknown physics term.
Speaker Intro
Jiao Xiaopei graduated with a bachelor's degree from the Zhi Yuan College of Shanghai Jiao Tong University (Physics Department) in 2017 and obtained his PhD from the Department of Mathematical Sciences at Tsinghua University in 2022, under the guidance of Professor Stephen Shing-Toung Yau (IEEE Fellow, former tenured professor at the University of Illinois at Chicago). He has conducted postdoctoral research at the Beijing Institute of Mathematica Science and Application and at the University of Twente in the Netherlands (under the guidance of Professor Johannes Schmidt-Hieber, Fellow of the Institute of Mathematical Statistics). His current research interests include control theory, numerical partial differential equations, and bioinformatics.