一、报告题目

Machine Learning and Statistical Emulation to Realize the Digital Twin of the Human Heart

二、主讲人

Hao Gao

三、报告时间

2023年7月6日 15：00 – 16：00

四、报告地点

青岛校区华岗苑东楼119会议室

五、摘要

The digital twin of a human heart, also known as a subject-specific digital model, built upon in vivo clinical measurements, has the potential to provide effective and consistent risk-stratification of patients. However, personalisation of these models can be challenging, particularly because different patients have different sets of biophysical parameters that can affect the quantities of interest, and it further requires running thousands of simulations of the mathematical model, which can be computationally expensive because these models are based on complex, nonlinear equations that do not have closed-form solutions. In this talk, I will first introduce the statistical emulation of computationally expensive cardiac models using Gaussian process with fixed computational domain and varied domains, then Bayesian inference of patient-specific biophysical parameters from real measurements. I will further talk about our recent work on automatic heart geometry reconstruction directly from medical images using state-of-art convolutional neural networks. Finally, I will discuss Graph Neural networks in emulating partial differential equations in complex domains both data-driven and physics-informed approaches.

六、主讲人简介

Dr Hao Gao obtained Bachelor of Science and Master of Science in theoretical and applied mechanics from Fudan University, and PhD in computational mechanics from Brunel University, UK. Then Post-doctoral researcher first at Strathclyde University, later at the University of Glasgow as a research fellow in the School of Mathematics and Statistics. He is the key researcher and co-investigator of the SofTMech centre, one of five mathematics centre across UK. Currently, he is a lecturer in applied mathematics and (co)-leading several projects funded by EPSRC and BHF.

His main research interest sits in the interface between applied mathematics, statistics and clinical science. He has published more than 90 research papers in Acta Biomaterial, Computer Methods in Applied Mechanics and Engineering, Journal of the Royal Statistical Society: Series C, Artificial Intelligence in Medicine, etc. Google Scholar citation: 2000 and h-index: 26.

七、主办单位

非线性期望前沿科学中心

数学与交叉科学研究中心