Yixiang Deng: Integrating Multiscale Modeling and Machine Learning in Computational Medicine
Abstract
Computational models have revolutionized our understanding of complex biological systems. These models typically fall into two categories: multiscale models and machine learning models. Multiscale models, grounded in the fundamental principles of physics and chemistry, can dissect the intricate causalities in disease progression. In parallel, machine learning models, based on rich datasets, have yielded unique insights into complex pattern recognition within these systems.
In this talk, I will demonstrate how multiscale models are developed to probe disease-mediated changes in blood dynamics. I will also show how various machine learning models, with a focus on deep learning, are designed to enhance accurate prediction, optimize treatment plans, and distill extensive knowledge of different diseases.
To conclude, I will discuss the pivotal factors—such as age and sex—that are critical to customizing treatments in the realm of precision medicine. I will share how to synergistically integrate multiscale modeling with machine learning to enable the design of more comprehensive personalized medicine.
Biography: Yixiang Deng is currently an Assistant Professor in the Department of Computer and Information Sciences at the University of Delaware. Before that, she was a Postdoctoral Fellow at the Ragon Institute of Mass General, MIT, and Harvard with a joint appointment at the MIT Department of Biological Engineering, advised by Prof. Douglas A. Lauffenburger. Her research focuses on integrating multiscale modeling and machine learning to probe the mechanisms of diseases and the effectiveness of therapeutics. Before joining the Ragon Institute, she completed her Ph.D. in the School of Engineering advised by Prof. George Em Karniadakis at Brown University in 2021. She received a B.Eng. degree in Engineering Mechanics at Shanghai Jiao Tong University in 2015.
She is the recipient of multiple honors and awards, including the Brown University Open Graduate Education Fellowship in 2018, MIT Rising Star in Mechanical Engineering in 2021, the Mark and Lisa Schwartz AI/ML/Immunology Initiative Fellowship in 2022, and the Duke Engineering Future Faculty of Innovation and Excellence (DEFINE) program in 2023.