报告题目： Data-Driven Modeling and Optimization for Decision Making

报 告 人：李宪奇教授

报告摘要：As the amount of available data grows exponentially, the decision-making process for groups, organizations and even individuals are being changed. For instance, companies can decide which types of products to create or increase to best meet customers' needs by gathering data online through their buying habits instead of relying on the lengthy process of customer feedback. In healthcare, doctors are able to make better treatment decisions for patients by collecting enough personal data such as lifestyle, disease history and genetics on each person. However, it is not the amount of data that only matters. The approaches we model the data and the methods we solve the formulated optimization problems are also critical components for decision making. In this talk, I will show how these two components driven by big data aids us to make decisions. First, I will present causality network learning with temporally dependent data by introducing our proposed rigorous and computationally efficient statistical machine learning methods. I will talk briefly about the established asymptotic upper bound on the estimation error rates of the introduced models and the convergence rate of the designed optimization algorithms, which will reveal us how the data/sample size influences the performance of the modeling and algorithm. Then, I will discuss the partially parallel MR image reconstruction problem from an optimization perspective and its significance in healthcare. Lastly, I will present our recently developed deep learning models and show how the doctors benefit from them by combining with the large amount of healthcare data.

报告人简介：Xianqi Li is currently an assistant professor in the Department of Mathematics and System Engineering at Florida Institute of Technology. Prior to this, he was a postdoctoral research fellow in the Department of Radiology, Harvard Medical School. He received his PhD from the Department of Mathematics under supervision of Dr. Yunmei Chen and Dr. George Michailidis in May 2018 and an MS from the Department of Electrical and Computer Engineering in May 2015 respectively at University of Florida. Earlier, he got an MS in Mathematics under supervision of Dr. Zhijun Qiao from the University of Texas Rio Grande Valley in August 2009 . He got his bachelor's degree from College of Mathematics and Statistics at Liaoning University in July 2007. His principal research interests now lie in the areas of optimization, machine/deep learning, and data analytics.

报告时间：2023年4月18日10：40-12：00

报告地点：腾讯会议：960 706 085

联 系 人：徐晓宁

                                                                                                    欢迎老师和同学参加！