CAST Seminar: Xinwei Deng

Join us at the CANSSI Ontario STatistics Seminars (CAST) with

Dr. Xinwei Deng

Professor, Data Science Faculty Fellow
Department of Statistics, Virginia Tech

Free Hybrid (On Line/In Person) Event | Registration Required

Talk Title

New Songs for Old Stories: Interface between Experimental Design and Machine Learning

Abstract

Experimental design and machine learning techniques have been widely used in engineering and data science applications. However, these two major areas have not been well integrated, especially on using experimental design thinking to enhance machine learning and using machine learning ideas to improve data collection. In this talk, we will present several recent research on the interface between experimental design and machine learning to facilitate data collection, modeling, and decision making in the era of data science and AI. Specifically, two research works will be presented. The first part will introduce an active learning approach, called QS-learning, to enable effective modeling and efficient optimization for a new type of data with quantitative-sequence (QS) factors. The QS factor involves a sequence of multiple components associated with their quantities, widely used in health care, logistics, and many other disciplines. The second part will present a variational mutual information (MI) estimator for data and model parameters, leading to a simple and powerful contrastive MI estimator for Bayesian optimal experimental design. The performance of the proposed methods is evaluated by both numerical examples and real applications.

Speaker Profile

Xinwei Deng is Professor of Statistics and Data Science Faculty Fellow at Virginia Tech. He is also a co-director of VT Statistics and Artificial Intelligence Laboratory (VT-SAIL). Dr. Deng received his PhD degree in industrial engineering from Georgia Tech in 2009. His research interests focus on statistical modeling of complex data, design and analysis of experiments, uncertainty quantification and digital twin, and the interface between experimental design and machine learning. Dr. Deng research development has produced over 120 publications in top statistics journals and machine learning conferences. He has been has been associate editors for seversl top-tier statistical journals.