معرفی
Shuwen Lou is an Associate Professor in the Department of Mathematics, Statistics, and Computer Science at Loyola University Chicago. His research focuses on probability theory, analysis, and their applications in stochastic processes, machine learning, and data science. He holds a PhD in Mathematics from the University of Washington (2014) and has held postdoctoral positions at the University of Illinois at Chicago (2014–2017) and the University of Toronto (2017–2018).
- Education:
- PhD in Mathematics, University of Washington (2014)
- Positions:
- Research Assistant Professor, University of Illinois at Chicago (2014–2017)
- Postdoctoral Fellow, University of Toronto (2017–2018)
His research interests include Markov processes, Dirichlet forms, rough path theory, and applications of probabilistic models in machine learning, such as analyzing stochastic differential equations in algorithmic contexts. Recent work explores Brownian motion models in varying-dimensional spaces and distorted systems, with contributions to heat kernel analysis and stochastic differential equations driven by fractional Brownian motions.
His publications highlight advancements in stochastic analysis, with a focus on boundary behavior, transition densities, and heat kernel estimates. Lou’s work bridges theoretical probability with applied domains like data science, emphasizing interdisciplinary applications.
Office: Loyola Hall 113 | Phone: 773.508.3596
