معرفی
Leo Duan is an Associate Professor with Tenure in the Department of Statistics at the University of Florida since 2018. His research focuses on developing statistical methods, computational tools, and Bayesian frameworks to address challenges in neuroscience, engineering, and transportation science. He specializes in combinatorial structures like tree graphs, clustering, and signal pathways, integrating optimization and probabilistic techniques.
Dr. Duan’s recent work includes advancements in Bayesian inference using optimization, such as bridged posteriors and gradient-based methods. He co-teaches a short course on optimization in Bayesian inference at JSM 2025. His funded projects include NSF-ATD grants for geospatial modeling and hurricane risk mitigation, alongside other institutional awards.
His advising spans doctoral students in optimization and diffusion models. Past trainees include Edric Tam (Stanford Postdoc) and Maoran Xu (Indiana University faculty). Current students Zeyu Yuwen and Yu Zheng are nearing graduation. Dr. Duan’s lab actively recruits new graduate researchers.
Key achievements include the 2018 NeurIPS Bayesian Non-parametrics Award and a series of high-impact publications in JASA, JMLR, and Biometrika. His research bridges theory and application, with contributions to spanning trees, graphical models, and Bayesian vector autoregression.
