Upcoming Seminars

A Data-Driven Framework for Flood Mitigation Using Transformers and Reinforcement Learning

Friday, February 6, 2026 3:30pm to 4:20pm
MacLean Hall

Speaker: Shaoping Xiao, Department of Mechanical Engineering

Colloquium - A Hessian View of Fine-tuning, Task Attribution, and Reinforcement Learning: Three Vignettes in Modern Machine Learning promotional image

Colloquium - A Hessian View of Fine-tuning, Task Attribution, and Reinforcement Learning: Three Vignettes in Modern Machine Learning

Friday, February 13, 2026 3:30pm to 4:30pm
Schaeffer Hall
We welcome Hongyang Zhang, Ph.D., from Northeastern University, whose research lies at the intersection of machine learning, optimization algorithms, and statistical learning.

Past Seminars

Evolution of Stress Response and Adhesin Gene Family in Pathogenic Yeasts

Friday, February 14, 2025 3:30pm to 4:20pm
MacLean Hall

Speaker: Bin He, Biology Dept.

Structural Models for Vascular Tissues

Friday, February 7, 2025 3:30pm to 4:20pm
MacLean Hall

Speaker: Jia Lu, Dept. Mechanical Engineering

Models of Mitochondrial Fission from ODE to PDE to DDE

Friday, January 31, 2025 3:30pm to 4:20pm
MacLean Hall

Speaker: Colleen Mitchell, Dept. of Mathematics

Time integration methods for systems with constraints

Friday, January 24, 2025 3:30pm to 4:20pm
MacLean Hall

Speaker: Laurent O. Jay, Department of Mathematics

Mathematics Faculty Colloquium - Xueyu Zhu; University of Iowa Department of Mathematics promotional image

Mathematics Faculty Colloquium - Xueyu Zhu; University of Iowa Department of Mathematics

Thursday, December 5, 2024 3:30pm to 4:20pm
MacLean Hall

Title: Recent Advancement of Scientific Machine Learning

Abstract: Machine learning has revolutionized scientific computing, offering unprecedented computational efficiency, flexibility, and applicability to real-world challenges. However, traditional machine learning approaches often overlook the rich insights provided by existing physical laws or mathematical properties. This talk explores the latest advancements in AI techniques that respect existing physical laws or mathematical properties...