Events
Upcoming Events
A Data-Driven Framework for Flood Mitigation Using Transformers and Reinforcement Learning
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
The University of Iowa Computing Conference (UICC) 2026
The University of Iowa Computing Conference (UICC) 2026
Past Events
Time integration methods for systems with constraints
Speaker: Laurent O. Jay, Department of Mathematics
Mathematics Faculty Colloquium - Xueyu Zhu; University of Iowa Department of Mathematics
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...
A Machine Learning Approach to Analysis of Daily Vocal Function and Vocal Behavior of Individuals with Phonotraumatic Vocal Hyperfunction
In-person (WJSHC 210) and via Zoom (https://uiowa.zoom.us/j/92047907158?pwd=35J1P4oAYnVfabrLo7xdtBFhrX22GC.1 )
Title:
A Machine Learning Approach to Analysis of Daily Vocal Function and Vocal Behavior of Individuals with Phonotraumatic Vocal Hyperfunction
Abstract:
Voice disorders affect approximately 8% of U.S. adults at a given point in time, with a lifetime prevalence of approximately 30% for adults. Many voice disorders are considered behavioral in nature and are associated with vocal...
Multigrid Methods in Space and Time for Extreme-scale Scientific Computing
Speaker: Dr. Rob Falgout, Center for Applied Scientific Computing (CASC) at Lawrence Livermore National Laboratory (LLNL)
Abstract: Multigrid methods play a key role in large-scale scientific simulation because they are among the fastest and most scalable approaches for solving systems of equations. They are widely used to solve the sparse spatial systems that arise in these simulations, and they have been shown to scale efficiently on today’s supercomputers. For time-dependent simulations...
Computational Math and Science Research at LLNL
Speaker: Dr. Rob Falgout, Center for Applied Scientific Computing (CASC) at Lawrence Livermore National Laboratory (LLNL)
Math Colloquium - Speaker: Dr. Rob Falgout, Lawrence Livermore National Lab
Title: Parallel-in-Time Solution of Systems of Linear and Nonlinear Hyperbolic PDEs
Abstract: The multigrid reduction in time (MGRIT) method is a parallel multigrid-in-time solver designed to be as non-intrusive as possible and take advantage of existing simulation codes and techniques. This has worked well for parabolic equations, but parallel-in-time methods for advection-dominated hyperbolic problems have proven difficult to develop. In previous work, we demonstrated the effectiveness of a...
Parallel-in-Time Solution of Systems of Linear and Nonlinear Hyperbolic PDEs
Speaker: Dr. Rob Falgout, Center for Applied Scientific Computing (CASC) at Lawrence Livermore National Laboratory (LLNL)
Abstract: The multigrid reduction in time (MGRIT) method is a parallel multigrid-in-time solver designed to be as non-intrusive as possible and take advantage of existing simulation codes and techniques. This has worked well for parabolic equations, but parallel-in-time methods for advection-dominated hyperbolic problems have proven difficult to develop. In previous work, we...
The application of implicit Runge-Kutta methods to various types of differential equations
Speaker: Laurent O. Jay, Dept. of Mathematics
Optimization and related problems
Speaker: David Stewart, Department of Mathematics
Advice for a Career in Academia
Speaker: Joe Eichholz, United States Air Force Academy