Colloquia & Seminars

Spring 2024

Title: "Interplay of Linear Algebra, Machine Learning, and High Performance Computing"

Dr. Xiaoye Sherry Li
Lawrence Berkeley National Laboratory

When: Friday, April 5th, 2024 from 3pm to 4pm

Where: Pickard Hall, Room 110

Abstract: In recent years, we have seen a large body of research using hierarchical matrix algebra to construct low complexity linear solvers and preconditioners. Not only can these fast solvers significantly accelerate the speed of large scale PDE based simulations, but also they can speed up many AI and machine learning algorithms which are often matrix-computation-bound. On the other hand, statistical and machine learning methods can be used to help select best solvers or solvers' configurations for specific problems and computer platforms. In both of these fields, high performance computing becomes an indispensable cross-cutting tool for achieving real-time solutions for big data problems. In this talk, we will show our recent developments in the intersection of these areas.

Short Bio: Dr. Xiaoye S. Li is a Senior Scientist in the Computational Research Division, Lawrence Berkeley National Laboratory. Dr. Li earned her Ph.D. in Computer Science from UC Berkeley in 1996, MS in Math & Computer Science from Penn State Univ. and B.S. in Computer Science from Tsinghua Univ. She has worked on diverse problems in high performance scientific computations, including parallel computing and sparse matrix computations. She has authored over 130 publications, and is the lead developer of SuperLU, a widely-used sparse direct solver, and has contributed to the development of several other mathematical libraries, including LAPACK and XBLAS. She has served on the editorial boards of the ACM Trans. Math. Software, IJHPCA, and SIAM J. Scientific Comput., as well as many program committees of the scientific conferences. She is a Fellow of SIAM and a Senior Member of ACM.

Title: "How do Immune Cells Kill Tumor Cells?”"

Ami E. Radunskaya, PhD
Lingurn H. Burkhead Professor of Mathematics at Pomona College, CA

When: Friday, February16th, 2024 from 10am to 11am

Where: Pickard Hall, Room 311

Abstract: The immune system is able to fight cancer by mustering and training an army of effector “killer” cells. Mathematical models of tumor-immune interactions must describe the proliferation, recruiting and killing rates of immune cells. Earlier work surprisingly showed that the functions describing the kill rates distinguish between two types of immune cells. The mechanisms behind these differences have been a mystery, however. In an attempt to unravel this mystery, we have created a cell-based fixed-lattice model that simulates immune cell and tumor cell interaction involving MHC recognition, and two killing mechanisms. These mechanisms play a big role in the effectiveness of many cancer immunotherapies. Results from model simulations, along with theories developed by ecologists, can help to illuminate which mechanisms are at work in different conditions.

Title: "What is Liutex: Examples of Hurricane and Tornado Vortex Visualization using Liutex"

Mr. Oscar Alvarez
University of Texas at Arlington

When: Friday, February 2nd, 2024, from 2pm to 3pm

Where: Pickard Hall, Room 311

Abstract: A vortex is a common phenomenon that occurs in fluid flow, especially when studying turbulence. It is to say, understanding vortices is essential knowledge for scientists, researchers, and engineers doing work in the field of fluid mechanics. In the past, scientists such as Helmholtz (1858) had a desire to understand the physical nature of vortices and popularized the idea of using vorticity to define a vortex in a fluid field. Vorticity became the default for studying vortices and vortex identification methods were created that were built on the idea of vorticity. This went on for a long time until only recently, Dr. Chaoqun Liu discovered the Liutex method in 2018. The Liutex method started a new generation of vortex identification methods. Liutex is based directly on the rotation of a fluid as opposed to vorticity which also contains shear. It has been shown that vorticity cannot distinguish between shear and rotation. An immediate counterexample for the invalidity of vorticity to define a vortex can be found near the boundary wall of a boundary layer where vorticity is large but there is no rotation or no vortex. Liutex has now become a well-known vortex identification method. Researchers around the world agree that Liutex mathematically defines what a vortex is. In this presentation I hope to explain what Liutex is. I will also show some examples of Liutex being applied using real/experimental hurricane data provided by the National Oceanic and Atmospheric Administration (NOAA) and simulated high-resolution tornado data with 250 billion grid points provided by a senior research scientist in University of Wisconsin.

Short Bio: Mr. Oscar Alvarez is a Research Scientist 1 at the University of Texas at Arlington Research Institute (UTARI) in Fort Worth, Texas. He also works under the supervision of Dr. Chaoqun Liu as a mathematics PhD student studying Liutex.