Andreas Stathopoulos

Overview

Andreas Stathopoulos is a Professor in the Department of Computer Science at William & Mary. He specializes in numerical linear algebra, high-performance computing, and scientific computing. His research focuses on eigenvalue methods, iterative solvers, parallel algorithms, and applications in quantum chromodynamics (QCD) and materials science. He developed the PRIMME software package for large-scale eigenvalue problems.

Education and Background

While his formal education details are not explicitly listed, his academic trajectory aligns with typical roles in computational science, including advanced degrees in computer science or applied mathematics.

Research Interests

• Numerical Linear Algebra: Eigenvalue methods, iterative solvers, preconditioning, and multigrid techniques.
• Scientific Computing: Applications in QCD, materials science, and kernel-based machine learning.
• Parallel Computing: Resource management, load balancing, and hybrid computing architectures.

Teaching

He teaches courses such as CSCI 243 (Discrete Structures), CSCI 653 (Analysis of Algorithms), and CS 780 (Big Data). He also contributed to interdisciplinary courses like UMSA (Undergraduate Modeling, Simulation, and Analysis).

Students and Postdocs

He has advised numerous PhD and MS students, including Yu Chen (2023), Lingfei Wu (2016), and Jesse Laeuchli (2016), as well as postdoctoral researchers like Konstantinos Liakos (2023–present) and Eloy Romero (2016–2020).

Affiliations

He collaborates with institutions such as DOE's Jefferson Lab and has contributed to software projects like PRIMME, which addresses large-scale eigenvalue problems in scientific computing.