Wes Bethel

Wes Bethel is an Associate Professor in the Department of Computer Science at San Francisco State University. His research focuses on quantum computing, machine learning applications in scientific modeling, and high-performance computing frameworks such as the SENSEI in situ visualization system. He leads efforts in optimizing quantum algorithms, real-time fusion energy modeling, and scalable data processing for large-scale simulations.

Key research themes include quantum protocols for polynomial computation, GPU-based quantum circuit simulation, and machine learning-driven approaches to plasma physics and radio frequency (RF) heating analysis. His work bridges theoretical advancements with practical implementations in energy science and computational infrastructure.

Recent projects emphasize accelerating RF modeling using AI surrogates, improving in situ visualization frameworks for heterogeneous architectures, and addressing challenges in classical-quantum system integration. Contributions span both methodological innovations and applied solutions for fusion energy research and distributed computing environments.

No scientific awards are listed in the provided materials. Advising and grants information is not explicitly detailed here, though his publications indicate collaborative involvement in DOE-funded projects and fusion energy initiatives. He contributes to open-source tools like SENSEI and WarpVisIt, supporting community-driven advancements in scientific computing.

Research labs and teams associated with his work likely include computational science groups focused on quantum computing, plasma physics modeling, and high-performance data management at San Francisco State University and collaborating institutions.