School of CSE Seminar Series: Aishik Ghosh

Speaker: Aishik Ghosh, assistant professor at Georgia Tech's School of Physics
Date and Time: November 21, 2:00-3:00 p.m.
Location: Coda 230
Host: Edmond Chow

Title: Accelerating Fundamental Physics Research with AI: From Designing Theories to Testing Them in Experiments

Abstract: In fundamental physics, we build bottom-up theories to explain the universe from elementary particles to the nature of gravity. Theoretical advancements have traditionally relied on human insight into complex mathematics without a systematic way to explore ideas. I will talk about an emerging research direction in neuro-symbolic AI to systematize this exploration and discuss challenges in scaling this approach.

Once you have a set of interesting theories, testing them in experiments, such as at the Large Hadron Collider, is yet another computational and engineering challenge. High-dimensional data are generated at 50 MHz (40 TB/s), and we need to make decisions using efficient hardware. I will also discuss how neural inference techniques let us maximally use the high-dimensional data and current efforts to make these algorithms compute-efficient.

Bio: Aishik Ghosh is an assistant professor in the School of Physics at Georgia Tech with a focus on developing AI methods to accelerate fundamental physics and astrophysics. His group works on theoretical physics, statistical methods, and experiment design. For robust scientific applications, Dr. Ghosh focuses on uncertainty quantification, interpretability, and verifiability of AI algorithms, targeting publications in physics journals and ML conferences.