معرفی
Jacob Laurel is an Assistant Professor in the School of Computer Science at Georgia Institute of Technology. His research focuses on static analysis of programming languages, particularly in probabilistic and differentiable programming. He actively recruits PhD students starting Fall 2025 for work in these areas.
Research interests include static analysis techniques for probabilistic/differentiable languages, compiler optimizations, and formal methods for ensuring correctness in AI systems. His work spans topics like abstract interpretation, automatic differentiation, and uncertainty quantification in distributed systems.
Notable contributions include the Diamont framework for uncertainty monitoring in distributed programs, the Statheros compiler for low-precision probabilistic inference, and foundational work on higher-order automatic differentiation analysis.
He has served on program committees for OOPSLA, SAS, ECCV, and WFVML. Teaching includes a special topics course on probabilistic/differentiable programming in Spring 2025.
