Jan Hoffmann

Jan Hoffmann is an Associate Professor in the Computer Science Department at Carnegie Mellon University. His research develops quantitative program analysis techniques to ensure software reliability, efficiency, and security. Key focus areas include resource-aware programming languages, probabilistic program verification, and scalable static analysis methods for modern computing environments.

Dr. Hoffmann leads the Carnegie Mellon Resource Analysis Group, advising PhD students on projects spanning energy-aware computing, secure compilation, and probabilistic inference. His work bridges formal methods with practical system design, emphasizing compositional verification and automated reasoning.

Recent publications advance CUDA kernel optimization, programmable Markov chain Monte Carlo methods, and robust resource bound synthesis. This research establishes foundations for predictable performance in concurrent systems and AI-driven applications.