Feras Saad

About

Dr. Feras Saad is an Assistant Professor at Carnegie Mellon University in the United States. His research focuses on areas such as random variate generation, programmable Markov Chain Monte Carlo (MCMC) methods, and scalable spatiotemporal prediction using Bayesian neural fields. Additionally, he has contributed to the development of probabilistic programming systems for generative models and robust resource analysis through static methods and Bayesian inference.