Professor Stefano Ermon

Stefano Ermon, Ph.D. is Assistant Professor in the Department of Computer Science at Stanford University, where he is affiliated with the Artificial Intelligence Laboratory and a fellow of the Woods Institute for the Environment.
 
Stefano’s research is centered on techniques for scalable and accurate inference in graphical models, statistical modeling of data, large-scale combinatorial optimization, and robust decision making under uncertainty, and is motivated by a range of applications, in particular ones in the emerging field of computational sustainability.
 
His papers include Sparse Gaussian Processes for Bayesian Optimization, Model-Free Imitation Learning with Policy Optimization, Variable Elimination in the Fourier Domain, Learning and Inference via Maximum Inner Product Search, Beyond Parity Constraints: Fourier Analysis of Hash Functions for Inference, Tight Variational Bounds via Random Projections and I-Projections, Transfer Learning from Deep Features for Remote Sensing and Poverty Mapping, and Closing the Gap Between Short and Long XORs for Model Counting.
 
Stefano earned his Bachelor’s degree in Electrical and Electronics Engineering at Università degli Studi di Padova in 2006. He earned his Master of Science in Electrical and Electronics Engineering at Università degli Studi di Padova in 2008 and his Master of Science in Computer Science at Cornell University in 2013. He earned his Ph.D. in Computer Science at Cornell University in 2015.
 
Watch Stefano Ermon | Computational Approaches to Sustainable Energy. Read his LinkedIn profile.