Barnabás Póczos

Barnabás Póczos is an Associate Professor in the Machine Learning Department at Carnegie Mellon University's School of Computer Science. He develops machine learning methods for automated discovery and efficient data processing across applied sciences including health-sciences, neuroscience, bioinformatics, cosmology, agriculture, robotics, civil engineering, and material sciences.

• Ph.D. in Computer Science (2007) and M.Sc. in Applied Mathematics (2001) from Eötvös Loránd University, Hungary
• Postdoctoral Fellow at University of Alberta (2007-2010) and Carnegie Mellon (2010-2012)

His research focuses on theoretical statistics and machine learning applications, with methods published in top journals/conferences. He has co-authored 100+ peer-reviewed papers and secured 15+ federal/non-federal grants. Current affiliations include Carnegie Mellon University and the Auton Lab.

Recent teaching roles include courses on Convex Optimization, Scalability in Machine Learning, and Advanced Introduction to Machine Learning at Carnegie Mellon, with additional teaching experience at University of Alberta and Eötvös Loránd University.

• Recipient of Yahoo! ACE award
• Research interests span theoretical statistics, applied machine learning, and interdisciplinary scientific discovery

Contact: Gates-Hillman Center, #8231, 5000 Forbes Ave., Pittsburgh, PA 15213