Barnabas Poczos

Barnabas Poczos is an Associate Professor in the Machine Learning Department at the School of Computer Science, Carnegie Mellon University. He is a member of the Auton Lab and has established himself as a leading researcher in theoretical machine learning with applications spanning numerous scientific domains.

• Carnegie Mellon University, School of Computer Science
• Machine Learning Department
• Auton Lab member

Dr. Poczos earned his M.Sc. in applied mathematics from Eotvos Lorand University in Budapest, Hungary in 2001, followed by a Ph.D. in computer science from the same institution in 2007. He completed postdoctoral training at the University of Alberta (2007-2010) in the RLAI group and at Carnegie Mellon University (2010-2012) in the Auton Lab.

His research focuses on theoretical questions of statistics and their applications to machine learning. Dr. Poczos develops machine learning methods for advancing automated discovery and efficient data processing across diverse scientific fields including health-sciences, neuroscience, bioinformatics, cosmology, agriculture, robotics, civil engineering, and material sciences. His work bridges theoretical foundations with practical applications, making significant contributions to both machine learning methodology and domain-specific scientific problems.

Analysis of his recent publications reveals a strong emphasis on diffusion models and generative AI techniques applied to scientific discovery. His work spans drug design, genomics, cosmology, and materials science, demonstrating a consistent pattern of developing novel machine learning methodologies that address specific challenges in scientific domains. The interdisciplinary nature of his research is particularly evident in the application of advanced ML techniques to solve complex problems in biology, physics, and engineering.

• Yahoo! ACE award

Dr. Poczos has served as PI or co-Investigator on 15+ federal and non-federal grants, supporting his research in theoretical machine learning and its scientific applications. His teaching portfolio at CMU includes advanced courses in optimization, convex optimization, and machine learning with large datasets. While specific students aren't mentioned in the provided information, as an Associate Professor at CMU, he undoubtedly mentors graduate students in the Machine Learning Department.

As a core member of the Auton Lab at Carnegie Mellon University, Dr. Poczos contributes to a research environment focused on developing machine learning methods for real-world applications, particularly in healthcare and scientific discovery. The lab's work emphasizes both theoretical foundations and practical implementations of machine learning systems.