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Professors in Probabilistic Graphical Models
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12 professors available publicly
Michael Jordan
computational statistics
probabilistic graphical models
Bayesian nonparametrics
Michael I. Jordan is the Pehong Chen Distinguished Professor in the
Department of Electrical Engineering and Computer Science and the
Department of Statistics at the University of California, Berkeley.
He received his Masters in Mathematics from Arizona State University,
and ...
Mathias Niepert
Efficient and Controllable Generative AI
Geometric and Physics-Aware Deep Learning
Probabilistic Graphical Models
Mathias Niepert is a professor (W3) at the University of Stuttgart, an ELLIS fellow, and a faculty member at the International Max Planck Research School for Intelligent Systems (IMPRS-IS). He leads the Machine Learning and Simulation Lab (MLS Lab), with affiliations to the AI In...
Mustafa Bilgic
Active Learning
Interactive Machine Learning
Interpretable Machine Learning
Dr. Mustafa Bilgic is a Professor of Computer Science and Chair of the Department of Computer Science at the Illinois Institute of Technology in Chicago. He also serves as Director of the Machine Learning Laboratory and leads the Master’s in Artificial Intelligence program. Dr....
Erik Sudderth
Probabilistic Graphical Models
Probabilistic Programming
Nonparametric Bayesian Methods
Erik B. Sudderth is Professor of Computer Science and Statistics, and Chancellor’s Fellow, at the University of California, Irvine. He directs the UC Irvine Center for Machine Learning and Intelligent Systems, as well as the HPI Research Center in Machine Learning and Data Scie...
Deepak Venugopal
Probabilistic Graphical Models
Markov Logic Networks
Lifted Approximate Inference
Dr. Deepak Venugopal joined the Department as an assistant professor in Fall 2015 after completing his PhD in computer science at the University of Texas at Dallas.
Dr. Venugopal's primary research interest is in developing fast, scalable, and accurate algorithms for inference...
Vibhav Gogate
Probabilistic Graphical Models
Statistical Relational Learning
Probabilistic Programming
Vibhav Gogate, Ph.D. is a Professor in the Department of Computer Science at The University of Texas at Dallas and Co-Director of the Center for Machine Learning. He earned his Ph.D. in Information and Computer Science from the University of California, Irvine in 2009 and complet...
Arthur Choi
Bayesian Networks
Probabilistic Graphical Models
Explainable AI
I joined the Computer Science Department at Kennesaw State University in Fall 2021. I was formerly a researcher in the Computer Science Department at UCLA, and formerly adjunct faculty at Santa Monica College.
My research interests are in areas of artificial intelligence and m...
Jun Ding
Neuro-AI
Computational Biology
Deep Generative Models
Dr. Jun Ding is an Assistant Professor in the Department of Medicine at McGill University, with associate appointments in the School of Computer Science and the Department of Biomedical Engineering. As a core member of the Meakins-Christie Laboratories and an affiliate of Mila (Q...
William Turkett
Probabilistic Reasoning
Bayesian Networks
Uncertainty Quantification
Dr. William Turkett is an Associate Professor in the Department of Computer Science at Wake Forest University. He received his Ph.D. in 2004 from the Department of Computer Science and Engineering at the University of South Carolina, where his research was in the area of probabil...
Rebecca Morrison
dynamical systems
probabilistic graphical models
uncertainty quantification
Assistant Professor, Dept. of Computer Science, University of Colorado Boulder, 2018 – present
Affiliate Faculty Member, Robotics Program
Postdoc, Dept. of Aeronautics and Astronautics, Massachusetts Institute of Technology, 2016 – 2018
Intern, Sandia National Laboratories...
Zhe Zeng
Probabilistic Graphical Models
Statistical Relational Learning
Deep Generative Models
Zhe Zeng is an assistant professor in the Department of Computer Science. Prior to that, she was a Faculty Fellow in the Computer Science Department at New York University, working with Andrew Gordon Wilson. She received her Ph.D. in Computer Science at the University of Californ...
Mohammad Ali Javidian
Classical Causal Inference
Quantum Entropic Causal Inference
Probabilistic Graphical Models
I am an assistant professor in computer science at Appalachian State University (ASU). My research interests include classical/quantum causal inference and probabilistic graphical models for decision making under uncertainty. My research seeks to develop theoretically sound, reli...