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Professors in Uncertainty Quantification
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11 professors available publicly
Paris Perdikaris
Physics-Informed Machine Learning (PIML)
Physics-Informed Neural Networks (PINNs)
Neural Operators
Paris Perdikaris is an Associate Professor of Mechanical Engineering and Applied Mechanics at the University of Pennsylvania, where he also directs the Predictive Intelligence Lab. His research is at the global forefront of AI for Science, specifically in the development of Physi...
Edmond Chow
Numerical Linear Algebra
Partial Differential Equation (PDE) Models
Quantum Chemistry Simulations
Edmond Chow is a Professor in the School of Computational Science in the College of Computing. He previously held positions at D. E. Shaw Research and Lawrence Livermore National Laboratory. His research interests are in numerical methods, particularly numerical linear algebra, f...
Stephan Mandt
Deep Generative Models
Variational Autoencoders (VAEs)
Diffusion Models
Stephan Mandt is an Associate Professor of Computer Science and Statistics at the University of California, Irvine. Previously, he led the machine learning group at Disney Research in Pittsburgh and Los Angeles and held postdoctoral positions at Princeton and Columbia University....
Georg Stadler
Inverse Problems
PDE-Constrained Optimization
Uncertainty Quantification
Georg Stadler is a Professor of Mathematics and Computer Science at New York University’s Courant Institute of Mathematical Sciences, having joined the faculty in 2014. His research is at the leading edge of applied mathematics and scientific computing, with a specialized focus...
Yan Yan
Uncertainty Quantification
Risk-Aware Robust Learning
Stochastic Optimization
I am an Assistant Professor at the School of Electrical Engineering and Computer Science, Washington State University, where I lead the ROMA Lab. My research interests include uncertainty quantification, risk-aware robust learning and stochastic optimization for machine learning ...
Peng Chen
Computational Mathematics
Finite Element Analysis
Computational Engineering and Sciences
Peng Chen is a tenure-track assistant professor in the School of Computational Science and Engineering at Georgia Tech. Previously, he was a Research Scientist working with Prof. Omar Ghattas at the Oden Institute for Computational Engineering and Sciences at University of Texas ...
Gabriel Terejanu
Causal AI
Invariant Machine Learning
Bayesian Inference
Gabriel Terejanu is a Professor of Computer Science at the University of North Carolina at Charlotte. He has previously held academic positions at the University of South Carolina and was a fellow at the University of Texas at Austin. His industry experience includes roles as a s...
Dr. Alexander Rodríguez
Scientific Machine Learning
Trustworthy AI for Spatiotemporal Dynamics
Epidemic Forecasting
Alexander Rodríguez is an Assistant Professor of Computer Science and Engineering at the University of Michigan. He earned his Ph.D. in Computer Science from the Georgia Institute of Technology and leads research at the intersection of machine learning, time series analysis, sci...
Elizabeth Qian
efficient surrogate modeling
model reduction
scientific machine learning
Elizabeth Qian holds a joint appointment at Georgia Tech as Assistant Professor in the Schools of Aerospace Engineering and Computational Science and Engineering. Her interdisciplinary research develops new computational methods to enable engineering design and decision-making fo...
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...