معرفی
Justin Domke is an Associate Professor in the Department of Computer Science at the University of Massachusetts Amherst, affiliated with the College of Computing and Information Sciences. He focuses on machine learning, probabilistic models, optimization, and statistical inference. His research addresses computational challenges in probabilistic reasoning and integrates approximate methods with complex models.
He holds a PhD and MS in Computer Science from the University of Maryland, College Park, and dual BS degrees in Physics and Computer Science from Washington University in St. Louis. Domke has been recognized as an outstanding reviewer at CVPR 2011 and NIPS 2013. He is currently on leave for the 2023 Spring semester.
His recent work spans variational inference advancements, including importance-weighted methods, Langevin diffusion approaches, and optimization techniques for hierarchical models. Domke has developed open-source tools like Pangolin and the Graphical Models Toolbox, and teaches courses on machine learning and graphical models at UMass.
