March 2014 I'm thrilled to receive an NSF CAREER Award for my work on large-scale Bayesian nonparametric learning.
September 2013 I'm teaching a fall Introduction to Machine Learning.
January 2013 I'm teaching a spring graduate course on Probabilistic Graphical Models.
September 2012 Thanks to everyone who attended our ICERM Workshop and Tutorials on Bayesian Nonparametrics.
I am an Assistant Professor of Computer Science at Brown University. My research interests span topics traditionally studied in statistics, machine learning, computer vision, and signal processing. Much of my recent work has explored vision systems which segment, recognize, and track objects in complex natural scenes. I believe data-driven, nonparametric Bayesian statistical methods (see my CVPR tutorial) provide a very promising framework to address such problems. My more abstract statistical research is inspired by the practical challenges of learning from large, richly structured datasets.
In June of 2006, I completed my Ph.D. in the EECS department at MIT, where I was advised by Professors Alan Willsky and William Freeman. The background chapter of my thesis provides a tutorial introduction to statistical machine learning, including probabilistic graphical models; Monte Carlo and variational inference algorithms such as belief propagation; and nonparametric Bayesian methods based on the Dirichlet process.
I am currently co-editing an IEEE PAMI Special Issue on Bayesian Nonparametrics. In the past, I have co-edited an IEEE Signal Processing Magazine special issue on Recent Advances & Emerging Developments of Graphical Models, and an IEEE PAMI Special Section on Probabilistic Graphical Models in Computer Vision. I was happy to co-organize a 2012 ICERM Workshop and Tutorials on Bayesian Nonparametrics.
Brown provides an exciting, interdisciplinary environment for research in statistical machine learning and computer vision:
- Brown Center for Vision Research and Institute for Brain Science
- Brown Institute for Computational and Experimental Research in Mathematics (ICERM)
- Brown Machine Learning Reading Group
- Brown Computer Vision Reading Group
- Brown Pattern Theory Group and seminar series
- Applied machine learning: Robotics, Natural Language Processing, Graphics
Tel: (401) 863-7660
Fax: (401) 863-7657