Organized a tutorial on combinatorial optimization in graphical models at IJCAI 2016; Co-program chair (with Dominik Janzing) of the 2016 UAI conference; The solver ('ai') won first place in five categories of UAI's 2014 Approximate Inference Challenge; Co-organized the NIPS'13 workshop 'Crowdsourcing: Theory, Algorithms and Applications'; Received an NSF CAREER award, 'Estimation and Decisions in Graphical Models'.
Research Experience
Professor in the Department of Information & Computer Science at UC Irvine; Research themes include organizing and structuring probability distributions over large systems using graphical models, and balancing theoretical and algorithmic advances with applications to real-world systems.
Background
Research interests: Artificial intelligence and machine learning, focusing on statistical methods for learning from data and approximate inference techniques for graphical models. Applications include data mining and information fusion in sensor networks, computer vision and image processing, and computational biology.