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My research area is machine learning and statistics, with interests spreading over the pipeline of data collection (e.g., by crowdsourcing), learning, inference, decision making, and various applications using probabilistic modeling.
Examples of topics of interest: probabilistic graphical models; variational and Monte Carlo inference; deep learning; deep reinforcement learning; distributed learning; big data problems; kernel and nonparametric methods; applications: crowdsourcing, vision, bioinformatics, etc.
I am an action editor of Journal of Machine Learning Research (JMLR).