Ben Marlin

Ben Marlin's research interests lie at the intersection of artificial intelligence, machine learning, and statistics. He is particularly interested in hierarchical graphical models and approximate inference/learning techniques, including Markov Chain Monte Carlo and variational Bayesian methods. His current research has a particular emphasis on models and algorithms for multivariate time series data. His current applied work is focusing on machine learning-based analytics for clinical and mobile health (mHealth) data. In the past, he has worked on a broad range of applications including collaborative filtering and ranking, unsupervised structure discovery and feature induction, object recognition and image labeling, and natural language processing, and he continues to consult on projects in these areas.

Marlin is a 2014 National Science Foundation CAREER award recipient and a 2013 Yahoo! Faculty Research Engagement Program award recipient. He has received awards for his work on collaborative filtering and recommender systems, including the Best Technical Paper award at the ACM Conference on Recommender Systems in 2009 and an invitation to the Best Papers track at the International Joint Conference on Artificial Intelligence in 2011. Marlin was the general co-chair for the 2014 Meaningful Use of Complex Medical Data Symposium, and has served on the senior program committees of top machine learning conferences including NIPS, ICML, and UAI. He held fellowships from the Killam Trusts and the Pacific Institute for the Mathematical Sciences while pursuing postdoctoral research at the University of British Columbia. He held a Canadian Graduate Scholarship from the Natural Sciences and Engineering Research Council of Canada, the top Canadian doctoral scholarship in the Sciences, while at the University of Toronto.