Research
My research focuses on probabilistic models for learning problems arising from real applications. My research interests include probabilistic graphical models, Bayesian deep learning, spatial data modeling, text modeling, and recommendation. See my publication list.
Ongoing research projects
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Embedding models: generalization of embedding models to items [Liu & Blei, 2017] [bird embedding].
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Spatial modeling: model spatial data with Gaussian processes
Previous research projects
Gaussian approximation of CGM, Superset (partial) label learning, Active learning for clustering, Labeling extremely imbalanced data
Blog
I’m writing a research blog here. Recent posts:
Teaching
- Fall 2017: COMP 150-01 Machine Learning for Ecology and Sustainability
- Spring 2018: COMP 135 Introduction to Machine Learning
Bio Sketch
I received my B.S. in computer science from Hebei University of Technology in 2006. After three years study in LAMDA group, I received my M.S. degree from Nanjing Univeristy in 2009. My advisor was Prof. Yuan Jiang and Zhi-Hua Zhou. Then I worked in Alibaba for one year and a half. After that, I went to Oregon State University and completed my PhD degree in 2016. My PhD advisor was Prof. Thomas Dietterich. Prior to joining Tufts, I worked as a postdoc researcher at Columbia University working with Prof. David Blei.