Research
My research focuses on probabilistic models and neural networks for learning problems arising from real applications. My research topics include variational inference, representation learning, and attention networks. See my publication list.
Research highlights
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Amortized variational inference for Gaussian processes
Idea: consider strong correlations only and run inference within neighborhoods with a shared structure
Benefits: accurate & fast
Publications: [Liu & Liu, 2019]
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Spatial modeling: modeling spatial data with neural networks
Publications: Kernel Convolutional Networks, accepted by AAAI 2020, coming soon.
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Embedding models: representing objects as vectors
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embedding molecules as vectors with embedding propagation
Publications: Predicting Reactions for Biochemical Networks Using Graph Embeddings, accepted by MLCB.
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generalization of embedding models to items
Idea: down-weight unuseful item relations and improve the embedding quality
Publications: [Liu & Blei, 2017], [Liu et al., 2017], [visualization]
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HIRING PhD Students: Our research group is hiring PhD students for 2020 fall. Applicants with strong motivations are preferred. Programming skills and math skills (calculus, linear algebra, and probabilities) will be appreciated.
HIRING Undergrads at Tufts: We are looking for an undergrad who is passionate about machine learning. This is a project related to image classification, so the candidate needs to have basic knowledge about neural networks. This is a PAID position.
Teaching
- Fall 2020: COMP 137 Deep Neural Networks
- Fall 2019: COMP 150 Machine Learning for Graph Analytics
- Spring 2019: COMP 150 Deep Neural Networks
- Fall 2018: COMP 135 Introduction to Machine Learning
- Spring 2018: COMP 135 Introduction to Machine Learning
- Fall 2017: COMP 150-01 Machine Learning for Ecology and Sustainability
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.