CV

Education

Ph.D in Computer Science, University of California, Los Angeles (currently enrolled)
M.S. in Computer Science, University of Southern California, 2017
M.S. in Electrical Engineering, University of Southern California, 2015
B.S. in Electrical Engineering, Harbin Engineering University, 2013

Summer 2020: Research Intern @ Yahoo Research Center
- Researched the cold-start recommendation issue in a dynamic online environment using counterfactual reasoning and contextual multi-armed bandit.
- Implement the Causal Thompson Sampling algorithm.
Summer 2019: Research Intern @ Alibaba Group
- Identified the selection bias and data sparsity issues in conventional conversion rate (CVR) estimation
- Proposed two theoretically unbiased CVR estimators, i.e., Multi-IPW, and Multi-DR, which solves these issues from a causal perspective.
- Evaluated the proposed models on a public dataset and a production dataset (with 10 Billion data samples), and the results reveal that the proposed method outperform the state-of-the-art CVR models.
- Drafted paper ”Large-scale Causal Approaches to Debiasing Post-clickConversion Rate Estimation with Multi-taskLearning”, and submitted it to The Web Conference 2020.

Contributions to Scikit-learn
- Solved the compatibility issue with python 3.7.0b5 in version 0.19.2 (Merged pull request #11256)
- Added a new interface in model selection module (sklearn.model selection) in version 0.21.0. This feature adds more flexibility in identifying the best estimator. (Merged pull requestion #11354)
Contribution to wkdict
- Published a dictionary app that sits in CLI enviroment