Software Engineer Intern in Machine Learning, Facebook,2020.5-2020.8
Ads Core Machine Learning, Mentored by Swati Rallapalli
Employed Domain Adversarial Neural Network (DANN) to mitigate label loss problem in conversion prediction task.
Implemented the proposed workflow in a large ML system and brought ads value gain in A/B testing.
Research Intern, Microsoft Research, 2019.5-2019.8
Bings Ads, Mentored by Emre Kiciman and Denis Charles
Built robust click predictions model with data from randomized experiments in online advertisement.
Extracted invariant features for robust predictions with counterfactual reasoning.
The proposed method was shipped in production and resulted in one publication in ML conference.
Travel Award, NeurIPS 2019
Runner up of Tom Ten Have Poster Competition, Atlantic Causal Inference Conference (ACIC), 2019
First Year Fellowship, Department of Statistical Science, 2017
National Scholarship: offered to the top 5 students one year
Mathematical Contest in Modeling: Outstanding Winner for Problem of "Data insight", Ranking Top 3 worldwide
Grosvenor Academic Scholarship: offered to the top 10 students one year
Wuliangye Academic Scholarship: offered to the top 10 students one year
Reviewer for American Journal of Epidemiology, Journal of Computational and Graphical Statistics, Journal of American Statistical Association, Journal of Causal Inference, Statistics in Medicine.
Translate the classic textbook, Causal Inference in Statistics, Social and Biomedical Sciences, by D.Rubin and G.Imbens into Chinese.
Teaching assistant for Causal Inference at Duke University (STAT 640, Fall 18,20)