About Me

I’m a Biostatistics Ph.D. candidate at Northwestern University Feinberg School of Medicine, working under the mentorship of Prof. Denise M Scholtens. My research involves developing statistical models and deep learning methods that address complex maternal data, expecially Missingness in Time Series data.

My academic journey began at Wuhan University, China where I pursued my Bachelor’s degree in Life Science and Biotechnology. Thereafter, I moved to the New York to complete my Master’s degree in Biostatistics from Columbia University, under the guidance of Prof.  Qixuan Chen and Prof.  Roderick Joseph Little from the University of Michigan. Post my Master’s, I worked as a Data Analyst at Columbia University Mailman School of Public Health, which honed my analytical skills further.

Research Interests

• Missing Data: Multiple Imputation, Deep Learning based Imputation
• Machine Learning: LTSM, Transformer, BRITS
• Reinforcement Learning: Recursing with benefit for EHR data
• Functional Data Analysis: Functional regression, and clustering methods with missing data
• Bayesian Regression: Bayesian Average, BART

Awards

• [2023] Student Paper Award Winner, Association of Clinical and Translational Statisticians

• [2021] Best Dashboard, Biostatistics In Action

• [2015-2019] National Scholarship & Merit Student & Excellent Student Leader, Wuhan University

• [2015] Bronze Medal, National Youth Science and Technology Innovation Competition