I am a Postdoctoral Researcher supervised by Dr. Wensheng Guo and Dr. Wei Yang in the Department of Biostatistcs, Epidemiology and Informations (DBEI) at the Perelman School of Medicine, University of Pennsylvania. My research focuses on developing methods to construct summary statistics that describe features in the data that are most relevant to some outcome of interest.
Currently, my methods development are motivated by electrocardiogram data and cardiovascular endpoints in renal disease patients participating in the Chronic Renal Insufficiency Cohort (CRIC) study.
Part of my duties as a postdoctoral researcher includes providing biostatistical support for clinical trials and cohort studies.
I obtained my PhD in Statistics at Penn State University, under the supervision of Dr. Bing Li, where I researched and developed sufficient dimension reduction methods for classification and functional data.
Current
Fall 2022 - Present – Postdoctoral Researcher in Biostatistics | Perelman School of Medicine, University of Pennsylvania
- Supervisor(s): Dr. Wensheng Guo and Dr. Wei Yang
- Developing methodological advances for summarizing Electrocardiograms
- Analyzing crossover trial for vascular effects of e-cigarette
Instructor
Introductory Statistics, STAT200 | Summer 2019, Summer 2020 Online, Summer 2022
Elementary Probability, STAT318 | Fall 2019, Spring 2019, Fall 2018
Introduction to Probability Theory, STAT414 | Summer 2018 World Campus
Teaching Assistant
- STAT517 - Probability Theory I (Fall 2020)
- STAT561 - Statistical Inference I (Winter 2020)
- STAT414 - Introduction to Probability Theory (Fall 2017, Summer 2017 World Campus)
- STAT319 - Introduction to Statistics (Winter 2017)
- STAT318 - Elementary Probability (Winter 2018)
- STAT200 - Introduction to Statistics (Fall 2016)
Education
PhD in Statistics | Pennsylvania State University, 2022
MSc in Statistics | University of Toronto, 2016
MA in Economics| University of Toronto, 2015
BSc (Honors) in Mathematics | University of Toronto, 2014
Programming Languages
- R, TeX, C++ (via Rcpp), SAS, Python, SQL, MATLAB, HTML
Languages
- English | Native level fluency