Involved in the development of cutting-edge statistical methods and machine learning algorithms inspired by massive healthcare datasets.

• Develop innovative statistical methods and machine learning algorithms for healthcare data analysis.
• Conduct research in areas of generative models for biomedical data (e.g., echocardiograms, genetics, EHRs); dynamic risk prediction models; Data harmonization techniques; EHR phenotyping.
• Collaborate with Dr. Anru Zhang, Eugene Anson Stead, Jr. M.D. Associate Professor.
• Contribute to the writing and publication of scientific papers.

Responsibilities include: communicate recommendations for statistical modeling actions to non-technical audiences

• Prenatal Diurnal Cortisol paper: I carried out the statistical analysis by building the lmer model, wrote code for the team and revised the statistical section of the paper.
• Adverse Childhood Experience paper: I developed the analytic approach in the paper, edited and revised the final draft.
• Fetal Growth project: I wrote a function to calculate estimated fetal weight percentile based on infant demographics and help the team gain insights about fetal growth curve patterns.
• Immune Age Difference paper: I introduced the “immune age difference,” a novel variable reflecting the relative maturity of infants’ immune systems.
• Baby Cortisol Analysis project: I conducted statistical imputation method to resolve the missing data issue in the analysis.
• Mom Postnatal Analysis project: I did statistical analysis to batch correct the problematic batches and outliers in the data.

• Launch SuretyOpsNLP 0.1 Project: Predicting the profitability of construction projects
• Build NLP models to capture the hidden signals of job profitability and contribute to benchmark model robustness

• Project 1: Statistical wind conditions assessment across inland and off-shore US under future climate scenarios
• Project 2: Estimate directional wind speed quantiles and quantify the uncertainty from internal variability & parameter sensitivity

• Project 1: Use text mining & optimization algorithm to significantly reduce overlapping in the conference schedule
• Project 2: Use topic modeling to design movie recommender system

Responsibilities include: grade homework, give guest lectures

• BST 426 [Spr 24] - Linear Models (graduate course)
• BST 426 [Spr 23] - Linear Models (graduate course)
• BST 467 [Spr 21] - Applied Statistics in the Biomedical Sciences (graduate course)
• BST 467 [Spr 20] - Applied Statistics in the Biomedical Sciences (graduate course)

Responsibilities include: grade homework, exams

• STAT 747 [Spr 18] - Principles of Statistical Data Mining (graduate course)
• MATH 251 [Spr 17] - Probability and Statistics