Teaching Experience

Designed and taught a new undergraduate course, Introduction to Public Health Economics and Policy, at Caltech, Division of Humanities and Social Sciences (Spring 2023–2024: 18 students & Spring 2024–2025: 36 students). Developed course materials, led lectures, and facilitated interactive discussions to engage students in key economic and policy concepts. Received significantly above-average scores on all 13 teaching evaluation metrics, including 11 metrics above both departmental and Caltech-wide averages, demonstrating consistently high student satisfaction and instructional effectiveness.

Served as a teaching assistant for the graduate-level course Applied Linear Regression Analysis at the Arctic University of Norway, Faculty of Health Sciences (2020). Led group exercises and provided hands-on instruction in R Studio, helping students develop practical programming and data analysis skills.

Ready-to-teach courses:  

Statistics / Data Science: Applied Statistics, Machine Learning & Data Science, Predictive Modeling, Causal Inference

Health & Public Policy: Health Informatics, Biostatistics, Epidemiology, Health Policy Analysis, Quantitative Methods in Public Health

Business & Analytics: Business Analytics, Data-Driven Decision Making, Quantitative Methods for Management

Interdisciplinary / Applied Topics: Environmental & Climate Data Analytics, Computational Social Science, Policy Evaluation, AI for Public Health

Mentorship

2024 — Co-mentor for undergraduate research, Caltech Summer Undergraduate Research Fellowship Project. Co-mentored an undergraduate for six months, guiding literature reviews, research question development, data collection, deep learning implementation, result interpretation, and full project execution.

2024 — Co-supervisor for a master’s Thesis student at the University of Cambridge, UK. Thesis passed on first submission without revisions; ranked in the top 25% of the cohort.

Selected Student Feedback Excerpts: