Teaching & Mentoring
Teaching Approach
I teach quantitative methods as a sequence of substantive decisions: define the question, choose a defensible measure and estimand, understand how the data were produced, select a method, interpret the result, and state its limits.
Students should be able to explain what evidence supports a conclusion, where uncertainty enters, and what additional evidence could change the answer. My teaching makes that reasoning visible and reproducible rather than treating statistical procedures as ends in themselves.
- Make reasoning visible I ask students to articulate the substantive question, measure, estimand, assumptions, and limits behind an analysis—not only reproduce a procedure.
- Scaffold reproducible independence Worked examples, annotated code, and structured checkpoints gradually give way to independent choices and reproducible analysis.
- Mentor toward ownership In research supervision, I move from technical guidance to student-led decisions, interpretation, documentation, and communication.
I bring this approach to causal modeling, statistics, demographic methods, population studies, research supervision, and technical workshops. I completed pedagogical training through Ohio State's Drake Institute for Teaching and Learning in 2021.
Teaching Experience
SOCIOL 8607: Causal Modeling
Teaching Assistant · The Ohio State University
Facilitated class discussion and provided coding and programming support.
SOCIOL 3549: Statistics in Sociology
Recitation Leader · The Ohio State University
Led synchronous recitation and lab sections with Stata examples; many students were taking their first statistics course.
380.651: Methods and Measures in Population Studies
Teaching Assistant · Johns Hopkins Bloomberg School of Public Health
380.603: Demographic Methods in Public Health
Teaching Assistant · Johns Hopkins Bloomberg School of Public Health
Research Supervision & Mentoring
Doctoral research supervision · Reference Data Archive
Supervised a PhD research assistant at The Ohio State University on data-quality checks, data cleaning, and coding.
Undergraduate research mentoring
Mentored an undergraduate research assistant at The Ohio State University.
Doctoral research supervision · Reference Data Archive
Supervised a PhD research assistant on data-quality checks, data cleaning, and coding during a visiting appointment at the Africa Health Research Institute.
Graduate research supervision
Supervised 10+ graduate research assistants at Johns Hopkins Bloomberg School of Public Health working on literature review, data extraction, data analysis, modeling support, and visualization.
Summer research mentoring
Mentored two undergraduate students through the Johns Hopkins Bloomberg School of Public Health Diversity Summer Internship Program.
Workshops & Training
R workshops
Hosted by the Sociology Graduate Student Association, The Ohio State University
Verbal autopsy data analysis workshops
Hosted by the openVA team, The Ohio State University
Teaching Areas
- Quantitative Methods and Applied Statistics
- Survey Methodology, Measurement, and Data Quality
- Demography and Population Health
- Computational Social Science and Data Science
- Global Health Data and Mortality Measurement