Awards

2025: I was awarded the Outstanding Graduate Student Instructor Award by the Rackham Graduate School at University of Michigan. Every year, the award recognizes 20 graduate students across the university who show “exceptional ability, continuous growth and creativity as teachers; service as outstanding mentors and advisors to their students and colleagues; and growth as scholars in the course of their graduate programs.”

2024: I was awarded the U-M Graduate Teacher Certificate in recognition of my professional development and experience as an instructor at the University of Michigan (see certificate description).

Previous Teaching Positions

EEB 429: Introduction to Statistical Model Building in R

Graduate Student Instructor (Winter 2024)
Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor

See Authored Assignments

• Week 1: Paths, functions, and tidy data
• Week 2: Data-types, matrices, and indexing
• Week 3: Logical operators, plotting, conditional execution and loops
• Week 4: Writing modular scripts (and Monte-Carlo method)
• Week 5: R-markdown and apply function
• Week 6: Probabilities of composite events
• Week 7: Simulating and sampling
• Week 8: Maximum-likelihood and Bayesian estimation
• Week 9: Stochastic fuctions
• Week 10: Generalized linear models

EEB 485: Population and Community Ecology

Graduate Student Instructor (Fall 2022 & Fall 2023)
Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor

See Authored Assignments

• Week 1: Intro to R
• Week 2: Population Growth
• Week 3: Structured Populations
• Week 4: Competition
• Week 5: Predation
• Week 6: Disease and Networks
• Week 7: Quantifying communities
• Week 8: Biodiversity & Ecosystem Function
• Week 9: Metapopulations and Neutral Theory

Please email me to request the assignments for EEB 485

CMPLXSYS 391: Modeling Political Processes

Graduate Student Instructor (Winter 2022)
Center for the Study of Complex Systems, University of Michigan, Ann Arbor

See Authored Assignments

• Week 1: Condorcet Jury Theorem
• Week 2: Diversity Prediction Theorem & Categorization Error
• Week 3: Linear and Non-linear models (and network template)
• Week 4: Markov models
• Week 5: Equilibrium
• Week 6: Entropy and MaxEnt
• Week 10: Spatial and Hedonic models
• Week 11: Game Theory and Collective Action
• Week 12: Individual value in groups
• Week 13: Optimization landscapes

BIO 173: Introduction to Biology Lab

Graduate Student Instructor (Fall 2021)
Program in Biology, University of Michigan, Ann Arbor