Teaching
Teaching Philosophy
I approach teaching statistics as $\color{#00a0d1}{\text{building intuition first, formalism second}}$. My primary goal as an instructor is to help students discover their intellectual potential and develop the confidence to think critically and logically. I strive to make students embrace mistakes not as failures but as valuable windows into their gaps in understanding. To be able to achieve this goal, I require an active participation from my audience and tend to pause and ask “What should the next step be, and why?”. In proof-intensive courses, I frequently encourage students to articulate the role of every assumption and explore what happens when those assumptions fail.
$\color{red}\text{Michigan State University}$
STT 882: Probability Theory II
Grader · Spring 2026
Second-semester graduate course covering extensions of the CLT, martingale theory and Brownian motion.
Responsibilities: Graded weekly assignments and provided feedback to graduate students preparing for the qualifying exams
Instructor: Prof. Shlomo Levental
Enrollment: ~12 students
STT 872: Statistical Inference I
Grader · Spring 2026
Second-semester graduate course covering advanced theoretical statistics, decision theory, point and interval estimation, and hypothesis testing.
Responsibilities: Graded weekly problem sets and provided feedback to graduate students preparing for the qualifying exams.
Instructor: Dr. Shrijita Bhattacharya
Enrollment: ~12 students
STT 843: Multivariate Analysis
Grader · Spring 2026
Second-semester graduate course covering advanced Multivariate normal distribution, tests of hypotheses on means, multivariate analysis of variance, discriminant analysis, principal components and factor analysis.
Responsibilities: Graded \& drafted solutions to weekly problem sets. I also provided feedback to enrolled students.
Instructor: Dr. Guanqun Cao
Enrollment: ~10 students
STT 200: Statistical Methods
Instructor · Summer 2023
Undergraduate course covering data analysis, informal probability models and random variables, randomization-based inference, confidence intervals, and simple linear regression
Responsibilities: Held weekly office hours to work through course concepts and problem sets with students, and collaborated with the instructional team in weekly meetings to design and grade homework, midterms, and final exams.
Enrollment: ~30 students
STT 200: Statistical Methods
Teaching Assistant · Fall 2022, Spring 2023, Fall 2023, Spring 2024, Fall 2024, Spring 2025, Fall 2026
Undergraduate course covering data analysis, informal probability models and random variables, randomization-based inference, confidence intervals, and simple linear regression
Responsibilities: Led weekly recitation sections; hosted office hours at the Statistics Learning Center; graded recitations and exams.
Instructor: Camille Fairbourn
Enrollment: ~90 students
$\color{red}\text{University of Ghana}$
STAT 221: Introductory Probability I
Teaching Assistant · Fall 2019
Undergraduate course covering foundational probability laws, random variables, and standard discrete and continuous distributions.
Responsibilities: Conducted weekly tutorial sections by solving custom problem sets; hosted office hours for students needing extra help with the material; graded exams and homeworks. Instructor: Prof. Louis Asiedu
Enrollment: ~100 students
ACTU 407: Survival Analysis and Modelling
Teaching Assistant · Fall 2019
Undergraduate course introducing survival analysis and its real life applications. The course covered topics such as, survival distribution functions, force of mortality, hazard rates, parametric and non-parametric methods to estimate survival probabilities.
Responsibilities: Conducted weekly tutorial sections by solving custom problem sets; hosted office hours for students needing extra help with the material; graded exams and homeworks. Instructor: Prof. Louis asiedu
Enrollment: ~20 students
STAT 451: Introduction to Stochastic Processes
Teaching Assistant · Fall 2019
Undergraduate course covering discrete and continuous time processes, Markov chains, random walks, birth and death processes, random trees and Galton-Watson processes,
Responsibilities: Conducted weekly tutorial sections by solving custom problem sets; hosted office hours for students needing extra help with the material; graded exams and homeworks. Instructor: Prof. Louis asiedu
Enrollment: ~20 students
STAT 608: Biostatistical Processes
Teaching Assistant · Spring 2020
Graduate course covering various modelling techniques and their applicability to data mainly in the fields of Biology and Medicine. Some topics include: Deterministic and Stochastic Models of Population Change; the concept and structure of life tables, competing risks of illness and death, survival and life expectancy of populations at risk.
Responsibilities: Conducted weekly tutorial sections by solving custom problem sets; graded exams and homeworks.
Instructor: Prof. Louis asiedu
Enrollment: ~15 students
STAT 446: Multivariate Methods
Teaching Assistant · Spring 2020
Undergraduate course introducing the theory and methods of multivariate data analysis. Topics discussed included: Estimation and Tests of Hypotheses, Profile Analysis, Discriminant Analysis, Factor Analysis, Principal Component Analysis and Cluster Analysis.
Responsibilities: Conducted weekly tutorial sections by solving custom problem sets; hosted office hours for students needing extra help with the material; graded exams and homeworks. Instructor: Prof. Louis asiedu
Enrollment: ~35 students