One of the phrases that have stuck with me since my pre-college years is
"zakaate elm dar nashre aan aast," which means the "taxes" on acquired knowledge are best paid by teaching it to others. Being able to integrate research and teaching in an intellectual environment is one of the most rewarding aspects of academia. I believe that research and teaching have a symbiotic relationship; I can instill my research results as fresh materials in the classroom, and the intellectual aspects of teaching can act as an indispensable aspect of my own efforts to grow as a researcher. I have been fortunate enough to serve as a teacher in several roles.
Instructor
- [May 2025] Causal Graphical Methods For Handling Nonignorable Missing Data
Short course presented at the American Causal Inference Conference (ACIC)
[Slides]
- [July 2024] Causal Graphical Methods For Handling Nonignorable Missing Data
Short course presented at the 40th Conference on Uncertainty in Artificial Intelligence (UAI)
[Slides]
- [May 2023] Causal Graphical Methods For Handling Nonignorable Missing Data
Short course presented at the American Causal Inference Conference (ACIC)
[Slides]
- [April 2023] Fairness in Data Science: Criteria, Algorithms and Open Problems
A short course on developed methodologies for "fairness-aware" algorithms.
16th annual Innovations in Design, Analysis, and Dissemination (IDAD)
[Slides]
- [Fall 2022] Advanced Causal Inference
Department of Biostatistics and Bioinformatics, Emory University
[Syllabus]
- [August 2022] Fairness in Data Science: Criteria, Algorithms and Open Problems
A short course on developed methodologies for "fairness-aware" algorithms.
Statistics in Epidemiology session at Joint Statistical Meetings (JSM)
[Slides]
- [Intersession 2020] Should Susan Smoke: An Introduction to Causal Inference
Computer Science Department, Johns Hopkins University
An introductory course in causal inference focusing on building scientific skepticism and introducing students to philosophical and statistical notions of causality.
The course was co-instructed and featured at Johns Hopkins Hub magazine
[Syllabus]
- [Summer 2015] Pre-College Math
Department of Statistics, University of Texas at El Paso
A summer-long course on basic calculus concepts, algebra, trigonometry, and geometry.
Head Course Assistant
- [Spring 2019] Machine Learning: Data to Models
Computer Science Department, Johns Hopkins University
A semester-long course focusing on probabilistic graphical models.
Teaching Assistant
- [Fall 2018] Causal Inference
Johns Hopkins University, Baltimore, MD
- [Spring 2016] Probability and Statistics
University of Texas at El Paso, El Paso, TX
- [Fall 2015] Elementary Statistical Methods
University of Texas at El Paso, El Paso, TX
- [Spring 2015] Calculus I/II
University of Texas at El Paso, El Paso, TX
- [Fall 2013 - Fall 2014] Physics I/II and Laboratory
Istanbul Sehir University, Istanbul, Turkey