Eight course sections at Northeastern, two courses of my own in Istanbul, and the summer institutes and workshops I’ve led — the record below, and the philosophy behind it at the end.

Experience

Traditional Classroom

Northeastern University — Department of Political Science · 2021–present. Eight course sections across the curriculum, working with the faculty who taught them.

Methods & Programming

  • Statistical Analysis (graduate) — with Beatrice Magistro. Graduate statistics in R: regression, causal inference from experiments and observational data, statistical inference.
  • Research Methods (undergraduate, two sections) — with Eliza Osorio Castro. Research design, measurement, and hypothesis testing across quantitative and qualitative traditions — including a guest lecture of my own, Research Design in Practice (slides (PDF)).
  • Quantitative Techniques (undergraduate) — with Sunny Yang. Descriptive statistics, distributions, estimation, group-difference tests, correlation and regression.

Substantive Courses

  • Comparative Politics (undergraduate) — with Emily Clough.
  • Government & Politics in the Middle East (undergraduate) — with Alice Verticelli.
  • Globalization & International Affairs (undergraduate, two sections) — with Risa Kitagawa and Alice Verticelli.

Alongside the sections: NULab Digital Integration Teaching Initiative (DITI) — Fellow · Summer 2022, integrating digital and computational methods into the classroom.

Kadir Has University, Istanbul — Visiting Lecturer · 2020–2021. Two undergraduate courses of my own, end to end — lectures, assessment design, grading:

  • Computational Thinking — a Python-based introduction to programming and computational problem-solving.
  • Civic Values — a substantive course on citizenship and civic life.

Summer Institutes & Workshops

Courses I’ve led:

  • AIDE Summer Program — AI Bootcamp Lead (Instructor) · The Ethics Institute, Northeastern · May–September 2025. Twelve labs taking fifteen philosophy and CS graduate students from Python fundamentals to building with LLMs: supervised ML, algorithmic fairness, differential privacy, transformers by hand, LLM auditing, RAG. All materials are open — syllabus (PDF) · labs on GitHub.
  • SICSS-Istanbul — Co-founder, Co-organizer & Instructor · four editions, 2019–2023. Two-week graduate institute in programming, data collection, and text analysis; mentoring teams through the project-based second week. Returned in 2026 as guest lecturer: Anthropology of Machines (slides (PDF)).
  • BLISS — Boston LLMs Initiative for Social Sciences — Co-founder · 2025–present. Faculty panel and hands-on workshops: Transformers by Hand; Hugging Face & APIs for LLM Use. → bliss.boston

This teaching is turning into a book: The Anthropology of Machines — mechanistic interpretability for social scientists, written in the open. Everything by hand first, everything connected to a real research task, and honest about what we do and do not know.

Teaching Philosophy

A theory is a model. A tool is a model. Even the data is a model. Why I teach from that idea, what these classrooms taught me, and what AI changes — the full essay: Teaching Philosophy.