Teaching
ECSE 316 — Signals and Networks
· Department of Electrical & Computer Engineering, McGill UniversitySeptember 2025
I have been part of the ECSE 316 instructional team since Fall 2020, serving as a TA and lab instructor across three offerings (~90 students per semester). In Fall 2025 I was promoted to faculty lecturer of record, responsible for leading lectures, coordinating labs, and updating the Python-based tooling for complex signal analysis.
- Guided lab sections covering convolution, frequency-domain analysis as well as the fundamentals of networking.
- Managed two teaching assistants.
ECSE 416 — Intro to Telecommunications Systems
· Department of Electrical & Computer Engineering, McGill UniversityJanuary 2023
Across Winter 2020-2023 I TA'd three offerings of ECSE 416 (~40 students per semester), where I led weekly labs.
- Earned the departmental Teaching Award (top-ranked across 500+ Faculty of Engineering courses) for student mentorship and course-wide support queues.
- Supported exam design, office hours, and tutorial recordings focused on demystifying telecom abstractions through hands-on projects.
ECSE 211 — Design Principles & Methods
· Department of Electrical & Computer Engineering, McGill UniversitySeptember 2021
From 2019 through 2025 I supported five offerings of ECSE 211 (~120 students per term) covering design methodology, prototyping, and project communication.
- Coached multidisciplinary project teams on requirements definition, robot prototyping, and technical writing.
- Ran design labs, grading sessions, and code reviews to keep student teams on track during intensive build weeks.
MAIS 202 — Intro to Machine Learning
· McGill University, McGill AI SocietyOctober 2019
I designed this zero-credit seminar for the McGill AI Society to give undergraduates a practical introduction to modern machine learning. Students completed weekly lectures, coding assignments, and final projects that emphasized both intuition and hands-on implementation.
- Delivered two offerings during Fall 2019 to cohorts of ~30 students each.
- Earned honorary accreditation from the McGill Faculty of Engineering so the course appears on official transcripts (0 credits).
- Produced the full curriculum, lecture material, and assessment rubrics covering supervised learning, neural networks, and applied ML tooling.