teaching
as instructor:
- Understanding Machine Learning (ESE 188), Spring 2025 & Fall 2025. This was a general audience 3-credit course, aimed at gaining an intuitive understanding of modern machine learning techniques. This was a super interesting course to prepare and teach, and I’m happy to chat about this experience with anyone preparing a similar course!
Some classes I’ve served as the teaching assistant for at SBU:
- Random Signals and Systems (ESE 306), Spring 2022 & Summer 2022, Graduate Teaching Assistant [Recitation Notes]
- Programming Fundamentals (ESE 124), Fall 2021, Graduate Teaching Assistant
- Classical Physics I (PHY 131), Fall 2020, Undergraduate Teaching Assistant
mentoring
In 2026, I mentored Luke Snow, a PhD research intern at Basis Research Institute, on Wiener-space cubature for filtering and sequential likelihood-informed subspaces.
I’ve also had the pleasure of mentoring several students in the Directed Reading Programs of CUNY and SBU. I’ve mentored the following projects there:
- Gaussian Processes and Bayesian Optimization
- Hamiltonian Monte Carlo — Jonathan Jaimangal (Outstanding Poster Award, CUNY Directed Reading Program)
- Dynamic Programming and Reinforcement Learning
- Probabilistic Machine Learning
- Fourier Analysis & Its Applications
- Elements of Statistical Learning
In Spring 2022, I served as a volunteer TA for an online version of Bayesian Data Analysis targeted towards those from the Global South and other under-represented groups.