teaching
Courses I've taught or for which I've served as a TA.
Courses Taught
- Machine Learning (MIT MITES Semester Program 2025)
- Machine Learning (MIT MITES Semester Program 2024)
Teaching Assistantships
Georgetown University
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COSC-3470 Deep Learning, taught by Sarah Bargal (Fall 2025 - in progress) -
COSC-3470 Deep Learning, taught by Sarah Bargal (Spring 2025) -
COSC-5455 Deep Learning, taught by Sarah Bargal (Fall 2024) -
COSC-5470 Deep Learning for Computer Vision, taught by Sarah Bargal (Spring 2024) -
COSC-5580 Introduction to Data Analytics, taught by Lisa Singh (Fall 2023)
UMass Amherst
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PHYS-281 Computational Physics, taught by Stéphane Willocq (Spring 2022) -
PHYS-131 Introductory Physics, taught by Heath Hatch (Fall 2021) -
PHYS-131 Introductory Physics, taught by Heath Hatch (Spring 2021) -
PHYS-131 Introductory Physics, taught by Heath Hatch (Fall 2020)
Miscellaneous
Student Projects Advised
- Keven Amaya-Muñoz, Arko Barua, and Luan Hoang, to appear at Massachusetts Institute of Technology Undergraduate Research Conference (URTC), 2025.
- Melissa Alfaro-Zeledon and Rida Karim, Identifying Key Factors for Femicide Prevention and Policy Development: Leveraging Supervised Machine Learning with Temporal and Geospatial Analysis. Lightning Talk at URTC, 2024.
- Hubert Hsu and Bethany Ray, MT-MOE: Protein-Specific Drug Design Utilizing Mixture of Experts Transformers. Poster at URTC, 2024
Brief introduction to Google Colab and PyTorch for building convolutional neural networks
The basis of some guest lecturing I’ve done in Sarah Bargal’s classes mentioned above.
Lecture given at Walter Payton Prep High School in Chicago, IL via Zoom
Lecture/Jupyter notebook on n-grams
Workshop on LaTeX
The slides for a workshop I’ve delivered a few times to my fellow graduate students at Georgetown’s Department of Linguistics.
Brief lesson on Shannon information
This was my contribution to a seminar course in which every student was required to present on a technical topic.