teaching

Teaching has pushed me beyond my comfort zone and taught me that the best student does not necessarily make the best teacher. I'm grateful for the opportunities to be able to share my perspective with others in the pursuit of achieving understanding.

6.S191 Introduction to Deep Learning

Teaching Assistant | Jan 2025

I'm super excited to be one of four in-person teaching assistants for one of the most highly enrolled classes during MIT's Independent Activities Period (IAP). To be updated!

20.309 Bioinstrumentation & Measurement

Teaching Assistant | Sep 2024 - Dec 2024

As one of three teaching assistants of this lab-based class, I hosted lab hours and graded problem sets each week. I also provided exam review sessions to students and answered students questions asynchronously on Slack. Sitting next to students while they debugged breadboards and built their own microscopes was incredibly fun; when the lightbulb went off, I felt just as gratified as the student. 20.309 covers quantitative biological measurement, electronic and optical instrumentation, microscopy and imaging systems, signal processing and noise analysis, and statistical interpretation of experimental data.
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6.3700 Probability & Statistics

Grader | Sep 2025 - Dec 2025

As one of five graders, I provided feedback to 120 students weekly through grading their problem sets. Having been one of the most challenging math courses I've ever taken, being given the chance to be a grader was validating and a great opportunity to continue reviewing course material. This course covers an introduction to probability theory, modeling and analysis for probabilistic systems, and Bayesian inference.

coursework

Coming into MIT as a first-gen, low-income student, browsing the course catalog made me feel as though I suddenly had the entire world at my fingertips. My limiting reagents became my time and the battery on my Apple Pencil. I cannot overstate my gratitude towards MIT for providing me a world-class, holistic education, which is least of all described by the smattering of classes I took during my time here.

(G) indicates a graduate level course.

Computer Science & Machine Learning

  • 6.7920 Reinforcement Learning (G)
  • 6.7930 Machine Learning for Healthcare (G)
  • 6.4300 Computer Vision
  • 6.390 Machine Learning
  • 6.C57 Optimization Methods
  • 6.1210 Algorithms
  • 6.1010 Fundamentals of Programming

Mathematics

  • 18.06 Linear Algebra
  • 6.3700 Probability & Statistics

Biology & Chemistry

  • 5.12 Organic Chemistry
  • 7.05 Biochemistry
  • 7.03 Genetics
  • 7.06 Cell Biology

Biological Engineering

  • 20.110 Thermodynamics
  • 20.309 Bioinstrumentation and Measurement
  • 20.320 Analysis of Biomolecular and Cellular Systems
  • 20.260 Computational Analysis of Biological Data

Tangential Academic Pursuits

  • 21G.715 Topics in Medicine and Public Health in the Hispanic World
  • 15.373 Venture Engineering
  • 6.4590 Foundations of Information Policy
  • 24.05 Philosophy of Religion
  • 2.00B Toy Product Design