Teaching & Courses

Teaching

Date

Role

Course Title

Students

Where

2018, 2019 Teaching Assistant Fundamentals of Data Science Masters Stanford MS&E
2019 Teaching Assistant Computer Science High School AddisCoder
2019 Course Design Assistant Data Science: An Introduction to Prediction Executive Education Stanford MS&E
2018 Teaching Assistant Data Science for Online Marketplaces MBA Stanford GSB
2017, 2018 Guest lecturer Methods & Models for Policy and Strategy Analysis Undergrad Stanford MS&E
2013 Teaching Assistant Introduction to Computing Undergrad UT Austin Computer Engineering
2012 Teaching Assistant Integral Calculus Undergrad UT Austin Math

Other

  • In partnership with a Houston-based non-profit, SWAG to College, I wrote a career guide for highschoolers considering majoring in computer science. Available here.
  • In 2016, I taught a Splash! class to high school kids on philosophical questions in technology, focusing on connections to the philosophy of mind.
  • UT Austin EE306 Study Guide/Course Packet: I led a team who wrote and published course packet and review guide for Introduction to Computing at UT. The packet serves as a supplement to the textbook and more thoroughly explained important and difficult concepts. It covers transistors, digital logic, binary, assembly language, debugging skills, and intro-level computer architecture. This packet has been made available to the 300 students taking EE306 each semester. Available here.
  • UT Austin PHL610QB Philosophy of Mind Study Guide: A friend and I wrote and shared a study guide for a Philosophy of Mind course at UT Austin. The packet covers various views of Consciousness, the Problem of Other Minds, the Mind-Body Problem (Dualism, Monism, and Physicalism), and Personal Identity. We gave a lecture based on the packet to our class. Available here.

Selected Coursework

  • Stanford Graduate Courses: Advanced Algorithms for Machine Learning, Reinforcement Learning, Deep Learning for Natural Language Processing, Statistical Learning Theory, Approximation Algorithms, Convex Optimization, Large Markets and Games, Statistical Signal Processing, Linear Dynamical Systems, Wireless Communications, Law Order & Algorithms, Theory of Probability, Empirics of Online Marketplaces
  • UT Austin Graduate Courses: Probability & Stochastic Processes, Information Theory, Digital Communications, Wireless Communications
  • UT Austin Undergraduate Courses: Algorithms, Embedded and Real-Time Operating Systems Lab, Computer Architecture, Digital Logic Design, Real Analysis, Digital Image and Video Processing, Digital Signal Processing, Real-time DSP Lab, History of Economic Thought, Foreign Policy