Artificial Intelligence, Instructor

January 2021

Two-week survey course for 7th-9th graders that provides an overview of artificial intelligence; understanding the core concepts of AI: perception, representation & reasoning, learning, natural interaction, and societal impact; recognizing AI in their daily lives; investigating high-level unsupervised and supervised learning algorithms; critical thinking about fairness, bias, and ethics in AI.

Stanford Pre-Collegiate Studies

Numerical Simulation, Instructor

August 2021

Two-week undergraduate-level course for 11th-12th graders that covers efficient computational methods for solving mathematical equations with a high degree of precision. Topics include function evaluation, interpolation, extrapolation, regression; solution of linear and nonlinear algebraic equations; numerical optimization, differentiation, and integration; solution of differential equations and eigenvalue problems; simulation of real-world dynamical systems.

Artificial Intelligence, Instructor

June 2020 August 2020 June 2021

Two-week undergraduate-level course for 11th-12th graders that provides an overview of modern artificial intelligence; development of mathematical and programming proficiency in machine learning and optimization, including supervised learning, unsupervised learning, and reinforcement learning algorithms.

Stanford University

AA 228/CS 238: Decision Making under Uncertainty, Teaching Assistant

Autumn 2020

Techniques for decision making under uncertainty and overview of necessary tools for building autonomous and decision-support systems; computational methods for solving decision problems with stochastic dynamics, model uncertainty, and imperfect state information; Bayesian networks, influence diagrams, dynamic programming, reinforcement learning, and partially observable Markov decision processes (POMDPs).

Texas A&M University

AERO 430: Advanced Numerical Simulation, Teaching Assistant

Spring 2018 Fall 2018 Spring 2019

Numerical and analytical simulation of physical problems in sciences and engineering using applied methods; developing and using numerical techniques for physical problems described by nonlinear algebraic equations, ordinary and partial differential equations.

MATH 152: Engineering Mathematics II, Teaching Assistant

Spring 2017

Differentiation and integration techniques and their applications (area, volumes, work), improper integrals, approximate integration, analytic geometry, vectors, infinite series, power series, Taylor series, computer algebra.

ENGR 289: Engineering Mathematics, Teaching Assistant

Fall 2016

Study of functions, graphs of polynomial and rational functions, radical functions, exponential and logarithmic functions, inequalities, trigonometric functions, fundamental identities, right triangles, trigonometric equations.