Teaching

Fall 2024: Math 173A - Optimization for Data Science

Spring 2024: Math 144 - Introduction to Fourier Analysis

Winter 2024: Math 216B - Mathematical Methods in Data Science

Fall 2023: Math 173A - Optimization for Data Science

Fall 2022: Math 173A - Optimization for Data Science

Winter 2022: Math 144 - Introduction to Fourier Analysis

Fall 2021: DSC 291 - Linear Algebra for Data Science

Fall 2021: Math 277 - Topics in Approximation Theory and Deep Learning

Winter 2021: Math 277 - Topics in Geometric Data Analysis

Winter 2021: DSC 120 - Signal Processing for Data Analysis

Fall 2020: Math 111A - Mathematical Modeling

Fall 2020: Math 10A - Calculus I

Spring 2020: Math 277 - Topics in Applied Approximation Theory and Deep Learning

Spring 2020: DSC 120 - Signal Processing for Data Analysis

Fall 2019: Math 170A - Numerical Linear Algebra

Spring 2019:Math 277 - Topics in Diffusion Geometry and Manifold Learning

Fall 2018: Math 196 - Student Colloquium

Fall 2018: Math 170A - Numerical Linear Algebra

Spring 2018: Math 20C - Calculus and Analytic Geometry for Science and Engineering

Winter 2018: Math 152 - Fourier Series, Wavelets, and Other Useful Bases

Fall 2017: Math 10A - Calculus 1

Advanced Topics in Machine Learning and Data Mining, graduate level, Yale University

Structure of Networks, intro undergraduate course level, Yale University

Elementary Mathematical Models, intro undergraduate course level, University of Maryland