Current Teaching

MATH 125
Fall 2025
Numerical Analysis (Undergraduate course)

Analysis of algorithms involving computation with real numbers. Interpolation, methods for solving linear and nonlinear systems of equations, numerical integration, numerical methods for solving ordinary differential equations.

Department of Mathematics, Tufts University
MATH 32
Calculus I
Fall 2019
MATH 70
Linear Algebra
Fall 2021, Spring 2022
MATH 123
Mathematical Aspects of Data Analysis
Summer 2020, Spring 2020, Summer 2021, Fall 2020, Fall 2021
MATH 125
Numerical Analysis
Fall 2022
MATH 126
Numerical Linear Algebra
Spring 2020, Fall 2021
MATH 190
Topics in Linear Algebra
Spring 2020
MATH 190
Nonlinear Optimization
Spring 2023
MATH 225
Numerical Analysis
Spring 2024
MATH 290
Matrix Analysis and Applications
Fall 2023
Department of Mathematics, Rensselaer Polytechnic Institute
Graduate TA
PDEs of Mathematical Physics
Spring 2019
Graduate TA
Advanced Calculus
Fall 2018
Graduate TA
Complex Variables with Applications
Spring 2016
Graduate TA
Foundations of Applied Mathematics
Fall 2015
Graduate TA
Introduction to Differential Equations
Spring 2015
Graduate TA
Multivariable Calculus and Matrix Algebra
Fall 2014
Massachusetts Institute of Technology
Aero/Astro TA
Mechanics and Structures
Fall 2013
ESG TA
Multivariable Calculus
Fall 2009 - Spring 2012
ESP Instructor
Introduction to Existentialism
Summer 2010

Teaching Philosophy

My teaching philosophy is rooted in making mathematics both rigorous and engaging through project-based learning, historical perspective, and interdisciplinary applications. As a teaching assistant at MIT’s Experimental Studies Group, I helped design applied problems that connected core concepts to real contexts, an initiative that contributed to my receiving the Excellence in Undergraduate Teaching award.

In my courses at Tufts, I have emphasized active learning through projects that use real data. For example, students in numerical analysis estimated implied volatility with the Black–Scholes model, while others in data analysis applied mathematical methods to challenges ranging from image recognition to public health. These experiences balance theory with practice and have consistently inspired students to explore mathematics more deeply.

I believe mathematics is best learned when students see it as both a body of knowledge and a way of thinking. By incorporating historical readings and fostering interdisciplinary projects, I aim to show how ideas evolve and how mathematics provides tools for diverse fields. My goal is to create an environment where students feel challenged, supported, and motivated to approach problems creatively and critically.