Teaching Interests

My teaching interests span applications of machine learning to finance, asset pricing, macroeconomics, investments, and fixed income at any level from introductory undergraduate through advanced masters.

Working at the nexus of computational methods and finance, I particularly enjoy bridging this gap for others: teaching finance fundamentals to technical audiences and technical methods to advanced finance and management students. I focus on integrating economic theory with mathematical modeling and numerical methods, emphasizing a blend of intuition and practicality to provide students with both theoretical foundations and real-world quantitative skills.

Teaching Experience

University of Toronto

Graduate

• Python for Business (asynchronous pre-course), All Masters’ Programs, 2026–
• Analytical Methods in Finance (RSM 8341), Master of Management Analytics, 2026–

Undergraduate

• Applications of Machine Learning in Finance (RSM 338), Commerce, 2026–
• Fundamentals of Accounting and Finance (JRE 300), Engineering, 2024–
• Investments (RSM 336), Commerce, 2024

Carnegie Mellon University

Graduate

• Advanced Microsoft Excel Workshop, Master of Business Administration, 2021–2023

Undergraduate

• Principles of Macroeconomics (73-103), Undergraduate, 2023
• Math-Finance Summer Undergraduate Research Program, Undergraduate, 2023

Open-Source Teaching Tool: Creating Teaching Content with AI Tools as Writing Assistants

I explain a flexible workflow framework for creating custom course materials using AI assistants as writing tools. The approach implements an iterative content generation pipeline where instructors retain control of pedagogical structure while delegating drafting, formatting, and iteration to AI. This editor-first methodology leverages modern language models to efficiently produce lecture slides, detailed notes, and practice materials tailored to specific student populations.

The flexible framework allows instructors to easily adapt the methodology to their own courses by customizing student level, examples, technical depth, and exposition style through LaTeX templates and AI configuration files.

GitHub: Creating Teaching Content with AI Tools as Writing Assistants