Primary Instructor

• Python for Analytics (INDENG 210; graduate-level). Spring 2025, UC Berkeley.
• Introduction to Machine Learning and Data Analytics (INDENG 142; upper-level undergraduate). Spring 2025, UC Berkeley.
• Optimization Analytics (INDENG 240; graduate-level). Fall 2024, UC Berkeley.
• Analysis and Design of Databases (INDENG 215; graduate-level). Fall 2024, UC Berkeley.
• Linear Algebra and Differential Equations (553.291; undergraduate-level). Summer 2023, Johns Hopkins University.
• The Role of Mathematical Optimization in the 21st Century (500.111; undergraduate-level). Fall 2022, Johns Hopkins University.
• Introduction to Scientific Programming in Python (553.285; undergraduate-level). Winter 2022, Johns Hopkins University.
• Introduction to Scientific Programming in Python (553.285; undergraduate-level). Winter 2021, Johns Hopkins University.

Other Teaching and Workshops

• Workshop: Coding with AI - Best Practices. March 2025, UC Berkeley, Bay Area Decision Sciences Summit.
• Workshop: INMAS Python Bootcamp. October 2021, Johns Hopkins University.
• Calculus Instructor, CSTEP Program Fordham University, Fall 2018 & Spring 2019.

Teaching Awards & Recognition

• Prof. Joel Dean Award for excellence in teaching (Johns Hopkins University): 2019/20, 2020/21, 2021/22
• Whiting School of Engineering Teaching Award (Johns Hopkins University): 2022 finalist
• Promotion to JHU Applied Math and Statistics Teaching Fellow 2022
• Promotion to JHU Applied Math and Statistics Apprentice Teaching Fellow 2021

Teaching Assistantships

• Combinatorial Optimization 553.766, Spring 2022 and 2024.
• Probability Theory II 553.721, Spring 2021.
• Stochastic Processes 553.626, Spring 2021.
• Probability Theory 553.720, Fall 2020.
• Introduction to Probability 553.420/620, Fall 2019, Spring 2020, and Fall 2020 (the infamous one - iykyk).
• Scientific Computing: Differential Equations 553.384, Spring 2020.
• Mathematical Modeling and Consulting 553.600, Fall 2019.