Teaching

At the undergraduate and masters level, I teach courses on the theory and applications of machine learning, which include practical experience for students with a data analytics project. At the PhD level, I teach classes on the foundations of continuous and convex optimization and their modern applications to and connections with statistical learning.

Teaching Experience at UC Berkeley (Instructor)

• Spring 2023:

  • IEOR 242A Machine Learning and Data Analytics I (MAnalytics/MEng)

  • IEOR 262B Mathematical Programming II (PhD/MS)

• Fall 2022:

  • IEOR 142 Introduction to Machine Learning and Data Analytics (Undergraduate)

• Spring 2022:

  • IEOR 262B Mathematical Programming II (PhD/MS)

• Fall 2021:

  • IEOR 142 Introduction to Machine Learning and Data Analytics (Undergraduate)

  • IEOR 242 Applications in Data Analysis (MEng)

• Spring 2021:

  • IEOR 142 Introduction to Machine Learning and Data Analytics (Undergraduate)

  • IEOR 242 Applications in Data Analysis (MEng)

• Spring 2020:

  • IEOR 262B Mathematical Programming II (PhD/MS)

• Fall 2019:

  • IEOR 142 Introduction to Machine Learning and Data Analytics (Undergraduate)

  • IEOR 242 Applications in Data Analysis (MEng)

• Spring 2019:

  • IEOR 242 Applications in Data Analysis (MEng)

  • IEOR 290 Modern Optimization for Statistical Learning (PhD/MS/MEng)

• Fall 2018:

  • IEOR 142 Introduction to Machine Learning and Data Analytics (Undergraduate)

• Spring 2018:

  • IEOR 242 Applications in Data Analysis (MEng)

  • IEOR 290 Modern Optimization for Statistical Learning (PhD/MS/MEng)

• Fall 2017:

  • IEOR 142 Introduction to Machine Learning and Data Analytics (Undergraduate)

• Spring 2017:

  • IEOR 242 Applications in Data Analysis (MEng)

  • IEOR 290 Modern Optimization for Statistical Learning (PhD/MS/MEng)