Teaching

Georgia Institute of Technology

CSE/ISyE 6740 — Computational Data Analysis (Machine Learning)

Offered: Fall semesters
Level: Graduate / Advanced Undergraduate

An introduction to statistical machine learning and data analysis. Topics include: supervised learning (regression, classification, SVMs, neural networks), unsupervised learning (clustering, dimensionality reduction, PCA), probabilistic graphical models, and optimization methods for ML.

CSE 8803 — Special Topics: AI for Social Good

Offered: Spring semesters
Level: Graduate

Advanced topics at the intersection of AI, optimization, and social impact applications. Topics include decision-focused learning, restless multi-armed bandits, game-theoretic planning, and deployed AI systems in health and conservation. Students complete a research project applying these methods to a real-world social impact domain.

For course materials, slides, and assignments, enrolled students should refer to Canvas.