Discrete time Markov chains, Poisson and renewal processes; transient and limiting behavior; average cost and utility measures of systems. Intended for Ph.D students. Crosslisted with MATH 6761.

This advanced undergraduate course introduces the mathematical principles behind probabilistic modeling, optimization-based model-fitting, and statistical inference, which form the bedrock of ML and AI systems.

Special Topics in the field of Operations Research.

Special topics in Industrial and Systems Engineering.

This course explores the intersection of optimization, economics, and artificial intelligence in the design and analysis of markets and resource allocation mechanisms. Topics include matching and assignment markets, market equilibrium and computation, and dynamic resource allocation and learning. Applications span healthcare, labor markets, transportation, electricity, and other societal systems. Emphasis is placed on computational methods, strategic incentives, efficiency, fairness, and the interaction between algorithms and human behavior. The course includes a substantive project that allows students to apply theoretical and computational tools to conduct original research or develop practical digital tools addressing real-world challenges in market design and societal systems.

Special topics in Industrial and Systems Engineering.

Methods and applications for life cycle assessment of environmental impacts of products, services, and decisions, with process-based and input-output modeling for attributional and consequential analyses.

Courses in special topics of timely interest to the profession, conducted by resident or visiting faculty.

Special Topics in the field of Operations Research.

Healthcare systems involve patients, providers, insurers and regulators aiming to optimize quality, access, efficiency. Topics include systems engineering methods to analyze and design healthcare systems.