CHAI Seminar: Advanced PhD Student Talk by Calvin Nau, PhD student, Industrial/Mechanical Engineering, RIT
Date: Monday, March 30, 2026, 12:00 PM- 1:00PM
Speaker: Calvin Nau, PhD Candidate, Rochester Institute of Technology
Title: Artificial Intelligence A Mutually Beneficial and Combinational Optimization: Relationship in Mathematics
In-Person: Golisano Hall (70), Room CYB 1720-1730
Abstract: Machine learning and AI address data representation and decision-making through a learned heuristic representation of complex systems. Combinatorial optimization determines optimal decisions for problems with an enumerable but finite set of feasible decisions, using constrained, interpretable modeling approaches. In this talk, an overview of the long-standing exchange of research between the fields of AI/ML and CO will be given. We described how AI/ML is applied to generate CO inputs or perform CO heuristically and how CO may be used as a form of ML in and of itself. Perspective will be offered on how AI/ML may become more human aware, through the integration and adoption of CO approaches, and how CO's human awareness is jeopardized by the adoption of AI/ML methodologies. The optimization of organ exchange, a resource allocation problem with tangible human impacts, will be used as an exemplar of the risks posed by each methodology to the other and the significance of human-aware AI. We conclude with a discussion of challenges and open research questions prompted by the exchange of research between the fields.
Bio: Calvin Nau is a Mechanical and Industrial Engineering PhD student advised by Dr. Katie McConky. His research focuses on combinatorial optimization, graph machine learning, and the intersection of these fields. Currently, he is applying these approaches to improve the efficiency and fairness of planning live donor kidney transplants.
Event Snapshot
When and Where
Who
This is an RIT Only Event
| Cost | FREE |
Interpreter Requested?
No