Michael Chavrimootoo

Assistant Professor of Computer Science, Denison University

(he/him/his)

My research spans computational social choice (COMSOC), which falls within AI (multiagent systems), but also draws on social choice theory, economics, political science, algorithms, and complexity theory.

I'm driven by a need to understand the landscape of the field to find surprising structures and techniques that open new avenues. This had led me to explore the problems in COMSOC (and complexity) to determine precisely what separates them from other problems, and when collapses are hiding in plain sight. I am also interested in developing models to better understand gerrymanderring-like electoral manipulation tactics and provide strong, provably guarantees about those models.

I received my Ph.D. at the University of Rochester (UR). Before that, I completed a BS in Computer Science along a BA in Political Science at UR, with a focus on courses in CS theory, elections, and economic development.

Some problems I've worked on:

• Determining which standard electoral control types are the same in concrete election systems (equivalences that have evaded the field for years).
• Linking search and decision complexities of equivalent electoral control problems, using a new framework we introduced to study/relate the complexity of search problems.
• Determining what properties of an election system lead certain control types to collapse (which immediately yields results for infinitely many systems).
• Providing tools to study the complexity of grid games with irreversible gravity (which were not well-studied; this opens up new research avenues).

Interested in collaborating or chatting? I'm always open to exploring new theoretical concepts in computer science, economics, and math, along with their applications. Feel free to reach out if you have overlapping interests!

Teaching

• At Denison University (2024–present):
• Analysis of Efficient Algorithms (Spring 2025)
• Data Structures (Fall 2024, Spring 2025)
• Markets, Polls, and Social Networks (Fall 2024)
• At University of Rochester (2021–023):
• Computer Models and Limitations (Summers of 2021, 2022, and 2023)
• Design & Analysis of Efficient Algorithms (Summers of 2022 and 2023)
• At Rochester Institute of Technology (2021–2023):
• Analysis of Algorithms (Summers of 2021, 2022, and 2023)
• Introduction to Cryptography (Summer 2021)

Email:

lastname firstinitial (at) denison (dot) edu

My links:

• DBLP