Ian Ludden

Ian Ludden is an Assistant Professor of Computer Science and Software Engineering at Rose-Hulman Institute of Technology. He holds a PhD in Computer Science (Theory and Algorithms) from the University of Illinois Urbana-Champaign (2023) and a BS in Computer Engineering and Mathematics from Rose-Hulman Institute of Technology (2016). His research focuses on combinatorial optimization, algorithmic game theory, graph theory, and their applications in political redistricting, healthcare analytics, and sports analytics.

Education:

• PhD in Computer Science, University of Illinois Urbana-Champaign, 2023
• Bachelor of Science in Computer Engineering and Mathematics, Rose-Hulman Institute of Technology, 2016

Research Interests:

• Optimization in political redistricting (e.g., fairness metrics, compromise protocols)
• Algorithmic game theory applications in public policy
• Healthcare analytics (e.g., pandemic mortality modeling)
• Graph theory and 3D zoning optimization
• Sports bracket analysis and prediction

Recent Work Trends: Recent publications highlight optimization frameworks for redistricting in Missouri and Arizona, transfer distance midpoints for compromise plans, and aerosol risk models for airplane seating. His work bridges theoretical computer science with practical policy applications.

Awards:

• NSF Graduate Research Fellowship
• Illinois CS Outstanding Teaching Assistant (Lifetime)

Grants & Projects: His NSF-funded research on redistricting protocols and frameworks (e.g., Optimap) demonstrates contributions to both theoretical and applied domains. Collaborations include work with the Missouri League of Women Voters on redistricting impact analysis.

Labs/Teams: Active in computational policy research and optimization methodologies, with GitHub projects focusing on redistricting games and bracket analytics.