Research

I'm an AI researcher with expertise in simulation, game theory, and machine learning for analyzing complex phenomena across domains such as finance and healthcare. I have hands-on experience developing models and conducting analysis to extract actionable insights and support data-informed decision-making. In addition to technical work, I've led projects involving method design, mentoring junior researchers and communicating findings to diverse audiences.

I am seeking an industry role where I can apply my technical background in AI to contribute to data-driven innovation. I'm particularly interested in positions that blend technical depth with strategic thinking such as data science, applied research, or AI strategy.

About Me

Hello! I am a recent graduate of the University of Michigan where I earned my PhD in computer science & engineering. While at Michigan, I was advised by Michael Wellman as a member of the Strategic Reasoning Group.

My dissertation research lies at the intersection of computer science and economics. I develop computational methods using simulation of agent-based models and empirical game-theoretic analysis to uncover key factors influencing the strategic decision-making of financial institutions and other financial participants. Additionally, I analyze simulation data to understand the consequences of decisions . My work has led to findings such as a greater understanding of the importance of asset recovery rates in the strategic cancellation of cycles of debt and identifying the potential for strategic restrictions of real-time payments to lead to a suboptimal outcome for all.

Prior to graduate school, I applied data analysis and machine learning methods to predict emergency room visits of cancer patients and to perform event detection from social media data. As an undergraduate student, I attended the University of Massachusetts Amherst from which I obtained degrees in computer science and economics, as well as a minor in Chinese. My honors thesis, advised by Brendan O'Connor, applied time series forcasting to Google trends data for predicting state unemployment rates.

Research Interests

AI: computational economics, multi-agent systems, empirical game theory, applications of machine learning

Finance: real-time payments, fraud, systemic risk

Publications

Conference Publications

1. Fraud Risk Mitigation in Real-Time Payments: A Strategic Agent-Based Analysis
   Katherine Mayo, Nicholas Grabill, and Michael P. Wellman
   IJCAI '24: 33rd International Joint Conference on Artifical Intelligence, August 2024
   Acceptance rate: 14%; 12 min presentation (alloted to 16% of main track papers)
   [paper][slides][poster]


2. A Strategic Analysis of Portfolio Compression
   Katherine Mayo and Michael P. Wellman
   ICAIF '21: 2nd ACM International Conference on AI in Finance, November 2021
   [paper][slides]
   Previous version presented as a poster at AAMAS 2021: [paper][poster]


3. An Agent-Based Model of Strategic Adoption of Real-Time Payments
   Katherine Mayo, Shaily Fozdar, Michael P. Wellman
   ICAIF '21: 2nd ACM International Conference on AI in Finance, November 2021
   [paper][slides]

Journal Publications

1. Navigating in a Space of Game Views
   Michael P. Wellman and Katherine Mayo
   Journal of Autonomous Agents and Multi-Agent Systems, July 2024
   [paper]


2. Machine Learning Model of Emergency Department Use for Patients Undergoing Treatment for Head and Neck Cancer Using Comprehensive Multifactor Electronic Health Records
   Michelle Mierzwa MD, Charles Mayo PhD, Pratyusha Yalamanchi MD, Joseph Evans MD, Francis Worden MD, Richard Medlin MD, Matt Schipper PhD, Caitlin Schonewolf MD, Jennifer Shah MD, Matthew Spector MD, Paul Swiecicki MD, Katherine Mayo MS, and Keith Casper MD
   JCO Clinical Cancer Informatics, January 2023
   [paper]

Workshop Papers

1. Flagging Payments for Fraud Detection: A Strategic Agent-Based Model
   Katherine Mayo, Shaily Fozdar, Michael P. Wellman
   MUFin '23: 3rd International Workshop on Modeling Uncertainty in the Financial World (@ 37th AAAI Conference on Artificial Intelligence), February 2023
   [paper][slides]

Coursework

Advanced Data Mining, Electronic Commerce (now called Incentives and Strategic Behavior in Computational Systems), International Finance, Reinforcement Learning Theory, Advanced Artificial Intelligence