Hi!

I’m Ashwin Kumar, a PhD student at Washington University in St. Louis, advised by Prof. William Yeoh. I’m interested in the intersection of AI and fairness, and how we can use AI to improve fairness and transparency in various people-facing problems.

Over the years, I’ve worked on a variety of problems in AI, including planning, explainability, and resource allocation. I’ve also worked on a variety of problems in fairness, including fairness in resource allocation, fairness in machine learning, and fairness in AI-assisted decision making. My current research focuses on Temporal Resource Allocation Problems, where resources and agents may re-enter the market over time. Ensuring equity in TRAPs is a challenging problem, especially when trying to balance efficiency and fairness. I’ve worked on improving fairness in ridesharing systems by giving incentives to drivers to pick passengers from less-served areas in metro cities. I’m also working on finding smarter ways to include fairness in the matching process of TRAPs using machine learning and statistics. Through my research, I plan to bridge the gap between algorithmic fairness techniques and efficient resource allocation.

When I’m not thinking about fairness, I work on explainability in AI-assisted decision making. Alongside Stylianos Vasileiou, a fellow PhD student at Washington University, I’ve been working on Human-Aware AI problems, where we try to understand how humans interact with AI systems, and how we can improve the quality of these interactions. Using logic-based techniques, we’ve designed methods to deliver explanations of agent behaviour to users using visualization techniques. We’ve also worked on improving the interaction quality of human-AI teaming systems through a dialogue-based argumentation framework, that allows users to engage in a conversation with AI agents to resolve disagreements. This is a work in progress, and there is more to come!

You can find more information about my research here.

When I’m not working, I can be found reading a book or biking in Forest Park. I also enjoy playing the piano, when I can get my hands on one. One of my favorite things to do is to travel, and I’ve been fortunate enough to visit many places around the world. I’m always looking for new things to do, new books to read, and interesting music to listen to, so if you have any recommendations, please let me know!

Side note: A language model helped me write parts of this. They are getting surprisingly good, but I believe the next big step in AI will come from reinforcement learning. I’m excited to see what the future holds!