Hi, I’m Jessie! (Pronouns: she/her; pronounced: Jeh-see Fin-uh-car-oh). Feel free to call me Jessie Fin if it’s easier.
I am a PhD candidate in the CS Theory group at CU Boulder, working with Dr. Rafael Frongillo (and unofficially with Dr. Bo Waggoner as well). In general, my research interests intersect Theoretical Machine Learning, Algorithmic Game Theory, and Computational Economics. In particular, I am interested in decisionmaking in the midst of uncertainty, how the questions we ask affect what we learn [from people, machine learning algorithms], and how this uncertainty affects people. I typically study these questions through the lens of property elicitation. I was named as a 2019 National Science Foundation Graduate Research Fellow.
I am hoping to start a postdoc in approx. fall 2022.
I am fairly involved with the group Mechanism Design for Social Good. From March 2020-August 2021, I was a working group co-organizer for the Discrimination and Bias working group with Faidra Monachou, Manish Raghavan and Duncan McElfresh. I currently am a Community Engagement co-lead alongside Logan Stapleton, and participate in two working groups.
Before starting graduate school, I didn’t feel like I knew anyone who had gotten a research-based graduate degree, and as a result, had no idea what I was getting into. For example, I didn’t know that many PhD programs are fully-funded, I had no idea how to search for programs, etc. In fact, I really didn’t even know what questions to ask about programs. If you feel like you’re in the same boat, I would be more than happy to chat and share my experience, or try to connect you to someone in graduate school with a similar background. At some point, I’ll turn some FAQs over the years into a blog post.
At one point, I was interviewed for our department get-to-know-you, and got to sit down with my good friend Izzy for a nice chat. Get to know some more folks at Boulder CS through other Neural Network features.
Thank you to the academicpages template, who let me fork their website template.