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Jesse S
- Research Program Mentor
PhD candidate at University of Chicago
Expertise
Theoretical Computer Science, Cryptography, Mathematics, and Logic
Bio
I am a PhD student at the University of Chicago doing research in theoretical computer science. I have been doing research in this area since high school. Over these 10 years of research, I have had the privilege to be mentored by 6 different professors who have helped to guide my research and career and travel globally to conferences and workshops. At a fundamental level, I am most fascinated by basic theoretical questions in the field (such as P vs NP) and by the study of mathematical proofs. I have also done extensive research in theoretical cryptography among other sub-fields. On a personal level, I greatly enjoy games and worked briefly as a board game designer. Sometimes this overlaps directly with my research (such as by studying the computational complexity of games or using games as a way to study interactive algorithms), but I admit that often it is just because I love a good puzzle or competitive game. As a person who loved math and logic, but struggled greatly in early education due to my dyslexia, I have since gained a life-long love of helping others work through difficult material and look forward to working with students on projects of mutual interest.Project ideas
The Complexity of Problems and Mathematical Limits of Computers
There are an endless number of fascinating and practical problems that we hope to solve with the help of computers. While some of these problems have efficient algorithms, such an algorithm is far from guaranteed to exist. During this project, we will focus on a problem of interest to you (i.e. the student). Rather then simply hoping this problem can be solved efficiently and diving straight into programming, we will study the mathematical structure the problem and prove limitations on our ability to write algorithms to solve it. Not only does this give us deep insight into the structure of problem, but it is of vast practical interest, as such results tell us what is and is not possible. One major benefit of this is that if anyone later tries to use computers to solve this problem, they can avoid seeking overly ambitious algorithms that may in fact be entirely non-existent, saving vast time and effort due to the insight granted them by your theoretical analysis of the problem. For a concrete example of such a project, I did a project along these lines myself as a high school student. The project was awarded 1st Prize at the Massachusetts State Science and Engineering Fair and the final paper can be found here: https://arxiv.org/abs/1110.1052