I'm currently studying Computer Science and Applied Math at Cornell University, with the hopes of breaking into the field of quantitative finance or machine learning development.I have always been interested in the "unsolvable": playing perfect chess games, developing optimal basketball offenses, or finding the fastest routes between 100 cities. By chasing answers to fundamentally unsolvable problems, we continually find something new such as novel chess position evaluations, unconventional player metrics, and surprising transport heuristics. This is what draws me to the fields of quantitative finance and machine learning development. Each day presents a new and exciting challenge to tackle, from optimizing server operations at a High-Frequency Trading firm to experimenting with new, innovative machine-learning models based on elements of human psychology or primate brain structure.Because of these interests, I've decided to pursue a degree in Computer Science with minors in Applied Math and Statistics. For me, a degree in Computer Science was a no-brainer since I love programming and building cool programs, but I also feel Applied Math and Statistics will give me more building blocks to experiment and learn within the fields of quantitative finance and machine learning research and development. In my free time, I like watching old horror movies such as The Shining and The House that Jack Built, listening to 90s Hip-Hop (Nas is the best), and reading books by Michael Lewis; my favorite books by him are Flash Boys and Money Ball