Noah Golowich completed a joint AB/SM degree in Mathematics and Computer Science at Harvard University and will pursue his PhD at Massachusetts Institution of Technology.
Noah is developing a greater understanding of the theoretical reasons behind the success of today’s deep learning methods. These methods use neural networks to perform tasks that could revolutionize technologies as seemingly unrelated as language translation and self-driving cars.
Noah has also applied neural networks to learn algorithms for social choice that maximize social welfare while respecting the incentives of individuals who provide inputs to the algorithms. He has further contributed to the theory of communication complexity, which involves structuring communication between computers in the most efficient way to solve a given problem. Some of his work in communication complexity is motivated by cryptography – generating efficient algorithms for two parties to communicate securely and efficiently.
In 2015 Noah won the First Place Medal of Distinction for Basic Research in the Intel Science Talent Search, the nation’s oldest and most prestigious pre-college science and mathematics competition. His honors also include a Goldwater Scholarship for undergraduate students who intend to pursue careers in science, mathematics, or engineering.
Noah is a New Jersey native who grew up in Lexington, Massachusetts. He was a member of the Harvard club tennis team and plays piano.