Daniel Kane has diverse research interests within mathematics and theoretical computer science, particularly in the areas of combinatorics, number theory, derandomization and Boolean functions. He has published papers on topics such as algorithms for Big Data, results on writing numbers as sums of primes, and the structure of polynomials in many variables. He has won best paper or best student paper awards in the Conference on Computational Complexity, Foundations of Computer Science and the Symposium on Principles of Database Systems. He also has experience as an instructor at Stanford University and Harvard University, and has helped train students for various mathematics contests, including as an instructor in the United States Math Olympiad Summer Program. As an Assistant Professor at UC San Diego, he will split his teaching responsibilities between the departments of computer science and mathematics. He expects to teach classes on discrete mathematics, combinatorics, algorithms and number theory, and to teach graduate courses on topics in these areas in addition to various areas of complexity theory, such as the analysis of Boolean functions.
- Pseudorandomness, Spring 2017. Visiting Scientist.