February 18, 2022
12:00 pm to 1:00 pm
Event sponsored by:
Biostatistics and Bioinformatics
Josh Alman, PhD
Abstract: Matrix multiplication is one of the most basic algebraic operations. Since Strassen's surprising breakthrough algorithm from 1969, which showed that matrices can be multiplied faster than the most straightforward algorithm, algorithmic problems from nearly every scientific domain have been sped up by clever reductions to matrix multiplication. It is popularly conjectured that two n × n matrices can be multiplied in roughly O(n^2) time, but we don't yet have the algorithmic techniques needed to achieve this. Speaker: Josh Alman, PhD Assistant Professor of Computer Science Columbia University Dr. Alan was previously a Michael O. Rabin postdoctoral fellow in theoretical computer science at Harvard, and he earned his Ph.D. in computer science from MIT in 2019. He works in algorithm design and complexity theory, and he's particularly interested in developing algebraic tools like algorithms for matrix multiplication and Fourier transforms, and applying them to a wide variety of computational problems. His awards include the European Association of TCS Distinguished Dissertation Award, the George M. Sprowls Award for outstanding Ph.D. theses in computer science at MIT, and best student paper awards at the 2019 Computational Complexity Conference (CCC) and the 2019 Symposium on Foundations of Computer Science (FOCS).