Link to Talk Video: https://mediaspace.illinois.edu/media/t/1_vpj6zfbr
Abstract: Algebraic geometry is the study of zero sets of polynomial equations. Representation theory is the study of symmetries of geometric objects, or, more precisely, the systematic exploitation of symmetry in linear algebra. I will explain how these two areas of mathematics are useful for numerous questions in theoretical computer science, including quantum information theory, L. Valiant's algebraic version of P v. NP, and the complexity of matrix multiplication.
Bio: Joseph (JM) Landsberg received a special joint Bachelorʼs and Masterʼs degree from Brown University in 1986 and a Ph.D. in Mathematics from Duke University in 1990. He is currently a professor in the mathematics department at Texas A&M University.
Dr. Landsbergʼs research interests are broad, with research in differential geometry, algebraic geometry, and representation theory. The main focus of his current work is theoretical computer science, especially algebraic complexity theory, in particular the complexity of matrix multiplication.
Dr. Landsberg served as a Clay Senior Scholar for Tensor Methods and Emerging Applications to the Physical and Data Sciences at IPAM (spring 2021), holds a U. Toulouse visiting endowed professorship "chaire dʼexcellence" (6 months, 2021-3). Other distinctions include a Stanford University Exceptional Teacher Tribute (2018), a CBMS lecture series (summer 2017), AMS fellow (class of 2017), UC Berkeley Chancellorʼs Professor (fall 2014), and an NSF postdoctoral fellowship (1990-93). He is the author of over 75 research articles, the books "Geometry and Complexity Theory" (Cambridge 2017), "Tensors: Geometry and Applications" (AMS 2011), and "Cartan for beginners" with T. Ivey (AMS 2003, Second Edition 2017), two research monographs, and is finishing a graduate textbook on "Quantum Computing and Quantum Information Theory" (draft available upon request).
Part of the Illinois Computer Science Speakers Series. Faculty Host: Michael Forbes
