During Michaelmas Term, OxTalks will be moving to a new platform (full details are available on the Staff Gateway).
For now, continue using the current page and event submission process (freeze period dates to be advised).
If you have any questions, please contact halo@digital.ox.ac.uk
Abstract:
Progress in mathematics often involves observing a large number of well distributed examples, postulating conjectures and rigorously proving them. In a physicist’s language, this is a “top-down” approach and many spectacular results in both these disciplines have been discovered through this process. Artificially intelligent machines are now able to both support and in limited instances outperform conventional mathematics. In this talk, I will give an overview of this burgeoning field and our ongoing research by focusing on two case studies. I will present our AI guided conjecture generation framework which has been used to discover new results in multiple domains of math. I will also show how techniques such as supervised learning and symbolic regression can be utilized for this purpose in the context of string geometry.
Bio:
Daattavya’s research interests are at the intersection of mathematical physics and machine intelligence. His main focus is on developing tools for the discovery of new mathematics and analyzing their structure. Other ongoing work includes studying interesting geometries that arise in string theory and mathematical physics, often through the application of machine learning techniques. Before joining Cambridge, Daattavya graduated with an MSc. in Mathematical and Theoretical Physics from the University of Oxford where his dissertation was on Calabi-Yau Manifolds and Mirror Symmetry.