OxTalks will soon move to the new Halo platform and will become 'Oxford Events.' There will be a need for an OxTalks freeze. This was previously planned for Friday 14th November – a new date will be shared as soon as it is available (full details will be available on the Staff Gateway).
In the meantime, the OxTalks site will remain active and events will continue to be published.
If staff have any questions about the Oxford Events launch, 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.
