ALIREZA BEHTASH

I defended my Ph.D. thesis successfully at the Department of Physics at North Carolina State University in late 2019. My research focus is mostly on semi-classical methods and in general studying mathematical means of understanding path integrals such as Morse theory, Picard-Lefschetz theory, and recently Conley index theory. These beautiful theories all tell us more-or-less something deep about the integration manifold and the topology of field space, being a quite mysterious facet of Feynman's path integrals.
My passion for Morse theory has gotten me involved with machine learning and data-driven AI, which happen to be putting the very same methods of my research in use to unravel the topology of datasets towards the ultimate goal of learning from it to make smart decisions. Together with Behnam Kia, I co-founded our legal tech company Stacks which focuses on extracting actionable insights from patents for predicting infringement and eligibility using the latest advances in deep learning. I have also experience developing AI systems for 3D image reconstruction of landscapes and topography and research tools based on manifold learning.