I'm a theoretical physicist. I work at the University of Southern California as a Postdoctoral Scholar - Teaching Fellow with a secondary appointment at the Information Sciences Institute as a Visiting Researcher. I have experience in theoretical physics (condensed matter physics), machine learning, and decentralized systems. Prior to this appointment, for two years I worked as a Lead Research Scientist for an AI&Blockchain company, working on novel consensus protocols, blockchain security, and decentralized machine learning. My current research interests focus on applications of machine learning in various areas of physics (e.g., in materials science or in modeling open quantum systems) and vice-versa (applications of physics in machine learning research).

Applications of machine learning in physics and material science. Applications of physics in machine learning research.

Previously: At Fetch.AI, research on novel consensus protocols, blockchain security, and machine learning applications in decentralized systems. At Jagiellonian University, research on the approximation methods for strongly-correlated quantum systems.

Physics Department, Dornsife, USC
Information Sciences Institute, USC