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I am currently a quantum applications engineer at IonQ, where I work on developing near-term quantum algorithms for real world use cases.
Previously I was a postdoctoral researcher at the Center for Theory of Quantum Matter and Department of Physics at the University of Colorado Boulder.
My graduate studies were completed at the University of California-Santa Barbara with Prof. Leon Balents.
Research Interests:
My current work centers around developing , testing and running quantum algorithm for real world applications. This involves studying and optimizing many different near-term quantum algorithms developed for quantum machine learning, quantum optimization and quantum chemistry applications, and implementing these algorithms on IonQ's trapped ion quantum computer.
My past research has focused on exploring numerical approaches to studying complex many-body quantum systems. This often involves developing novel numerical techniques based on physical insights to study specific problems which arise in these many-body systems. Recent work has focused on understanding the growth of entanglement and quantum state complexity in wave functions which evolve under local quantum circuits, as well as developing methods to simulate special classes of quantum circuits classically, and studying thermalization and discrete time dynamics in the presence of symmetry. Other areas of interest include harnessing machine learning algorithms to study quantum wave functions and applying tensor network methods to simulate circuit dynamics.
Past work has involved combining analytic insights with large scale numerical simulations to study experimentally relevant strongly correlated quantum materials. Specific examples include using variational Monte Carlo methods to study spin-orbit coupled quantum spin liquids and combining analytically exact calculations with DMRG to study magnetism in oxide heterostructure materials.