Education

• Ph.D. in Physics from the University of Southern California, 2010
• B.S. in Electrical and Computer Engineering from Cornell University, 2003

Research

Theory: quantum computing and simulation, computational methods

Bio

I joined the burgeoning quantum computing community as a postdoc at USC, where I started working on open quantum system simulations, quantum annealing and more generally adiabatic quantum computing. I subsequently joined the Information Sciences Institute at USC, where I continued my work in benchmarking quantum annealing processors and continuing the search for the still elusive physically relevant example of a quantum speedup. In August 2019, I joined the faculty at the ECE department at UNM, and I am honored to be a member CQuIC and to be a part of the long tradition of quantum information sciences at UNM. My present research interests are on understanding how and whether quantum advantages may manifest themselves in near-term quantum information processing hardware. While quantum algorithms are known to provide computational speedups over their classical counterparts, current devices are limited both in the size and length of computations they can perform. The challenge is now to uncover computational tasks for which these and future near-term devices could provide measurable performance advantages given these constraints. Of particular interest is the question of whether there is ultimately a tradeoff between the noise-sensitivity of an algorithm and its ability of providing a genuine quantum speedup.