Xiaodi Wu

xwu's picture
Associate Professor
3247 Atlantic Building

I am an Associate Professor in the Department of Computer Science and Institute for Advanced Computer Studies at the University of Maryland, College Park, and a Fellow at the Joint Center for Quantum Information and Computer Science (QuICS).  I am also an Amazon Visiting Academic working for AWS Braket. I am a recipient of the Sloan Research Fellowship, NSF CAREER, and AFOSR YIP awards.

Before coming to Maryland, I was an Assistant Professor in the Computer and Information Science Department at the University of Oregon from 2015 to 2017. Before that, I was a Postdoctoral Associate at Massachusetts Institute of Technology from 2013 to 2015 (advisor: Aram Harrow, Scott Aaronson).  I was also a Simons Research Fellow at the Simons Institute for the Theory of Computing at Berkeley, for the program of Quantum Hamiltonian Complexity in Spring 2014. I also spent two summers at the Institute for Quantum Computing, University of Waterloo as a student intern (advisor: John Watrous). I received my Ph.D. in theoretical computer science in 2013 (advisor: Yaoyun Shi) from the University of Michigan, Ann Arbor. I received my B.S. degree in mathematics and physics in 2008 from the Academic Talent Program, Tsinghua University.

My research aims to bridge the gap between the theoretical foundation of quantum computing and the limitation of realistic quantum machines. More specifically, I am working on the foundations of practical quantum applications on realistic quantum machines by investigating computational models that capture the native programmability of quantum devices.  I am also building efficient and reliable systems to operate both near-term and long-term quantum devices. Please check my research overview for details of my existing and ongoing projects.

Courses

Publications

2024

2023

2022

2021

K. Hietala, Rand, R., Hung, S. - H., Wu, X., and Hicks, M., A Verified Optimizer for Quantum Circuits, Proceedings of the ACM on Programming Languages, vol. 5, no. POPL, 2021.
X. You and Wu, X., Exponentially Many Local Minima in Quantum Neural Networks, Proceedings of the 38th International Conference on Machine Learning, PMLR, vol. 139, pp. 12144-12155, 2021.
K. Hietala, Li, L., Gaur, A., Green, A., Rand, R., Wu, X., and Hicks, M., Expanding the VOQC Toolkit, in The Second International Workshop on Programming Languages for Quantum Computing (PLanQC 2021), 2021.

2020