Assistant Professor

3247 Atlantic Building

Xiaodi Wu is an assistant professor of computer science in the Joint Center for Quantum Information and Computer Science (QuICS).

As a QuICS Fellow, he will continue his work on the theoretical aspects of quantum information and computation, which includes classical and quantum cryptography, quantum communication, quantum algorithms, and more.

Prior to coming to UMD, Wu was an assistant professor in the Computer and Information Science Department at the University of Oregon.

He was also a postdoctoral associate at MIT and a Simons Research Fellow at the Simons Institute for the Theory of Computing at Berkeley. Additionally, Wu spent two summers at the Institute for Quantum Computing, University of Waterloo as a student intern.

Wu received his doctorate in theoretical computer science from the University of Michigan, Ann Arbor in 2013.

“EasyPQC: Verifying Post-Quantum Cryptography”, ACM CCS 2021, 2021. ,

“A Verified Optimizer for Quantum Circuits”, Proceedings of the ACM on Programming Languages, vol. 5, no. POPL, 2021. ,

“Exponentially Many Local Minima in Quantum Neural Networks”, Proceedings of the 38th International Conference on Machine Learning, PMLR, vol. 139, pp. 12144-12155, 2021. ,

“Expanding the VOQC Toolkit”, in The Second International Workshop on Programming Languages for Quantum Computing (PLanQC 2021), 2021. ,

“Simulating large quantum circuits on a small quantum computer”, Phys. Rev. Lett., vol. 125, no. 150504, 2020. ,

“Quantum algorithms and lower bounds for convex optimization”, Quantum, vol. 4, no. 221, 2020. ,

“Sublinear classical and quantum algorithms for general matrix games”, To appear in the Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI 2021), 2020. ,

“Quantum Wasserstein Generative Adversarial Networks”, Advances in Neural Information Processing Systems (NIPS), vol. 32, 2019. ,

“Quantum query complexity of entropy estimation”, IEEE Transactions on Information Theory, vol. 65, no. 5, pp. 2899-2921, 2019. ,

“Sublinear quantum algorithms for training linear and kernel-based classifiers”, Proceedings of the 36th International Conference on Machine Learning (ICML 2019) PMLR , vol. 97, pp. 3815-3824, 2019. ,

“Limitations of semidefinite programs for separable states and entangled games”, Commun. Math. Phys., vol. 366, no. 2, 2019. ,

“Quantitative Robustness Analysis of Quantum Programs (Extended Version)”, Proc. ACM Program. Lang., vol. 3, no. POPL, p. Article 31, 2018. ,

“Quantum SDP Solvers: Large Speed-ups, Optimality, and Applications to Quantum Learning”, To appear at the 46th International Colloquium on Automata, Languages and Programming (ICALP 2019), 2018. ,