Adjunct Associate Professor

3100J Atlantic Building

(301) 314-1850

Yi-Kai Liu is an Adjunct Associate Professor in the University of Maryland Institute for Advanced Computer Studies (UMIACS) and a staff scientist in the Applied and Computational Mathematics Division at the National Institutes of Standards and Technology (NIST). Liu's research centers on quantum computation, in particular, quantum algorithms and complexity, quantum state tomography and cryptography. He also works on related topics in compressed sensing and machine learning. He received his doctorate in computer science from the University of California, San Diego in 2007.

“Phase Retrieval Without Small-Ball Probability Assumptions”, IEEE Transactions on Information Theory , vol. 64, no. 1, pp. 485-500, 2018. ,

“Phase retrieval using unitary 2-designs”, in SampTA 2017, 2017. ,

“Optimized tomography of continuous variable systems using excitation counting”, Physical Review A, vol. 94, p. 052327, 2016. ,

“Phase Retrieval Without Small-Ball Probability Assumptions: Stability and Uniqueness”, SampTA, pp. 411-414, 2015. ,

“Privacy Amplification in the Isolated Qubits Model”, Eurocrypt, pp. 785-814, 2014. ,

“Single-shot security for one-time memories in the isolated qubits model”, CRYPTO, vol. Part II, pp. 19-36, 2014. ,

“Testing quantum expanders is co-QMA-complete”, Physical Review A, vol. 87, no. 4, 2013. ,

“Multilingual Summarization: Dimensionality Reduction and a Step Towards Optimal Term Coverage”, MultiLing (Workshop on Multilingual Multi-document Summarization), pp. 55-63, 2013. ,

“Building one-time memories from isolated qubits”, Innovations in Theoretical Computer Science (ITCS), pp. 269-286, 2013. ,

“Quantum Tomography via Compressed Sensing: Error Bounds, Sample Complexity, and Efficient Estimators
”, New Journal of Physics, vol. 14, no. 9, p. 095022, 2012. ,

“A Spectral Algorithm for Latent Dirichlet Allocation”, Algorithmica, pp. 193-214, 2012. ,

“Direct Fidelity Estimation from Few Pauli Measurements”, Physical Review Letters, vol. 106, no. 23, 2011. ,

“Universal low-rank matrix recovery from Pauli measurements”, Advances in Neural Information Processing Systems (NIPS), pp. 1638-1646, 2011. ,