Graduate Student (2015-2021)

3100M Atlantic Building

(301) 314-1839

Shih-Han was a doctoral student in computer science from 2015 to 2021. He received his PhD in Computer Science from the University of Maryland. His adviser was Andrew Childs. Shih-Han will be a postdoc at UT Austin.

“Quantum algorithm for estimating volumes of convex bodies”, ACM Transactions on Quantum Computing, 2023. ,

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

“Proving Quantum Programs Correct”, Schloss Dagstuhl, 2021. ,

“Quantum query complexity with matrix-vector products”, Proceedings of the 48th International Colloquium on Automata, Languages, and Programming (ICALP 2021), Leibniz International Proceedings in Informatics, vol. 198, pp. 55:1-55:19, 2021. ,

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

“Non-interactive classical verification of quantum computation”, Theory of Cryptography Conference (TCC), vol. Lecture Notes in Computer Science 12552, pp. 153-180, 2020. ,

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

“Quantum algorithm for multivariate polynomial interpolation”, Proceedings of The Royal Society A, vol. 474, no. 2209, 2018. ,

“Optimal quantum algorithm for polynomial interpolation”, 43rd International Colloquium on Automata, Languages, and Programming (ICALP 2016), vol. 55, p. 16:1--16:13, 2016. ,