Alice Zheng

I am a Ph.D. candidate in Computer Science at Virginia Tech supervised by Jamie Sikora.

My current areas of research include:

• Quantum information theory,
• Computational learning theory (esp. Online learning),
• Semidefinite programming,
• Quantum computing.

Preprints and Publications (see also )

1. Autonomous Hamiltonian certification and changepoint detection. Steven T. Flammia, Dmitrii Khitrin, Muzhou Ma, Jamie Sikora, Yu Tong, Alice Zheng. 2026. [arXiv:2603.26655]
2. Randomness compression in communication networks. Yukari Uchibori, Alice Zheng, Anurag Anshu, Jamie Sikora. 2026. [arXiv:2603.13197]
3. Local strategies are pretty good at computing Boolean properties of quantum sequences. Tathagata Gupta, Ankith Mohan, Shayeef Murshid, Vincent Russo, Jamie Sikora, Alice Zheng. 2026. [arXiv:2603.05452]
4. Online learning of a panoply of quantum objects. Akshay Bansal, Ian George, Soumik Ghosh, Jamie Sikora, Alice Zheng. Quantum Machine Intelligence, 7(2):78, Springer, 2025. [arXiv:2406.04245|Talk|Poster]
5. Divergence inequalities with applications in ergodic theory. Ian George, Alice Zheng, Akshay Bansal. 2024. [arXiv:2411.17241] Parts also appeared in:
   6. The rate of information destruction and f-divergence Pinsker inequalities. Ian George, Alice Zheng, Akshay Bansal. In 2025 IEEE International Symposium on Information Theory (ISIT), pages 1–6, IEEE, 2025. [Talk]
   7. Divergence inequalities from multivariate Taylor's theorem. Ian George, Alice Zheng, Akshay Bansal. In 2024 IEEE Information Theory Workshop (ITW), pages 561–566, IEEE, 2024.