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.

Resources

• Quantum Information & Semidefinite Programming. Jamie Sikora. Alice Zheng, editor.

Preprints and Publications (see also )

1. Quantum Online Learning. Alice Zheng. PhD thesis, Virginia Tech, 2026.
2. Autonomous Hamiltonian certification and changepoint detection. Steven T. Flammia, Dmitrii Khitrin, Muzhou Ma, Jamie Sikora, Yu Tong, Alice Zheng. 2026. [arXiv:2603.26655|Talk]
3. Randomness compression in communication networks. Yukari Uchibori, Alice Zheng, Anurag Anshu, Jamie Sikora. 2026. [arXiv:2603.13197]
4. 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]
5. 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]
6. Divergence inequalities with applications in ergodic theory. Ian George, Alice Zheng, Akshay Bansal. 2024. [arXiv:2411.17241] Parts also appeared in:
   7. 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]
   8. 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.