Holographic deep thermalization: theory and experimentation
Bingzhi Zhang, Peng Xu, Xiaohui Chen, Quntao Zhuang. (2025). Holographic deep thermalization: theory and experimentation.
CV
Education
- PhD in Statistics, University of Illinois at Urbana-Champaign, Since 2020
- M.A. in Statistics, Columbia University, 2018
- M.S. in Financial Engineering, University of Illinois at Urbana-Champaign, 2016
- B.S. in Mathematics and Statistics, University of Illinois at Urbana-Champaign, 2015
- B.S. in Finance, University of Illinois at Urbana-Champaign, 2015
Awards and Honors
- 2023 Doctoral Student Teaching Award
Work Experiences
- Visiting Student. Department of Mathematics, University of Southern California. 2024.
- Advised by Prof. Xiaohui Chen and Prof. Quntao Zhuang.
- Research Associate. Department of Statistics, Columbia University. 2019.
- Advised by Prof. Bodhisattva Sen and Dr. Margaret Holen on seperate projects.
Publications
Generative quantum machine learning via denoising diffusion probabilistic models
Bingzhi Zhang, Peng Xu, Xiaohui Chen, Quntao Zhuang. (2024). Generative Quantum Machine Learning via Denoising Diffusion Probabilistic Models. Phys. Rev. Lett., 132, 100602. doi:10.1103/PhysRevLett.132.100602
Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions
Wenda Zhou, Shuaiwen Wang, Peng Xu, Haiho Lu, Arian Maleki, Vahab Mirrokni. (2019). Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions. 2019 INFORMS Workshop on Data Mining and Decision Analytics.
orthoDr: Semiparametric Dimension Reduction via Orthogonality Constrained Optimization
Ruoqing Zhu, Jiyang Zhang, Ruilin Zhao, Peng Xu, Wenzhuo Zhou, Xin Zhang. (2019). orthoDr: Semiparametric Dimension Reduction via Orthogonality Constrained Optimization. The R Journal, 11(2), 24–37.
Talks
Generative quantum machine learning via denoising diffusion probabilistic models
Talk at 2024 APS March Meeting, Minneapolis, MN