Haimeng Zhao

Haimeng Zhao

PhD Student in Physics

Caltech

Welcome!

Hello ~ I’m Haimeng Zhao /haɪ məŋ dʒaʊ/ (赵海萌), a PhD student in Physics at Caltech, advised by John Preskill and Hsin-Yuan Huang. I also work as a Student Researcher at Google Quantum AI. I’m deeply fascinated by how the universe works and how we can possibly understand it. So I started working in the intersection of Physics and Artificial Intelligence.

In particular, I’m interested in the foundation, applications and interplay of quantum many-body physics, information theory and high-dimensional statistics. I aspire to understand scientific discovery as a quantum process and exploit its quantum nature to facilitate discoveries.

Before Caltech, I received my Bachelor’s degree in Mathematics and Physics with Honours from Tsinghua University. I was an undergrad research fellow in John Preskill’s group at IQIM, Caltech and an exchange student in Giuseppe Carleo’s group at EPFL in Switzerland. At Tsinghua, I worked on quantum information in Dong-Ling Deng’s group at IIIS and AI for Astronomy with Wei Zhu.

Interests

  • Quantum Many-body Physics
  • Quantum Information, Complexity & Learning Theory
  • AI for Science, especially Physics & Astrophysics

Education

  • PhD Student in Physics

    Caltech

  • BS in Mathematics and Physics, 2024

    Tsinghua University

  • Outstanding Graduate, 2020

    Shanghai High School

Publications

(2025). Entanglement-induced provable and robust quantum learning advantages. npj Quantum Information 11, 127.

PDF Code arXiv Talk

(2024). Learning quantum states and unitaries of bounded gate complexity. PRX Quantum, 5(4), 040306. Featured on the cover and in the International Year of Quantum Collection.

PDF Code arXiv Talk

(2024). Empirical Sample Complexity of Neural Network Mixed State Reconstruction. Quantum 8, 1358.

PDF Code arXiv

(2023). Non-IID Quantum Federated Learning with One-shot Communication Complexity. Quantum Machine Intelligence, 5(1), 3.

PDF Code arXiv Conf Talk

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