About Me

Hello there! My name is Zihao Qi (齐子皓). I am a fourth-year PhD Candidate in Physics at Cornell University. I am fortunate to be advised by Prof. Christopher Earls. Prior to Cornell, I completed my undergraduate degree in Physics at Caltech, where I worked with Prof. Gil Refael and Prof. John Preskill.

I am currently working at the intersection of physics and machine learning. In one direction, I explore how tools in machine learning can be applied to scientific discovery, particularly for problems in condensed matter physics and quantum information. More recently, I have become interested in using physical principles to design machine learning architectures and provide insights into the inner workings of Large Language Models (LLMs). In the past, I have studied non-equilibrium quantum systems, Floquet prethermalization, quantum information dynamics, and various lattice models.

In my spare time, I enjoy playing soccer, card and board games, and hiking around Ithaca.

Contact: zq73 [at] cornell [dot] edu.

09/2025: Our recent work proposes using Fourier Neural Operators as an effective, accurate, and scalable surrogate model for Floquet quantum dynamics. It has now been posted on arXiv – check it out!

08/2025: I have passed the Admission to Candidacy Exam and will be awarded a Master’s degree in Physics.

03/2025: I attended the APS Global Physics Summit in Anaheim, CA and presented our work on the real-space topological invariant for time-quasiperiodic Majoranas. The slides are available here.

11/2024: I have joined the group of Prof. Christopher Earls in the Department of Civil and Environmental Engineering at Cornell!

07/2024: Our recent paper, which defines a real-space topological invariant for time-quasi-periodic superconducting systems (whose energy spectra is dense!), has now been published in PRB as an Editors’ Suggestion.