Kerry Zhou

A.K.A Kairui Zhou
Academic Focus Quantum Computing & Machine Learning
Undergraduate Student @ UChicago
Chicago, IL Updated: Nov 19, 2025
01 // Identity

Undergraduate Researcher at the University of Chicago. Synthesizing Quantum Computing, Machine Learning, and Physics to probe the fundamental limits of computation.

Focusing on the intersection of topological order and neural representations.

Fig 1.1: Lorenz Attractor
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01 // About

Who I Am

I am a researcher and developer with a passion for bridging the gap between abstract theory and practical application. My background spans computer science, physics, and philosophy.

My work is grounded in the belief that the rigorous structures of mathematics and the intuitive leaps of the humanities are not opposing forces, but complementary lenses for understanding reality.

What I'm Doing

Currently, I am focused on completing my undergraduate studies at UChicago while conducting research in quantum error correction. I am also exploring new ways to visualize complex data structures.

Personal

When I'm not coding or deriving equations, I enjoy exploring mid-century modern architecture, reading speculative fiction, and experimenting with analog photography.

  1. Born in Beijing, educated in New York, currently researching in Chicago.
  2. I approach computer science not just as engineering, but as a medium for philosophical inquiry.
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02 // Research

Research Identity

My research interests lie at the intersection of quantum computing and machine learning. I am particularly interested in how topological order can be used to protect quantum information and how neural networks can be used to optimize quantum circuits.

Background

I have worked with several research groups at UChicago and beyond, contributing to projects in quantum error correction, neural architecture search, and topological data analysis.

[SELECTED WORKS DATABASE]

01

Topological Codes under Non-Uniform Noise

Physical Review B QEC, Surface Codes, Noise Bias

// Threshold improved by ~10x with tailored lattice.

2024
02

Differentiable NAS for Edge Devices

NeurIPS Workshop AutoML, NAS, Edge AI

// Reduced search time from 2000h to 24h.

2023
03

Mapper Algorithm for High-Dimensional Data

Undergraduate Research Symposium TDA, Topology, Data Vis

// Best Poster Award

2023
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Fig 1.2: Wave Interference