Won Joon Yun

Quantum Computer Architecture · Fault Tolerance · Compilation

I am a Ph.D. student in Electrical and Computer Engineering at The University of Texas at Austin, where I work with Prof. Jonathan Baker in the Baker Group.

My research sits at the boundary of quantum computer architecture and compilation. I study how to improve the reliability of fault-tolerant quantum computation across different hardware platforms, including distributed quantum computers, neutral-atom systems, and devices with biased noise.

Research

  • Per-qubit Clifford frame selection for spatially non-uniform biased noise
  • Placement, routing, and atom transport in neutral-atom architectures
  • Teleportation-aware scheduling for distributed quantum computers

Projects

Architecture & Systems

Chameleon

The Baker Group · 2026

Calibration-aware optimization of per-qubit Clifford frames for spatially non-uniform biased noise.

Decoder-free frame selection for surface, color, and bivariate-bicycle codes.

IRIS

UT Austin ACES · EuroSys 2027 (accepted)

Teleportation-aware instruction scheduling for distributed quantum computers with limited EPR-pair capacity.

Lower effective teleportation count and program-schedule latency under EPR-capacity constraints.

Open Source & Research Software

Bloqade Lanes Contributions

QuEra Computing · Open source

Lookahead routing and multi-candidate placement strategies for QuEra's neutral-atom compiler stack.

Merged lookahead routing; a separate multi-candidate placement proposal remains under review.

Neutral-Atom FTQC Simulator

Independent research software

Simulation of neutral-atom schedules, physical-noise artifacts, and logical error rates.

Selected Publications

  1. Computationally Efficient Optimization of Per-Qubit Clifford Deformation for Non-uniform Biased Noise

    W. J. Yun, A. Nemec, and J. M. Baker

    arXiv:2608.17870; Under review, 2026.

    PaperCode

  2. IRIS: A Compiler for Distributed Quantum Systems

    W. J. Yun, D. Nag, S. Ballabh, J. Zhao, E. Kaur, and P. Das

    EuroSys 2027, accepted; to appear.

    PaperCode

  3. Quantum Multi-Agent Meta Reinforcement Learning

    W. J. Yun, J. Park, and J. Kim

    Proceedings of the AAAI Conference on Artificial Intelligence, 2023.

    PaperCode

  4. SlimFL: Federated Learning with Superposition Coding over Slimmable Neural Networks

    W. J. Yun, Y. Kwak, H. Baek, S. Jung, M. Ji, M. Bennis, J. Park, and J. Kim

    IEEE/ACM Transactions on Networking, vol. 31, no. 6, pp. 2499–2514, 2023.

    Paper

Earlier work in quantum machine learning, federated learning, and networking → Google Scholar

Education & Experience

Education

  • 2024–Present

    The University of Texas at Austin

    Ph.D. Student, Electrical and Computer Engineering

    Cockrell School of Engineering Multiyear Fellowship.

  • 2021–2023

    Korea University

    M.S. Candidate, Electrical and Computer Engineering

    Excellent Research Performance Graduate Student Award, College of Engineering.

  • 2015–2021

    Korea University

    B.E., Electronic Engineering

    Outstanding Achievement Award for Graduation Project.

Research Experience

  • 2026–Present

    The Baker Group, UT Austin

    Graduate Research Assistant · Advisor: Prof. Jonathan Baker

    Calibration-aware Clifford frame selection and logical-error suppression under spatially non-uniform biased noise.

  • 2024–2026

    ACES Laboratory, UT Austin

    Graduate Research Assistant · Advisor: Prof. Poulami Das

    Distributed quantum-computer architecture, teleportation-aware instruction scheduling, and EPR-constrained interconnects.

  • 2023

    C³ Laboratory, University of Utah

    Visiting Researcher · Advisor: Prof. Mingyue Ji

    Machine-learning theory, caching systems, and Lyapunov stability bounds.

  • 2020–2023

    AI and Mobility Laboratory, Korea University

    Researcher · Advisor: Prof. Joongheon Kim

    Quantum multi-agent reinforcement learning for networking and distributed decision-making.

Industry Experience

  • 2023–2024

    MetaFarmers

    Lead Software Engineer

    Vision AI, sim-to-real reinforcement learning, robotic trajectory planning, and systems infrastructure.

  • Jun–Aug 2022

    Advanced Research, Cipherome Inc.

    Visiting Scholar · Advisor: Dr. Samuel Kim

    Developed and validated a federated-learning framework for medical AI using NVFlare and AWS.

  • 2019–2020

    NScreen

    Full Stack Software Engineer

    Learning-management, grading, statistics, automation, and backend systems.

Honors & Service

Honors and Awards

  • 2024

    Cockrell School of Engineering Multiyear Fellowship

    The University of Texas at Austin

  • 2023

    Excellent Research Performance Graduate Student Award

    College of Engineering, Korea University

  • 2023

    ICAT Best Paper Award

    International Conference on Advanced Technologies

  • 2023

    AAAI Student Abstract Top 25 Finalist

    AAAI Conference on Artificial Intelligence

  • 2022

    Spotlight Oral Presentation

    ICML Workshop on Dynamic Neural Networks

Academic Service

  • 2025–2026

    Artifact Evaluation Committee

    MICRO 2025; EuroSys, HPCA, and ISCA 2026

  • Ongoing

    Reviewer

    IEEE TQC, JSAC, TWC, TCOM, TVT, and Neurocomputing