Tak Hur.

Quantum + AI

Tak Hur

I am a postdoctoral researcher at the University of Waterloo. I explore how quantum technologies and AI can come together to make real impact.

I completed my PhD in Statistics and Data Science at Yonsei University in 2026. My work spans quantum machine learning, quantum error correction, and neural quantum states, with an interest in both theory and practical algorithms.

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Publications

* first author

  1. 2026

    Stochastic Reconfiguration as Spectral Filters for Overparameterized Neural Quantum States

    T. Hur* · Advances in Neural Information Processing Systems (NeurIPS)

  2. 2026

    Scalable Neural Decoders for Practical Real-Time Quantum Error Correction

    C. Lee, T. Hur*, and D. Park · npj Quantum Information

  3. 2026

    Machine Learning Approaches to Decoding Topological Quantum Codes

    C. Lee, T. Hur, J. Jae, and D. Park · arXiv:2608.15760

  4. 2025

    Optimizing Quantum Data Embeddings for Ligand-Based Virtual Screening

    J. Choi, T. Hur, S. Jeong, et al. · arXiv:2512.16177

  5. 2025

    Multi-channel Convolutional Neural Quantum Embedding

    Y. Kim, C. Im, T. Kim, T. Hur, and D. Park · Advanced Quantum Technologies, e00575

  6. 2025

    Neural Quantum Embedding via Deterministic Quantum Computation with One Qubit

    H. Liu, T. Hur*, S. Zhang, et al. · Physical Review Letters 135, 080603

    Tutorial →
  7. 2025

    Understanding Generalization in Quantum Machine Learning with Margins

    T. Hur* and D. Park · International Conference on Machine Learning (ICML)

    Tutorial →
  8. 2025

    Early-stage Detection of Cognitive Impairment by Hybrid Quantum-Classical Algorithm Using Resting-state Functional MRI Time-series

    J. Choi, T. Hur, D. Park, N. Shin, S. Lee, H. Lee, and S. Han · Knowledge-Based Systems 310, 112922

  9. 2024

    Neural Quantum Embedding: Pushing the Limits of Quantum Supervised Learning

    T. Hur*, I. Araujo, and D. Park · Physical Review A 110, 022411

    Tutorial →
  10. 2024

    Generative Modeling of Quantum Distribution with Functional Flow Matching

    J. Hahm, T. Hur*, J. Lee, and D. Park · Quantum Techniques in Machine Learning (QTML)

  11. 2022

    Quantum Convolutional Neural Network for Classical Data Classification

    T. Hur*, L. Kim, and D. Park · Quantum Machine Intelligence 4, 3

    Tutorial →