Junseo Lee

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Update: I will be joining Harvard University in Fall 2026 as a PhD student in Quantum Science and Engineering, affiliated with the Harvard Quantum Initiative and the Theory of Computation Group.

I am currently a Research Fellow at the Institute of Computer Technology, Seoul National University, in a position supported by projects from the National Research Foundation of Korea (NRF), the Institute of Information & Communications Technology Planning & Evaluation (IITP), and the Electronics and Telecommunications Research Institute (ETRI).

My research focuses on theoretical computer science questions concerning quantum systems, particularly quantum learning theory and quantum complexity theory, as well as related problems in theoretical physics and pure mathematics, including quantum gravity and quantum topology.

Previously, I completed my mandatory military service in South Korea as a Technical Research Personnel, during which I was also a Research Affiliate at the Research Institute of Mathematics, Seoul National University (RIM SNU). Prior to that, I completed my undergraduate studies in Electrical and Electronic Engineering at Yonsei University on a full scholarship from the Hyundai Motor CMK Foundation, and worked with Dr. Kabgyun Jeong in the Quantum Information Theory Group at RIM SNU.

Curriculum Vitae (CV)
Profiles: LinkedIn, Google Scholar, X (formerly Twitter)
Email: junseolee (at) fas (dot) harvard (dot) edu
Selected Papers

Full publication list available here.

  • Optimal certification of constant-local Hamiltonians
    Junseo Lee, Myeongjin Shin
    arXiv Preprint (2025).
    [PDF], [Property Testing Review]

  • Efficient learning of bosonic Gaussian unitaries
    Marco Fanizza, Vishnu Iyer, Junseo Lee, Antonio Anna Mele, Francesco Anna Mele
    arXiv Preprint (2025).
    Contributed talk at QIP (2026).
    [PDF], [Slides], [QIP 2026]

  • Resource-efficient algorithm for estimating the trace of quantum state powers
    Myeongjin Shin, Junseo Lee, Seungwoo Lee, Kabgyun Jeong
    Quantum (2025).
    [PDF], [Journal], [Slide], [Poster], [Property Testing Review]

Recent Teaching