Junseo Lee

I am an incoming PhD student in Quantum Science and Engineering at Harvard University, where I am fortunate to be advised by Professors Anurag Anshu, Sitan Chen, and Jordan Cotler.

At Harvard, I am affiliated with the Harvard Quantum Initiative, the Theory of Computation Group, and the Department of Physics. I am also a Junior Investigator at the NSF AI Institute for Artificial Intelligence and Fundamental Interactions (IAIFI), based at MIT.

My research lies at the interface of theoretical computer science and mathematical physics, with the goal of understanding the quantum world through computation and information. I am broadly interested in quantum complexity theory, including the quantum PCP conjecture, area laws, and connections to black holes and quantum field theory. I also study algorithms for learning quantum systems and extracting information from them, as well as problems in quantum many-body physics involving qubits, bosons, fermions, and anyons.

Previously, I conducted research at Seoul National University through the Institute of Computer Technology and the Research Institute of Mathematics. I completed my undergraduate studies in electrical and electronic engineering at Yonsei University, fully supported by the Hyundai Motor CMK Science and Technology Scholarship.

📄 Curriculum Vitae (Last updated: May 23, 2026)
🔗 LinkedIn | Google Scholar | X (formerly Twitter)
📨 junseolee at fas.harvard.edu

News +
  • May 2026: I joined the NSF AI Institute for Artificial Intelligence and Fundamental Interactions (IAIFI) as a Junior Investigator.
  • Apr. 2026: I gave an invited career talk for students at Shinil High School.
  • Apr. 2026: Our paper on Hamiltonian certification was selected as a contributed talk at TQC 2026.
  • Apr. 2026: I joined the Institute of Computer Technology at Seoul National University as a Research Associate, where I will be working until August 2026 before joining Harvard.
  • Mar. 2026: I visited Harvard for the QSE Open House and continued my visit with support from Anurag Anshu.
  • Mar. 2026: I completed my mandatory military service!
  • Feb. 2026: I was delighted to be admitted to the doctoral programs in Quantum Science and Engineering at Harvard, Physics at MIT, and Computer Science at Oxford. I have accepted the offer from Harvard and am excited for the journey ahead!
Selected Papers +
A full publication list is available here.
  • Certifying and learning local quantum Hamiltonians
    (with Andreas Bluhm, Matthias C. Caro, Francisco Escudero Gutiérrez, Aadil Oufkir, Cambyse Rouzé, Myeongjin Shin)
    Contributed talk at TQC (2026)
  • Efficient learning of bosonic Gaussian unitaries
    (with Marco Fanizza, Vishnu Iyer, Antonio Anna Mele, Francesco Anna Mele)
    Contributed talk at QIP (2026)
  • Resource-efficient algorithm for estimating the trace of quantum state powers
    (with Myeongjin Shin, Seungwoo Lee, Kabgyun Jeong)
    Quantum 9, 1832 (2025)
Mentoring +

I mentored undergraduate students in research, which I found both deeply rewarding and intellectually enriching. I had the privilege of working with outstanding students and learned a great deal from our collaborations. The students I have worked with are listed below:

Current Mentees:
Former Mentees:
  • Kartik Anand (IIT Goa, 2025; now a master's student at Hamburg University of Technology)

I am happy to discuss potential research opportunities with undergraduate students, including summer projects. In some cases, projects may also develop into collaborations involving other researchers. Please feel free to reach out by email if you are interested.

Teaching +
QISCA Special Lecture Series:
University-Industry Research Internship:
  • Instructor, AAA559: College of Informatics Internship (II) (Graduate Course), Korea University, Fall 2025
  • Instructor, AAA558: College of Informatics Internship (I) (Graduate Course), Korea University, Fall 2025
  • Instructor, SW4343: Software Field Placement (I), Korea Aerospace University, Fall 2024
Yonsei University:
  • Teaching Assistant, YCS1009: Change the World through Programming, Fall 2022
  • Teaching Assistant, YCS1002: Software Programming, Fall 2022
  • Teaching Assistant, EEE1108: Engineering Information Processing, Fall 2021
  • Course Tutor, MAT2016: Engineering Mathematics (III), Spring 2022 (Best Tutor Award)
  • Course Tutor, MAT1012: Engineering Mathematics (II), Fall 2021 (Best Tutor Award)