Unpil Baek

Unpil Baek

Ph.D. student in Physics

University of California, Berkeley

Biography

Unpil Baek is a Ph.D. student in physics at the University of California, Berkeley, working in Birgitta Whaley’s group. He is interested in simulating strongly-correlated electrons with near- and intermediate-term quantum computers. He is also interested in combining classical machine learning techniques with variational quantum-classical algorithms to improve accuracy and reduce resource costs.

Past research

Unpil worked briefly on superconducting qubit experiments in Quantum Nanoelectronics Lab led by Irfan Siddiqi. He developed a custom FPGA-based hardware for superconducting qubit control with Dr. Gang Huang from Lawrence Berkeley National Laboratory. He also designed and built several 80/20 frames for the new dilution refrigerators in the lab.

For his undergraduate senior thesis, Unpil worked with Robert Littlejohn on the presymplectic reduction of general relativity under the local Lorentz invariance.

Interests
  • Digital quantum simulation
  • Variational quantum-classical algorithms
  • Strongly-correlated systems
  • Machine learning applied to quantum computing
Education
  • Ph.D. in Physics, 2023*

    University of California, Berkeley

  • M.A. in Physics, 2018

    University of California, Berkeley

  • B.A. in Physics and Applied Mathematics, 2017

    University of California, Berkeley

Skills

Python
C++
GitHub
Public Speaking
& Teaching
Languages

Korean, Japanese, Chinese
Spanish, Latin

writing

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