[Joint CQSE & NCTS Special Seminar] Variational Quantum Circuits as Machine Learning Models

  • Event Date: 2022-12-13
  • Quantum Information and Quantum Computing
  • Speaker: Dr. Yen-Chi Chen (Senior Software Engineer, Wells Fargo Bank)  /  Host: Profs. Hsi-Sheng Goan & ​Hao-Chung Cheng (NTU)
    Place: NCTS Physics Lecture Hall, 4F, Chee-Chun Leung Cosmology Hall, NTU

Title: [Joint CQSE & NCTS Special Seminar] Variational Quantum Circuits as Machine Learning Models
Speaker: Dr. Yen-Chi Chen (Senior Software Engineer, Wells Fargo Bank)
Time: Dec. 13, 2022, 12:30-13:30
Place: NCTS Physics Lecture Hall, 4F, Chee-Chun Leung Cosmology Hall, NTU
Online: https://nationaltaiwanuniversity-zbh.my.webex.com/nationaltaiwanuniversity-zbh.my/j.php?MTID=mff0fb89b085cb380e34d19466b26897c

Abstract:
Quantum machine learning (QML) is an emerging research field combining
quantum computing and machine learning to solve challenging tasks. Variational
quantum circuits (VQC) is a leading framework to build QML models for near-term
quantum devices. In this talk, I will describe the fundamentals behind this paradigm and
provide several examples. Promising research directions in this field will also be
discussed.

Biography:
Dr. Samuel Yen-Chi Chen received the Ph.D. and B.S. degree in physics and the M.D.
degree in medicine from National Taiwan University, Taipei City, Taiwan. He is now a
senior software engineer at Wells Fargo Bank. Prior to that, he was an assistant
computational scientist in the Computational Science Initiative, Brookhaven National
Laboratory. His research interests include building quantum machine learning
algorithms as well as applying classical machine learning techniques to solve quantum
computing problems. He won the First Prize in the Software Competition (Research
Category) from Xanadu Quantum Technologies, in 2019.