CFCS Youth Talks

Quantum AI: From near-term to fault-tolerance

  • Dr. Junyu Liu, University of Chicago & IBM
  • Time: 2023-07-10 16:00
  • Host: Dr. Tongyang Li
  • Venue: Room 204, Courtyard No.5, Jingyuan


Quantum machine learning, namely, running machine learning algorithms on quantum devices, has been considered a flag-ship application of quantum computing. In this talk, we will describe two perspectives of quantum machine learning: near-term algorithms and fault-tolerant algorithms. In the near-term realizations, I will discuss applications of variational quantum circuits in machine learning problems, and how a theory of quantum neural tangent kernel could be an analytic principle to optimize quantum neural networks. In the fault-tolerant realizations with quantum error correction, I will briefly discuss some ongoing works with end-to-end applications of the HHL algorithm that provides a provable, generic and efficient quantum algorithm to a class of machine learning problems.



Dr. Junyu Liu(刘峻宇) is a theoretical physicist and postdoc scholar currently  working for the University of Chicago and IBM, associated with the Chicago  Quantum Exchange. He graduated from California Institute of Technology with  a PhD in physics in June 2021, with the working experiences from the Walter  Burke Institute for Theoretical Physics and the Institute for Quantum  Information and Matter, supervised by Clifford Cheung, John Preskill and  David Simmons-Duffin. Starting in 2022, He is a co-founder of SeQure (a  software company for blockchain security using AI and cryptography), and a  research scientist of qBraid co. He graduated from School of the Gifted Young  in the University of Science and Technology of China in 2016 with a bachelor  degree in physics. He is interested in theoretical physics and its relation to  computation, including blockchains, machine learning, optimization, quantum  computing, data science, data security, cryptography and the commercial  value of modern computing technologies.