QCE20 Workshop on
Applied Quantum Artificial Intelligence (AQAI)

 

Date and Time

  • Mon, Oct 12, 2020
  • 10:45─16:45 Mountain Time (MT) — UTC-6

Organizers

  • Prasanna Date, Oak Ridge National Laboratory – Organizing Committee Chair
  • Kathleen Hamilton, Oak Ridge National Laboratory – Organizing Committee Chair

Overview

The goal of the Applied Quantum Artificial Intelligence workshop is to advance the state of Quantum Artificial Intelligence (QAI) by highlighting recent research on the utilization of near-term quantum processors as well as hybrid quantum-classical approaches in many different real-world artificial intelligence applications. We hope to promote the exchange of QAI research ideas, build a collaborative platform for QAI research, forge a community of QAI researchers and outline a long-term research roadmap for QAI.

Invited Speakers

Alejandro Perdomo-Ortiz, Zapata Computing
Keynote Speaker, AQAI Workshop

Alejandro Perdomo-OrtizAlejandro Perdomo-Ortiz did his graduate studies, M.A and Ph.D. in Chemical Physics, at Harvard University. Over the past 12+ years, he has explored the computational limits and opportunities of quantum computing for real-world applications. Before joining Zapata Computing as a Senior Quantum Scientist and Quantum Applications Lead, Alejandro was the lead scientist of the Quantum Machine Learning effort at NASA’s Quantum Artificial Intelligence Laboratory (NASA QuAIL) where he worked for 5+ years. He was also the Co-Founder of Qubitera LLC, a consulting company acquired by Rigetti Computing where he worked after NASA and before his current appointment with Zapata Computing. His latest research involves the design of hybrid quantum-classical algorithms to solve hard optimization problems and intractable machine learning subroutines.

Nathan Killoran, Xanadu Quantum Computing
Panel Discussion Speaker, AQAI Workshop

Nathan KilloranNathan Killoran is the Head of Software & Algorithms at Xanadu, and one of the founding developers of PennyLane, the world’s leading quantum machine learning software library. Nathan steers Xanadu’s open-source quantum software products and leads algorithm research in photonics and quantum machine learning. Nathan holds a PhD in Physics from the University of Waterloo, with expertise in quantum computing, deep learning, and quantum optics.


AQAI Workshop Schedule

10:45-11:45 Keynote by Alejandro Perdomo-Ortiz (Zapata Computing)
11:45-12:15 Paper Presentation Session 1


13:00-14:30 Paper Presentation Session 2


15:15-15:45 Paper Presentation Session 3
15:45-16:45 Panel Discussion on “Quantum Artificial Intelligence in the NISQ Era and Beyond
with Patrick Coles (LANL), Nathan Killoran (Xanadu Quantum Computing),
Maria Schuld (University of KwaZulu-Natal and Xanadu Quantum Computing),
and Davide Venturelli (NASA)

Program Committee

Important Dates

  • Paper Submission Deadline extended: August 15, 2020
  • Notification of Acceptance extended: September 15, 2020
  • Workshop Date: October 12, 2020

Submission Instructions

Call for Papers

Current research pertaining to Quantum Artificial Intelligence (QAI) is mainly comprised of designing novel QAI algorithms or formulating existing machine learning algorithms for quantum computers. Researchers are also exploring real-world applications and use cases for NISQ-era quantum computers within the AI and machine learning space. Physicists have used AI and machine learning models for enhancing and augmenting the simulation of quantum systems. Accordingly, we have the following three sessions:

  • Theory and Algorithms: Development of QAI theory, development of novel QAI algorithms, and formulation of classical AI and machine learning techniques for quantum computers.
  • Applications: Near-term real-world QAI applications on NISQ-era quantum computers.
  • Quantum Simulations: Use of QAI for simulating quantum systems.

Contact Us

For more information about the Applied Quantum Artificial Intelligence (AQAI) workshop, contact Prasanna Date (datepa@ornl.gov) or Kathleen Hamilton (hamiltonke@ornl.gov).