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.


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:

1. Theory and Algorithms: Development of QAI theory, development of novel QAI algorithms, and formulation of classical AI and machine learning techniques for quantum computers.

2. Applications: Near-term real-world QAI applications on NISQ-era quantum computers.

3. Quantum Simulations: Use of QAI for simulating quantum systems.


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