About the Workshop
This workshop will cover recent advances in the exciting intersection of Artificial Intelligence and Quantum Computing, focusing on novel algorithms and their applications. We aim to bring together researchers and practitioners to discuss the latest developments and future directions in this rapidly evolving field.
Paper Submission Link
Paper submission details and link will be available soon. Stay tuned!
Workshop Organizers
Pooja Rao
Marwa Farag
Zohim Chandani
Huck Yang
Taylor Patti
Amandeep Singh Bhatia
Yuri Alexeev
Sabre Kais
Workshop Objectives
- Present Cutting-Edge Research: Highlight the latest advancements in AI-driven quantum computing.
- Address Key Quantum Challenges: Explore AI models designed to mitigate issues in quantum machine learning.
- Focus on Industry-Relevant Applications: Showcase practical applications in quantum chemistry, materials science, and more.
- Encourage Cross-Disciplinary Collaboration: Promote knowledge sharing across domains.
- Provide Insights into Future Quantum Technologies: Equip attendees with knowledge of emerging research and industry adoption frameworks.
- Promote AI for Quantum Computing: Offer a platform for exploring the potential of AI in advancing quantum technology.
- Foster Community Building: Create a collaborative space for researchers and industry professionals.
Workshop Relevance
This workshop is highly relevant to the fields of quantum computing and quantum engineering, focusing on key areas such as hybrid quantum computing, AI-integrated quantum algorithms, scalability, and more. It explores the integration of AI techniques with quantum algorithms, aligning with current research trends in error mitigation and scalable quantum-classical hybrid systems.
Anticipated Workshop Outcomes
- Community Building: Establish a collaborative research network.
- Research Roadmap Development: Identify challenges and opportunities for a shared research roadmap.
- Cross-disciplinary Synergy: Generate synergy between quantum computing and classical machine learning communities.
- Standards and Curriculum: Lay the groundwork for developing common standards or curricula.
- Industry Adoption Strategies: Develop frameworks to accelerate industry adoption of AI-enhanced quantum computing.
Invited Speakers
Information about our distinguished invited speakers will be announced soon.
Related NVIDIA Quantum in AI Publications and Blog Posts
- NVIDIA CUDA-Q Powers Quantum Applications Research
- Advancing Quantum Algorithm Design with GPTs
- Augmenting Simulated Noisy Quantum Data Collection by Orders of Magnitude Using Pre-Trajectory Sampling with Batched Execution
- A Quantum Circuit-Based Compression Perspective for Parameter-Efficient Learning