Recent Advances in AI for Quantum:
Algorithms, Applications
The inaugural workshop bringing together researchers at the intersection of artificial intelligence and quantum computing to discuss novel algorithms and applications.
Overview
This workshop covered recent advances at the exciting intersection of artificial intelligence and quantum computing, focusing on novel algorithms and their applications.
Researchers and practitioners discussed the latest developments and future directions in this rapidly evolving field, spanning hardware integration, AI-assisted algorithm design, scalability of quantum-classical hybrid systems, and error mitigation techniques.
The workshop explored how AI techniques can be integrated with quantum algorithms — addressing hybrid quantum computing, scalable AI-quantum workflows, and current trends in quantum software and systems.
Schedule
Friday, September 5, 2025 · Albuquerque, NM
Organizers
Pooja Rao
NVIDIA
Marwa Farag
NVIDIA
Zohim Chandani
NVIDIA
Huck Yang
NVIDIA
Taylor Patti
NVIDIA
Amandeep Singh Bhatia
NC State University
Yuri Alexeev
NVIDIA
Sabre Kais
NC State University
Related publications
- 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
- QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits
- Cross-Problem Parameter Transfer in Quantum Approximate Optimization Algorithm: A Machine Learning Approach
- MLQAOA: Graph Learning Accelerated Hybrid Quantum-Classical Multilevel QAOA
- Graph Representation Learning for Parameter Transferability in Quantum Approximate Optimization Algorithm