SQAI

SQAI

Academic conference dedicated to the advancement of quantum AI research and education.

Research

Quantum Research Source: quantum.gov - Computer scientists in the NSF Quantum Leap Challenge Institute for Robust Quantum Simulation.

Welcome to the SQAI Research page.

Here you’ll find highlights of ongoing projects, open collaboration opportunities, and curated resources in the rapidly evolving field of Quantum Artificial Intelligence.

Current Research Directions

We are focused on building bridges between quantum computing and AI, with work spanning both theoretical and applied domains:

  • Quantum Machine Learning (QML): Hybrid quantum-classical models for classification, generation, and optimization.
  • Quantum Algorithms: Development and benchmarking of variational, Grover-based, and hybrid optimization routines.
  • AI for Quantum Control: Machine learning techniques to optimize quantum gates, pulses, and experimental setups.
  • Quantum-Inspired AI: Classical algorithms inspired by quantum principles like superposition or entanglement.

“Quantum Neural State Tomography with Attention-Based Circuits” (2025)

  • Authors: Zhao, L., Martinez, A., & Narang, P.
  • Published in: Nature Quantum Information (May 2025)
  • Citation count: 432+

  • Summary:
    This influential paper proposes an attention-based variational quantum circuit architecture for reconstructing quantum states from sparse measurements. It demonstrates scalability beyond 10 qubits using real IBMQ devices and introduces a hybrid training protocol that reduces gradient noise using classical attention heads.

  • Read the paper on arXiv

Collaborations

We actively partner with academic labs, startups, and institutional researchers working at the intersection of quantum technologies and AI.

If you are interested in collaborating, please contact us. We’re especially open to:

  • Joint project proposals
  • Hosting visiting researchers
  • Co-authoring papers for SQAI 2026

Get Involved

We welcome researchers, students, and developers passionate about quantum AI. Here’s how to participate:

  • Join an ongoing research initiative (announced on our Newsletter)
  • Submit your work to our Symposium CFP
  • Reach out via the Committee page to explore mentorship or project ideas

Resources

Explore key open-source tools and datasets in the Quantum AI ecosystem:

We are also preparing tutorials and open benchmark challenges for SQAI 2026 — stay tuned.

Together, we’re shaping the future of Quantum AI.