Workshop on Quantum Artificial Intelligence and Optimization

QAIO is designed as a collaborative bridge between classical artificial intelligence and emerging quantum computing technologies, bringing AI researchers together with quantum computing specialists for knowledge transfer in both directions. Sessions cover how quantum computing can advance AI through enhanced optimization algorithms, quantum machine learning models, and the integration of quantum and classical techniques, spanning theoretical foundations, practical applications, and hybrid systems that draw on both paradigms. Paper submissions are due 3 December 2026, with author notification on 21 December 2026 and camera ready on 8 January 2027. Accepted papers appear in a special section of the ICAART proceedings under an ISBN and in the SCITEPRESS Digital Library with a DOI, and are submitted for indexing by Scopus, Google Scholar, DBLP, Semantic Scholar, EI, and Web of Science. The workshop is chaired by Michael Koelle and Tobias Rohe of LMU Munich.

  For more information, visit the workshop website