Workshop
Workshop on Quantum Artificial Intelligence and Optimization -
QAIO
2026
5 - 7 March, 2026 - Marbella, Spain
In conjunction with the 18th International Conference on Agents and Artificial Intelligence - ICAART 2026
CO-CHAIRS
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Michael Kölle
Mobile and distributed Systems Group, LMU Munich
Germany
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Brief Bio
Michael Kölle is a researcher currently pursuing a Ph.D. in Computer Science, focusing on the intersection of Artificial Intelligence and Quantum Computing. After obtaining a Bachelor of Science in Media Informatics in 2018, Mr. Kölle graduated with a Master’s degree in Computer Science in 2021, both from Ludwig-Maximilians-Universität München, Germany. Mr. Kölle's research primarily explores how quantum computing can be integrated with machine learning to develop innovative solutions within Quantum AI. This work aims to harness the computational powers of quantum technologies to address complex problems that are beyond the scope of classical computing methods. Alongside, Mr. Kölle is also deeply involved in studying Multi-Agent Systems, investigating how multiple intelligent agents can interact within a system to achieve individual or collective goals efficiently.
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Tobias Rohe
LMU Munich
Germany
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Brief Bio
Tobias Rohe earned a Bachelor of Science in Business Administration from the University of Munich, including a semester at the University of Exeter, in 2019. He completed a Bachelor of Science in Computer Science at the University of Munich in 2022, and also holds a Master of Science in Business Administration, with a focus on Innovation & Digital Business, from the same university since 2021. Currently, he is a PhD student in Computer Science at the University of Munich, having started in 2023.
His professional experience includes working as an academic assistant and serving as an external consultant for IQM Quantum Computers.
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SCOPE
Our workshop, "Quantum Artificial Intelligence and Optimization", is designed as a collaborative bridge between classical artificial intelligence (AI) and emerging quantum computing technologies. It aims to facilitate knowledge transfer and synergistic exploration among AI experts and quantum computing pioneers. This session will delve into how quantum computing can enhance AI through improved optimization algorithms, quantum machine learning models, and the seamless integration of quantum and classical computing techniques. Participants will engage in discussions on theoretical foundations, practical applications, and the development of hybrid systems that leverage the best of both worlds. By focusing on collaboration, this platform encourages the sharing of insights, challenges, and future directions, paving the way for breakthroughs in AI capabilities powered by quantum advancements.
TOPICS OF INTEREST
Topics of interest include, but are not limited to:
- Quantum AI & Decision Making
- Quantum Machine Learning
- Quantum Optimization Algorithms
- Hybrid Quantum-Classical Computing
- Quantum Architecture Design & Synthesis
- Quantum Circuit Optimization using AI
- Applications of Quantum AI
- Quantum Machine Learning Operations
- Distributed Quantum Machine Learning
- Quantum Cognition & Affect
IMPORTANT DATES
Paper Submission:
December 17, 2025
Authors Notification:
January 14, 2026
Camera Ready and Registration:
January 22, 2026
WORKSHOP PROGRAM COMMITTEE
Available soon.
PAPER SUBMISSION
Prospective authors are invited to submit papers in any of the topics listed above.
Instructions for preparing the manuscript (in Word and Latex formats) are available at: Paper Templates
Please also check the Guidelines.
Papers must be submitted electronically via the web-based submission system using the appropriated button on this page.
PUBLICATIONS
After thorough reviewing by the workshop program committee, all accepted papers will be published in a special section of the conference proceedings book - under an ISBN reference and on digital support.
All papers presented at the conference venue will be available at the SCITEPRESS Digital Library (http://www.scitepress.org/DigitalLibrary/).
SCITEPRESS is a member of CrossRef (http://www.crossref.org/) and every paper is given a DOI (Digital Object Identifier).