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Workshop
Workshop on Quantum Artificial Intelligence and Optimization - QAIO 2027

26 February, 2027 - Valletta, Malta

In conjunction with the 19th International Conference on Agents and Artificial Intelligence - ICAART 2027


CO-CHAIRS

Michael Kölle
Mobile and Distributed Systems Group, LMU Munich
Germany
 
Short Bio
Michael Kölle is a researcher specializing in Artificial Intelligence and Quantum Computing. He completed his Ph.D. in Computer Science in 2026, with research focused on the intersection of quantum technologies and machine learning. He received a Bachelor of Science in Media Informatics in 2018 and a Master of Science in Computer Science in 2021, both from Ludwig-Maximilians-Universität München, Germany. His current work focuses on Quantum Artificial Intelligence, including the integration of quantum computing and machine learning to develop innovative approaches for solving complex computational problems. He also leads the AIONA Lab, where his research explores Artificial Intelligence for healthcare and medical applications, including intelligent methods for clinical decision support, medical data analysis, and the development of advanced healthcare technologies.
Jonas Stein
LMU Munich
Germany
 
Short Bio
Jonas Stein is a researcher specializing in Quantum Computing, Artificial Intelligence, and Optimization. He completed his Ph.D. in Computer Science at Ludwig-Maximilians-Universität München (LMU Munich) in 2026. His doctoral research focused on quantum applications in optimization and AI, as well as algorithmic methods for improving their practical performance. He previously earned both a Bachelor’s and a Master’s degree in Computer Science from LMU Munich. He has authored or co-authored more than 50 conference and journal papers in Quantum Computing, spanning Quantum Machine Learning, Quantum Optimization and Quantum Algorithms. He co-leads the Quantum Applications and Research Laboratory (QAR-Lab), where his research focuses on developing application-oriented quantum and hybrid quantum-classical methods for solving complex computational problems and identifying areas in which practically relevant quantum advantage may emerge.
Tobias Rohe
LMU Munich
Germany
 
Short Bio
Tobias Rohe is a researcher currently pursuing a Ph.D. in Computer Science, focusing on the intersection of Artificial Intelligence, Optimization and Quantum Computing. After obtaining a Bachelor of Science and a Master of Science in Business Administration in 2019, respectively 2021, Mr. Rohe graduated with a Bachelor of Science in Computer Science in 2022, all from the Ludwig-Maximilians-Universität München, Germany. Mr. Rohe's research primarily explores how quantum computing can be used for approximating optimal solutions for combinatorial optimization problems, in particular under consideration of entanglement. In addition, Mr. Rohe is interested in how entanglement can be used not only for optimization, but also for generative quantum machine learning tasks. His research focuses strongly on concrete applications. He is project coordinator of the quantum software platform QuCUN.

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 revolutionize AI through enhanced 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 Generative Models

IMPORTANT DATES

Paper Submission: December 3, 2026
Authors Notification: December 21, 2026
Camera Ready and Registration: January 8, 2027

WORKSHOP PROGRAM COMMITTEE

Damir Cavar, Indiana University Bloomington, United States
Samuel Yen-Chi Chen, Wells Fargo, United States
Elias Combarro, University of Oviedo, Spain
Sven Engelmann, Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen, Germany
Sebastian Feld, Delft University of Technology, Netherlands
Victoria Goliber, D-Wave, United States
Daniel Hein, Foundational Technologies, Siemens AG, Germany
Janine Hilder, neQxt GmbH
Thomas Husslein, OptWare, Germany
Luigi Iapichino, Leibniz Supercomputing Centre (LRZ), Germany
Chon-Fai Kam, University at Buffalo, United States
Gopal Karemore, IBM Quantum, United States
Florian Knäble, Fraunhofer IAO, Germany
Florian Krellner, SAP SE, Germany
Rajiv Krishnakumar, QuantumBasel, Switzerland
Jeanette Miriam Lorenz, Fraunhofer IKS, Germany
Francisco Martínez Álvarez, Pablo de Olavide University of Seville, Spain
Nico Meyer, Fraunhofer IIS, Germany
Evert van Nieuwenburg, Leiden University, Netherlands
Daniel Scherer, Fraunhofer IIS, Germany
Michael Schlotter, Schaeffler Technologies AG & Co. KG, Germany
Takao Tomono, Research & Development Directorate, Japan Aerospace Exploration Agency (JAXA), Japan
Steffen Udluft, Learning Systems, Siemens Technology, Germany
Autilia Vitiello, University of Naples Federico II , Italy
Sebastian Wölckert, LMU Munich, Germany
Jianjun Zhao, Faculty of Information Science and Electrical Engineering, Kyushu University, Japan
Maximilian Zorn, LMU Munich, Germany

(list not yet complete)

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).

SECRETARIAT CONTACTS

ICAART Workshops - QAIO 2027
e-mail: icaart.secretariat@insticc.org
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