# Michael Kölle

Michael Kölle works on digital transformation and automation, combining expertise in AI research and software engineering. He is finishing his PhD at LMU Munich, where he leads the Artificial Intelligence for Optimization, Nutrition and Applied Health Laboratory (AIONA-Lab) and is part of the QAR-Lab. He is also the creator and chair of the scientific workshop on Quantum Artificial Intelligence and Optimization.

- LinkedIn: https://www.linkedin.com/in/michaelkoelle/
- GitHub: https://github.com/michaelkoelle
- Google Scholar: https://scholar.google.de/citations?user=lzXyvoAAAAAJ
- ResearchGate: https://www.researchgate.net/profile/Michael-Koelle-2

## Projects (5 of 16)

### [Quantum Artificial Intelligence and Optimization 2026](https://www.michaelkoelle.de/projects/quantum-artificial-intelligence-and-optimization-2026)
A Workshop on Quantum Artificial Intelligence and Optimization co-located with ICAART 2026
Tags: qaio

### [PC Config Automation](https://www.michaelkoelle.de/projects/pc-config-automation)
Automating Price Intelligence for Custom PC Builds
Tags: automation, scape

### [Academic Content Authoring Platform](https://www.michaelkoelle.de/projects/academic-content-authoring-platform)
Create academic documents in seconds—use smart templates, fill in your data, and generate PDFs with ease.
Tags: cap, automation

### [Real-Time Collaborative Exam Correction Tool](https://www.michaelkoelle.de/projects/exam-correction-tool)
A real-time collaborative tool that helps university lecture teams to correct exams efficiently
Tags: automation

### [Quantum Artificial Intelligence and Optimization 2025](https://www.michaelkoelle.de/projects/quantum-artificial-intelligence-and-optimization-2025)
A Workshop on Quantum Artificial Intelligence and Optimization co-located with ICAART 2025
Tags: qaio

## Academic Publications (5 of 64)

### [An Adaptive Purification Controller for Quantum Networks: Dynamic Protocol Selection and Multipartite Distillation](https://www.michaelkoelle.de/publications/An-Adaptive-Purification-Controller-for-Quantum-Networks-Dynamic-Protocol-Selection-and-Multipartite-Distillation)
Pranav Kulkarni, Leo Sünkel, Michael Kölle · 2026
Efficient entanglement distribution is a cornerstone of the Quantum Internet. However, physical link parameters such as photon loss, memory coherence...

### [Quantum King-Ring Domination in Chess: A QAOA Approach](https://www.michaelkoelle.de/publications/Stenzel2026KingRing)
Gerhard Stenzel, Michael Kölle, Tobias Rohe, Julian Hager, Leo Sünkel, Maximilian Zorn, Claudia Linnhoff-Popien · 2026 · Proceedings of the 18th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART
DOI: https://doi.org/10.5220/0014447700004052
The Quantum Approximate Optimization Algorithm (QAOA) is extensively benchmarked on synthetic random instances such as MaxCut, TSP, and SAT problems,...

### [Reinforcement Learning for Parameterized Quantum State Preparation: A Comparative Study](https://www.michaelkoelle.de/publications/Stenzel2026ReinforcementParameterized)
Gerhard Stenzel, Michael Kölle, Tobias Rohe, Leo Sünkel, Julian Hager, Claudia Linnhoff-Popien · 2026 · Proceedings of the 18th International Conference on Agents and Artificial Intelligence - Volume 4: ICAART
DOI: https://doi.org/10.5220/0014395600004052
We extend directed quantum circuit synthesis (DQCS) with reinforcement learning from purely discrete gate selection to parameterized quantum state pre...

### [Illustration of Barren Plateaus in Quantum Computing](https://www.michaelkoelle.de/publications/Illustration-of-Barren-Plateaus-in-Quantum-Computing)
Gerhard Stenzel, Tobias Rohe, Michael Kölle, Leo Sünkel, Jonas Stein, Claudia Linnhoff-Popien · 2026 · Proceedings of the 18th International Conference on Agents and Artificial Intelligence - Volume 1: QAIO
DOI: https://doi.org/10.5220/0014310300004052

### [Emergent Cooperation in Quantum Multi-Agent Reinforcement Learning Using Communication](https://www.michaelkoelle.de/publications/Emergent-Cooperation-in-Quantum-Multi-Agent-Reinforcement-Learning-Using-Communication)
Michael Kölle, Christian Reff, Leo Sünkel, Julian Hager, Gerhard Stenzel, Claudia Linnhoff-Popien · 2026 · ICC 2026 - IEEE International Conference on Communications
Emergent cooperation in classical Multi-Agent Reinforcement Learning has gained significant attention, particularly in the context of Sequential Socia...

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Full lists: [projects](https://www.michaelkoelle.de/projects) · [publications](https://www.michaelkoelle.de/publications) · https://www.michaelkoelle.de
Last updated: 2026-05-06