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Robert Gieselmann
I am an AI Researcher at Amazon in Berlin developing
fast, verifiable, and self-improving reasoning systems, primarily leveraging Large Language
Models (LLMs).
Previously, I completed a PhD in Computer Science at KTH Royal Institute of Technology in Stockholm,
supervised by Florian T.
Pokorny, and supported by WASP, the
Wallenberg AI, Autonomous Systems and Software Program. I completed several internships, including
at Meta and Bosch AI.
Before my PhD, I worked as a Research Assistant within machine learning and robotics at the Technical
University of Hamburg (TUHH). I received my M.Sc. in Robotics, Cognition, Intelligence from the
Technical University of Munich (TUM).
LinkedIn /
Google Scholar /
Github
Selected Publications
Efficient Test-time Inference for Generative Planning Models with OCL Search
Robert Gieselmann, Mihai Samson, Federico Pecora, Jeremy L. Wyatt
International Conference on Machine Learning (ICML), 2026
[Paper]
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Self-Improvement for Fast, High-Quality Plan Generation
Robert Gieselmann, Henrike von Huelsen, Mihai Samson, Marie-Christine Meyer,
Dariusz Piotrowski, Oleksandr Radomskyi, Justin Okamoto, Turan Gojayev, Michael Painter,
Gavin Brown, Federico Pecora, Jeremy L. Wyatt
International Conference on Automated Planning and Scheduling (ICAPS), 2026
[Paper]
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Expansive Latent Planning for Sparse Reward Offline Reinforcement
Learning
Robert Gieselmann, Florian T. Pokorny
Conference on Robot Learning (CoRL), 2023
(oral presentation 6.6%)
[Paper]
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Latent Planning via Expansive Space Trees
Robert Gieselmann, Florian T. Pokorny
Neural Information Processing Systems (NeurIPS), 2022
[Paper]
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