Jannis Blüml
Artificial Intelligence and Machine Learning Group, Computer Science Department, TU Darmstadt
and hessian.AI
S2|02, D216 Hochschulstraße 10, 64289 Darmstadt, Germany
jannis (dot) blueml (at) tu-darmstadt (dot) de
Meetings by appointment.
S2|02, D216 Hochschulstraße 10, 64289 Darmstadt, Germany
jannis (dot) blueml (at) tu-darmstadt (dot) de
Meetings by appointment.
Mission.
My research is centered around reinforcement learning, using deep neural networks. Currently I try to combine modern
approaches in this field with transformer networks as well as develop new approaches. My overall goal is to understand reasoning within RL better,
especially when used in partial observable enviroments.
Availability of thesis topics. If you are not yet familiar with our thesis notes, I recommend you start here: Thesis Proposals at AIML
As I said, my focus is on RL. Accordingly, theses that I supervise often fall into this area. Here it is helpful, but not mandatory, if you are familiar with PyTorch/Tensorflow and Deep Neural Networks. If you already have a topic in this direction in mind or are generally interested, feel free to contact me.
Availability of thesis topics. If you are not yet familiar with our thesis notes, I recommend you start here: Thesis Proposals at AIML
As I said, my focus is on RL. Accordingly, theses that I supervise often fall into this area. Here it is helpful, but not mandatory, if you are familiar with PyTorch/Tensorflow and Deep Neural Networks. If you already have a topic in this direction in mind or are generally interested, feel free to contact me.
Timeline.
2021 - now: | PhD student at AIML, CS Department, TU Darmstadt, and hessian.AI, Germany |
2018 - 2021: | M.Sc. Computer Science at TU Darmstadt, Germany |
2014 - 2018: | B.Sc. Computer Science at TU Darmstadt, Germany |
2024 | LSTM-based beampath optimizer for the S-DALINAC, B.Sc. Thesis |
2024 | ISMCTS - Practical Enhancements using Transformers and Theoretical Guarantees for Best Responses, M.Sc. Thesis |
2024 | Game Phase Specific models in A0, M.Sc. Thesis, co-supervised by Johannes Czech |
2023 | Transformers for Urban Energy Management, B.Sc. Thesis |
2023 | Using Graph Neural Networks to Improve Generalization in Self-Play Reinforcement Learning, Yannik Keller, M.Sc. Thesis, co-supervised by Gopika Sudhakaran |
2022 | Replacing PUCT with a Planning Model, M.Sc. Thesis, co-supervisied by Johannes Czech,pdf |
2022 | Multimodal Learning for Chess, B.Sc. Thesis, co-supervisied by Johannes Czech |
2022 | Creating an Agent for the Chess Variant Reconnaissance Blind Chess (RBC), M.Sc. Thesis, co-supervisied by Johannes Czech |
WS 2024/25 | Einführung in die Künstliche Intelligenz, with Prof. Dr. Kristian Kersting, Johannes Czech |
WS 2023/24 | Einführung in die Künstliche Intelligenz, with Prof. Dr. Kristian Kersting, Johannes Czech, Dr. Martin Mundt, |
WS 2023/24 | HackAtari - Object manipulation using the RAM representation in Atari 2600, B.Sc.-Praktikum, with Quentin Delfosse |
WS 2022/23 | Einführung in die Künstliche Intelligenz, with Prof. Dr. Kristian Kersting, Johannes Czech, Dr. Martin Mundt, |
WS 2022/23 | AtariARI 2.0 - Object extraction using the RAM representation in Atari 2600, B.Sc.-Praktikum, with Quentin Delfosse |