About Me #
I am a doctoral researcher with a background in Computer Science and a passion for AI, currently completing my PhD at Deutsches Elektronen-Synchrotron DESY in Hamburg, Germany. My research focuses on the development of machine learning-based algorithms towards the goal of autonomous particle accelerator operations with a strong focus on control and tuning using reinforcement learning. My other research interests include surrogate modelling and virtual diagnostics using a variety of supervised learning methods.Download my CV
Jan Kaiser, Chenran Xu, Annika Eichler, Andrea Santamaria Garcia, Oliver Stein, Erik Bründermann, Willi Kuropka, Hannes Dinter, Frank Mayet, Thomas Vinatier, Florian Burkart and Holger Schlarb. Learning to Do or Learning While Doing: Reinforcement Learning and Bayesian Optimisation for Online Continuous Tuning. In arXiv, 2023.
Chenran Xu, Jan Kaiser, Erik Bründermann, Annika Eichler, Anke-Susanne Müller and Andrea Santamaria Garcia. Beam Trajectory Control with Lattice-agnostic Reinforcement Learning. In 14th International Particle Accelerator Conference (IPAC), 2023.
Jan Kaiser, Annika Eichler, Sergey Tomin and Zihan Zhu. Machine Learning for Combined Scalar and Spectral Longitudinal Phase Space Reconstruction. In 14th International Particle Accelerator Conference (IPAC), 2023.
Zihan Zhu, Sergey Tomin and Jan Kaiser. Application of Machine Learning in Longitudinal Phase Space Prediction at the European XFEL. In FEL2022, 2022.
Jan Kaiser, Oliver Stein and Annika Eichler. Learning-based Optimisation of Particle Accelerators Under Partial Observability Without Real-World Training. In 39th International Conference on Machine Learning (ICML), 2022.
Oliver Stein, Jan Kaiser, Annika Eichler and Ilya Agapov. Accelerating Linear Beam Dynamics Simulations for Machine Learning Applications. In 13th International Particle Accelerator Conference (IPAC), 2022.
Annika Eichler, Florian Burkart, Jan Kaiser, Willi Kuropka, Oliver Stein, Chenran Xu, Erik Bründermann and Andrea Santamaria Garcia. First Steps Toward an Autonomous Accelerator, a Common Project Between DESY and KIT. In 12th International Particle Accelerator Conference (IPAC), 2021.
Fin Hendrik Bahnsen, Jan Kaiser and Görschwin Fey. Designing Recurrent Neural Networks for Monitoring Embedded Devices. In IEEE European Test Symposium (ETS), 2021.
Jan Kaiser, Kai Bavendiek and Sibylle Schupp. Do We Need Real Data? - Testing and Training Algorithms with Artificial Geolocation Data. In INFORMATIK 2019: 50 Jahre Gesellschaft für Informatik – Informatik für Gesellschaft, 2019.
Featured talks #
Reinforcement Learning Tutorial: Application to an Accelerator Problem. In RL4AA'23, Karlsruhe, Germany, 2023.
Reinforcement Learning for the Optimization of Particle Accelerators. In Machine Learning in Engineering Summer School, Hamburg, Germany, 2022.
Reinforcement learning for Particle Accelerators. In MT ARD ST3 pre-meeting Machine Learning Workshop, Berlin, Germany, 2022.