Jan Kaiser

Deutsches Elektronen-Synchrotron · MSK - Maschine Strahlkontrollen

Online tuning of real-world plants is a complex optimisation problem that continues to require manual intervention by experienced human operators. Autonomous tuning is a rapidly expanding field of research, where learning-based methods, such as Reinforcement Learning-trained Optimisation (RLO) and Bayesian optimisation (BO), hold great promise for...

In recent work, it has been shown that reinforcement learning (RL) is capable of outperforming existing methods on accelerator tuning tasks. However, RL algorithms are difficult and time-consuming to train, and currently need to be retrained for every single task. This makes fast deployment in operation difficult and hinders collaborative efforts i...

In recent work, it has been shown that reinforcement learning (RL) is capable of solving a variety of problems at sometimes super-human performance levels. But despite continued advances in the field, applying RL to complex real-world control and optimisation problems has proven difficult. In this contribution, we demonstrate how to successfully ap...

Machine learning has proven to be a powerful tool with many applications in the field of accelerator physics. Training machine learning models is a highly iterative process that requires large numbers of samples. However, beam time is often limited and many of the available simulation frameworks are not optimized for fast computation. As a result,...

Reinforcement learning algorithms have risen in popularity in the accelerator physics community in recent years, showing potential in beam control and in the optimization and automation of tasks in accelerator operation. The Helmholtz AI project "Machine Learning Toward Autonomous Accelerators" is a collaboration between DESY and KIT that works on...

Embedded systems play an important role in various tasks in many areas of our lives. In the case of safety-critical applications, e.g., in the fields of autonomous driving, medical devices or control of unmanned aerial vehicles (UAV), the correct system operation must always be guaranteed. Standard methods for monitoring an embedded application, i....

As big data becomes increasingly important, so do algorithms that operate on geolocation data. Privacy requirements and the cost of collecting large sets of geolocation data, however, make it difficult to test those algorithms with real data. Artificially generated data sets therefore present an appealing alternative. This paper explores the use of...