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iSAS

Innovate for Sustainable Accelerating Systems

Andrei Maalberg joins iSAS as a PostDoc from Helmholtz-Zentrum Berlin

Andrei Maalberg joins iSAS as a PostDoc from Helmholtz-Zentrum Berlin

It is our great pleasure to announce the starting from September 2024 of Dr. Andrei Maalberg

By Nicholas Shipman

It is our great pleasure to announce that starting from September 2024 Dr. Andrei Maalberg joins Helmholtz-Zentrum Berlin as a PostDoc who will be working in the context of the innovate for Sustainable Accelerating Systems (iSAS) program. Dr. Maalberg will strengthen our team with his expertise in the theory of automatic control, machine learning and digital logic. One of the main goals of the iSAS collaboration is to reduce radio frequency power that is required for the operation of particle accelerator cavities. At the same time, it is critically important that such power reduction does not compromise the daily operation of existing as well as future accelerator facilities. Dr. Maalberg will contribute to this effort by designing and implementing new control algorithms for accelerator systems, including piezo and fast reactive tuners.  Specifically, Dr. Maalberg will strengthen HZB’s contribution to WP2 “Low Level RF controls” and the interface to WP1 “Ferro-Electric Fast Reactive Tuners”.

Andrei Maalberg received his B.Sc. and M.Sc. degrees from Tallinn University of Technology in computer systems and engineering, 2015 and 2018, respectively. During his Master’s studies he also had an exchange period at École Polytechnique Fédérale de Lausanne, Switzerland. In 2023, he received his Ph.D. degree in information and communication technology from Tallinn University of Technology for his work at Helmholtz-Zentrum Dresden-Rossendorf. His main research interests include the design and implementation of control algorithms for cyber-physical systems. Recently he began to research the feasibility of merging stability notions from the theory of automatic control with the flexibility and expressiveness of machine learning.

“This is a beautiful opportunity to put theory into practice. Provided our algorithmic study to unite control theory and machine learning succeeds, we can deliver a provably stable and yet adaptable control solution that will facilitate the sustainability of particle accelerators”.

Dr. Andrei Maalberg

Given Dr. Maalberg’s expertise and passion we have no doubt he will make invaluable contributions to the iSAS collaboration.

Published on September 16, 2024
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