Homepage Dr. Michael Lupberger

My field of research is experimental particle and hadron physics. I focus on gaseous detectors, data acquisition systems and machine learning on embedded processors across disciplines. My students and I are currently working on the preparation of the AMBER experiment, the further improvement of RD51's general Scalable Readout System and on exploiting the novel Xilinx Adaptive Compute Acceleration Platform. On the latter, we develop low-latency, ultra-high rate tracking based on artificial intelligence.


December 2022: New student - The AMBER pilot run data will be investigated by a new bachelor student I will supervise.

October 2022: TRA project granted - I was warded 20.000 € as seed funds related to an ERC Starting Grant preperation. In 2023, I will get the FTD clean rooms ready for GridPix and double-grid structures. Thanks to the Transdisciplinary Research Unit Matter!

October 2022: New student - We will look into the signal-to-noise ratio of the VMM front-end chip at the GEM detector prototype for AMBER in a bachelor thesis project I supervise.

July 2022: DRDC1 preperaction - We started the implemenation of the ECFA Detector R&D Roadmap in an extended RD51 Management Board, in which I am a member.

June 2022: Marie Curie - My Marie-Curie Fellowship project ended and I submitted my final report.

June 2022: Global Cooperation - I just came back from Paris, where I presented the SRS VMM readout and AMBER at the CEA DEDIP Seminar and discussed cooperation related to Machine Learning on FPGA. On the visit of my collaboartors in Bonn, we had a super interesting talk on Machine Learning at CMS.

May 2022: Strategic partnership - We just had a fascinating presentation on Fast Machine Learning on FPGAs and its application in High Energy Physics. We also established a partnership which is our entry point to the Fast Machine Learning community.

December 2021: yHEP MB - I have been elected Management Board Member of the Particle Physics division of the young High Energy Physics Association.

November 2021: Bonn Global Cooperation project granted: I was awared 20.000 € by the University of Bonn as seed funding for a cooperation with the Université Paris-Saclay to work towards a joint third-party funding application related to Machine Learning on FPGA.

October 2021: AMBER pilot run - Two intense week are over and I have taken an enormous about of data with a prototype GEM detector for AMBER and the triggerless VMM front-end electronics with the SRS readout.

Final presentation slide
© Michael Lupberger
© Michael Lupberger

RD51 will end in December 2023. At the 30th (and final) collaboration meeting, I presented our work on the AMBER GEM detectors and readout electronics. My final slide is an attribute to the RD51 collaboration, in which I grow up as a scientist. The farewell party for RD51 is at the same time the celebration of the approval of the DRD1 collaboration, where we will continue our fruitful work.

I had the honour to lecture at the RD51 MPGD School on the topic of Electronics Readout Techniques. It was a pleasure to see about 100 (local and remote) participants in the lecture and the 24 highly motivated students to participate in the hands-on sessions in the lab. The live demo of SRS VMM was a highlight of the school and will be a reference for future users.

As an output of the workshop Sustainability in the Digital Transformation of Basic Research on Universe and Matter I was involved in the organisation, we have published a paper on arXiv on Resource-aware Research on Universe and Matter: Call-to-Action in Digital Transformation, which will soon appear in the journal Computing and Software for Big Science.

© M. Lupberger/J. Kaminski
© CC0 1.0 שמוליק הראל
© Michael Lupberger

Our project Instrumentation for Next GEneration
Neutron Science (INGENS) on the development of novel neutron detectors and readout electronics by technology transfer from particle physics was approved for funding! As in the past funding period, I will co-manage the project with another PostDoc and be responsible for two PhD students and one PostDoc.

The project is carried out in the AG Desch.

I am looking forward to meeting you at the MPGD conference at Weizmann Institute of Science in Rehovot (Israel), where I will present a poster on neutron detectors. As a member of the extended RD51 Management Board, I will also be involved in the discussion on the transition to the new Detector R&D Collaboration 1 related to the ECFA Detector R&D Roadmap.

For more information, see the conference web page.

Our proceedings paper from the 15th Pisa Meeting on Advanced Detectors was accepted for publication. Find it here (restricted) or here (open access).

My research


Micro-pattern gaseous detector are my field of expertise. For the AMBER experiment at CERN, my students and I work with GEM detectors, their improvement and construction. I also employ boron-coated GEMs for neutron detection. I am one of the leading experts in the GridPix technology, for which I have demonstrated the feasibility of a Pixel-TPC.

I am a member of the RD51 collaboration since 2009 and currently a member of the extended management board to prepare the transition to DRDC1.

As one of the main developers of the Scalable Readout System (SRS) of the RD51 collaboration, I implemented the Timepix and VMM chips. With my students, I constantly improve the system with the VMM. One of my PhD students currently implements the Timepix3 chip into SRS.

As one of the first groups in academia, me and a PhD student are employing the Xilinx Versal AI Series for fast inference of Machine Learning. Our goal is low-latency, high-rate online particle tracking using Graph Neural Networks embedded in the data acquisition system.


Within the group of Prof. Ketzer, we develop novel high-rate GEM detectors for planar tracking with triggerless readout. I am mainly responsible for the front-end electronics for which we intend to apply the VMM chip.

In this BMBF funded project, we transfer detector technology and readout electronics from particle physics to neutron science. We modify state-of-the-art detector concepts with neutron converters and employ the Scalable Readout System of the RD51 collaboration with the VMM and Timepix(3) as readout platform.

Within the globalisation strategy of the University of Bonn, I collaborate with another early-career researcher from the Université Paris-Saclay/CEA Saclay to work on Machine Learning on FPGA. The goal of the project is a common third-party funding application towards set the project on a solid basis.

To build GridPixes and double-grid structures, the setup of the photolithographic processes in the clean rooms of the FTD is supported.

CV, publications, presentations

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