Suren Chilingaryan

Dr. Suren Chilingaryan is a Data Processing and Software Performance Expert at the Institute for Process Data Processing and Electronics (IPE) at Karlsruhe Institute of Technology (KIT), where he has been working since 2007. His expertise lies in developing high-performance computing solutions for scientific experiments, with a focus on data acquisition systems, parallel computing architectures, and optimization of image processing software for scientific applications.

His educational background includes:

• PhD in Computer Science (2006) from the Institute for Informatics and Automation Problems of the National Academy of Science of the Republic of Armenia
• Diploma in Mechanics and Mathematics (2001) from Moscow State University, with thesis on neural networks

Dr. Chilingaryan's research spans high-performance computing, parallel hardware architectures, and scientific data management. He specializes in developing efficient algorithms for data acquisition and control systems, particularly for particle physics experiments. His current activities include high-speed data acquisition and control, management of large data, and optimization of image processing software for parallel computing architectures. He has pioneered techniques for GPU-accelerated data processing that enable real-time analysis of massive datasets from experiments like KATRIN (neutrino mass measurement), PANDA, and ASEC (Aragats Space Environmental Center).

His recent publications demonstrate a strong focus on neutrino physics, cosmic ray phenomena, and high-speed data acquisition systems. The integration of FPGA and GPU technologies in his research has enabled breakthroughs in real-time data processing for scientific experiments, particularly in synchrotron imaging and particle detection applications. His work bridges computer science and experimental physics, with particular emphasis on developing scalable infrastructure for managing and analyzing large scientific datasets.

Dr. Chilingaryan leads development of key software infrastructure including:

• UFO (Ultra fast X-Ray imaging platform) for smart experiments using GPU computing
• ADEI (Advanced Data Extraction Infrastructure) for time-series data management
• High-throughput DAQ Platform for FPGA-based scientific experiments

His technical leadership supports major international collaborations including KATRIN, PANDA, and ASEC, providing critical data management solutions that enable new types of scientific investigations across particle physics, astrophysics, and atmospheric science disciplines.