Multi-Static Radar Systems Professors and Supervisors

Christian CreßView profile

Researcher

Technical University of MunichGermany

Christian Creß is a Research Assistant and Ph.D. candidate at the Technical University of Munich (TUM), working at the Chair of Robotics, Artificial Intelligence and Real-Time Systems under the supervision of Prof. Dr.-Ing. habil. Alois Christian Knoll. He joined TUM in 2020 after completing his M.Sc. in Applied Computer Science at the University of Applied Sciences Kempten in 2016. Creß holds a Master of Science degree in Applied Computer Science from the University of Applied Sciences Kempten, where he completed his thesis titled "Visual Scene Analysis for the Segmentation of Static and Dynamic Objects" in collaboration with ESG Elektroniksystem- und Logistik-GmbH. Prior to his position at TUM, he worked as a software developer in the industry. His research focuses on computer vision, particularly with event-based cameras, within the context of intelligent transportation systems. Creß has established the complete perception pipeline for the Providentia++ roadside intelligent transportation system, covering calibration, object detection, and data fusion. His work bridges theoretical computer vision research with practical applications in autonomous driving and traffic monitoring systems. He has published extensively on topics including sensor calibration, event-based vision, and multi-modal perception for intelligent transportation infrastructure. Creß has contributed significantly to the AUTOtech.agil and Providentia++ projects, prestigious research initiatives in the field of intelligent transportation. His publications demonstrate a strong focus on practical computer vision solutions for roadside infrastructure, with particular expertise in event-based cameras, sensor calibration, and multi-modal perception systems. His most cited works include literature surveys on roadside ITS infrastructure and datasets like TUMTraf Event that have become valuable resources for the research community. As a thesis supervisor, Creß has mentored numerous Master's and Bachelor's students through their research projects, covering topics such as radar-based instance segmentation, camera-based object detection in poor visibility conditions, deep learning for rain removal, and traffic trajectory prediction. His students have completed works on accident prevention frameworks, self-diagnosis functionality for ITS, and synthetic data generation using GANs.

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Hongjian SunView profile

Professor

Durham UniversityUnited Kingdom

Hongjian Sun is Professor and Director of Research in Smart Grid at Durham University's Department of Engineering, where he leads the Durham Smart Grid Laboratory. He earned his Ph.D. from the University of Edinburgh and held postdoctoral positions at King's College London and Princeton University. Sun's research encompasses: Demand response and virtual power plant optimization Electric vehicle charging infrastructure management Smart grid communications and IoT integration Renewable energy-grid interface solutions His publications demonstrate consistent focus on energy system digitalization, with recent advancements in digital twins for virtual power plants, reinforcement learning for grid management, and integrated sensing-communication systems. Research integrates theoretical frameworks with practical implementations in microgrid optimization and EV-grid integration. Sun has secured significant research funding from EU H2020, EPSRC, and UK government programs for projects including TESTBED2 (€1.4M), CHEDDAR (£3M), and VPP-WARD (£1.84M). These initiatives develop solutions for grid decarbonization and renewable integration. Honors include Fellowship of Durham Energy Institute and Higher Education Academy. Sun serves on editorial boards for IET Smart Grid and IEEE Transactions on Industrial Informatics, and organizes leading conferences in smart grid communications.

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Bernhard RabusView profile

Professor

Simon Fraser UniversityCanada

Bernhard Rabus is a Professor and holder of the Industrial Research Chair in Synthetic Aperture Radar (SAR) at Simon Fraser University's School of Engineering Science. His work focuses on SAR technologies, with emphasis on maritime applications and novel land applications using multi-channel SAR systems. He leads the SARlab and collaborates with institutions like IEEE. Rabus earned his Ph.D. in Geophysics from the University of Alaska Fairbanks and an M.Sc. from the Technical University of Munich. His research integrates advanced interferometric and polarimetric techniques to study glaciers, landslides, and environmental dynamics. Recent projects include landslide deformation analysis, glacier motion tracking, and SAR-based wildlife monitoring. Rabus teaches graduate courses like ENSC895/EASC609 and advises students on SAR applications. His work is funded through industrial and academic partnerships, addressing challenges in geohazard monitoring and remote sensing innovation. Education: Ph.D., Geophysics, University of Alaska Fairbanks (1997); M.Sc., Technical University of Munich (1992) Affiliations: IEEE, SARlab Director Labs/Teams: SARlab, collaborating with NASA, ESA, and industry partners Research Highlights: Rabus pioneers SAR applications for maritime domain awareness, landslide prediction, and glacier dynamics. His team develops novel algorithms for interferometric analysis and airborne SAR systems. Recent studies include Fels Slide displacement tracking and Arctic ice cap stability assessments. Outcomes contribute to disaster risk reduction, climate science, and environmental policy. Awards: Industrial Research Chair in SAR (SFU), recognized for advancing SAR technology in geoscience and engineering. Grants/Projects: Funded by NSERC, NASA, and industry partnerships for SAR sensor development and environmental monitoring initiatives.

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Dejan GjorgjevikjView profile

Professor

University of SkopjeMacedonia

Dejan Gjorgjevikj is a Full Professor at the Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University in Skopje. He joined the Department of Computer Science and Engineering in 1992, progressing from Assistant Professor (2004) to Associate Professor (2009) before attaining full professorship in 2014. His international academic engagements include research visits to institutions in Austria, Bulgaria, the Czech Republic, and the UK. Education: Bachelor's and Master's degrees from the Faculty of Electrical Engineering, Skopje (1992, 1997); PhD from the same institution (2004). Research Focus: His primary research explores pattern recognition, machine learning, and software engineering. Recent work emphasizes applications in industrial diagnostics (fault detection in machinery), blockchain security (Ponzi scheme detection), environmental monitoring (air pollution prediction), and human-computer interaction (sensor-based activity recognition). Methodologies frequently involve deep learning architectures like autoencoders, LSTMs, and adversarial networks. Publication Trends: Gjorgjevikj has authored over 90 publications, with recent works demonstrating increased focus on neural network applications in cross-domain problems (mechanical engineering, finance, IoT) and NLP tasks like sarcasm detection. His articles frequently appear in IEEE, Springer, and Elsevier journals. Awards: AAIA’15 Data Mining Competition Award (2015) Projects & Service: Involved in 10+ international/domestic research projects IEEE member since 1991, ACM member since 1997 Program committee member for multiple international conferences

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Klen Čopič PuciharView profile

Associate Professor

University of PrimorskaSlovenia

Dr. Klen Čopič Pucihar serves as Associate Professor at the Faculty of Mathematics, Natural Sciences and Information Technologies (FAMNIT) at the University of Primorska in Koper, Slovenia. He holds multiple leadership roles including Department Chair of Information Sciences and Technologies, Deputy Chair of HICUP Lab, and Study Programme Coordinator for the Doctoral Computer Science program. His research centers on Human-Computer Interaction with particular emphasis on: Augmented, Mixed, and Virtual Reality systems Micro-gesture recognition using radar sensing (e.g., Google Soli) Paper interfaces and augmentation of physical media AR for educational applications, particularly vocabulary learning Addressing the 'dual-view problem' in handheld AR systems Dr. Čopič Pucihar's work is driven by the vision to 'unclog the bottleneck' between humans and digital information. His recent publications (2019-2025) show a strong trajectory from theoretical interaction techniques toward practical educational applications and novel input methods using radar sensing, with consistent output in top venues including CHI, ISS, MobileHCI, and ISMAR. His notable achievements include: Best Paper Award at ACM IUI 2025 Honorable Mentions at ACM EICS 2022 and ACM ISS 2022 Best Poster Award at ISMAR Multiple hackathon victories including at Columbia University As Study Programme Coordinator for Doctoral Computer Science, Dr. Čopič Pucihar mentors graduate students and shapes research directions. His HICUP Lab hosts an international research group focused on making digital interfaces more intuitive and effective for human use through advanced sensing methods and personalized services. HICUP Lab leverages techniques from data mining, machine learning, computer vision, and human perception to develop interfaces that function as extensions of human minds, bodies, and behavior, with the ultimate goal of enabling 'digital augmentation of human abilities to its fullest potential.'

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