Johannes Balling is a Postdoc researcher at the Laboratory of Geo-information Science and Remote Sensing, Wageningen University. His work focuses on tropical forest monitoring using satellite remote sensing, particularly integrating Synthetic Aperture Radar (SAR) and optical data to detect forest disturbances. He has contributed to projects analyzing deforestation patterns in regions like Indonesia and the Amazon, leveraging tools like Google Earth Engine for large-scale data analysis. Research Interests: Tropical forest dynamics, SAR applications, deforestation detection, multi-source satellite data fusion. Recent work emphasizes timeliness and accuracy in disturbance mapping through innovative combinations of radar and optical sensors. Collaborations include projects with researchers like Herold and Reiche, focusing on fire-related forest changes and real-time monitoring systems. His PhD thesis (2024) explored temporally-dense satellite remote sensing for tropical forest monitoring. He has published widely on SAR-based methods and their application to environmental challenges.
Peter Baltus is Full Professor of High-Frequency Electronics in the Department of Electrical Engineering at Eindhoven University of Technology. With industry experience at Philips/NXP and academic credentials from TU/e, his research focuses on high-frequency integrated circuit and system design. Research domains include: Ultra-low power transceivers Millimeter-wave wireless power transfer Efficient wideband beamforming Sensor swarm networks RF system architecture His educational contributions feature innovative RF laboratory designs for remote learning environments. Current projects include photonic-electronic integration and satellite communication systems.
Marion K. Matters-Kammerer is a Full Professor of Electrical Engineering at Eindhoven University of Technology, leading research in terahertz (THz) and millimeter-wave systems. She holds positions in the Center for Wireless Technology, THz Electronics and Integration Lab, and RF Sensing & Communication Lab. Her expertise includes integrated circuits, antenna design, and power amplifier systems. She has led EU projects like 3DmicroTune and ULTRA, and co-authored over 70 journal/conference papers with 13 US patents. Education: MSc in Physics from École Normale Supérieure (Paris) and TU Berlin (1999), PhD in Physics from RWTH Aachen (2007). Past roles include Senior Scientist at Philips Research (1999–2011) and Guest Professor at RWTH Aachen (2009–2010). Research focuses on THz spectroscopy, mm-wave integrated circuits, and energy-efficient wireless systems. Key projects involve THz biosensing, 60 GHz sensor networks, and co-integration of photonics and electronics. Her work addresses UN SDGs like affordable and clean energy, and industry-academia collaboration via NXP Smart Mobility projects. Recent articles highlight advancements in mm-wave power amplifiers, waveguide integration, and radar signal processing. Grants include €2.5M for TeraIBs (2025–2028) and €1.8M for Future Wireless Interfaces (2024–2029). Labs include THz Electronics Lab and RF Sensing Team, advancing sensor and communication technologies.
Alexander Yarovoy is a Full Professor at the Faculty of Electrical Engineering, Mathematics and Computer Science at Delft University of Technology (TU Delft), specializing in Radar Systems, Antenna Design, and mm-Wave Technology. His research bridges theoretical and applied domains, with a focus on automotive radar, weather radar, and machine learning integration in radar signal processing. Active in radar, antennas, and microwave engineering Key contributions to automotive radar and human activity recognition Collaborates on datasets like RaDelft for autonomous driving Recent work explores OTFS radar for communication integration, polarimetric calibration, and high-resolution imaging algorithms. His research often addresses challenges in real-world applications, such as urban meteorology and vehicular safety. In 2023, he received the outstanding paper award at IEEE MetroAeroSpace for radar waveform coexistence studies. He participates in conferences and editorial activities, advancing radar metrology and phased array technologies.
O. Cats is a Professor of Passenger Transport Systems and Head of the Department of Transport & Planning at Delft University of Technology (TU Delft). They also serve as a Guest Professor at KTH Royal Institute of Technology. Their research focuses on multi-modal passenger transport networks, combining simulation, operations research, behavioral sciences, and complex network theory to address challenges in public transport, shared mobility, and long-distance travel dynamics. Key interests include network robustness, service operations, and passenger demand modeling. Dr. Cats leads the Smart Public Transport Lab at TU Delft, collaborating closely with transport authorities and operators. They hold editorial roles at journals like the Journal of Public Transportation and have received prestigious grants, including the ERC Starting Grant for the CriticalMaaS project. Awards include recognition for work on crowding valuation in urban transport systems. Recent publications emphasize optimization of electric vehicle infrastructure, sustainability in travel behavior, and dynamics of ridesourcing markets. Their work bridges theoretical research with practical applications, aiming to enhance transport efficiency and sustainability globally.
Jan Bergmans is a Full Professor in the Department of Electrical Engineering at Eindhoven University of Technology (TU/e). He leads the Signal Processing Systems group and holds professorships at multiple research centers including the Eindhoven MedTech Innovation Center (e/MTIC), Center for Care & Cure Technology Eindhoven, NeuroPlatform, EAISI Health, and EAISI Foundational. With approximately 35 years of experience in signal processing theory and applications, Bergmans focuses on developing computationally efficient signal analysis techniques for healthcare, wireless communication, surveillance, and intelligent lighting applications. Bergmans' educational background includes: MSc in Electrical Engineering from Eindhoven University of Technology (1981) PhD in Electrical Engineering from Eindhoven University of Technology (1987) His research interests center around signal processing and data analytics theories, algorithms, architectures, and systems. Bergmans develops mathematical models that incorporate domain-specific knowledge, such as propagation models for radio communication channels or pathophysiological models for clinical decision support systems. His work emphasizes creating powerful yet computationally efficient signal analysis techniques, with significant applications in healthcare technology and medical diagnostics. The integration of engineering principles with clinical needs is a hallmark of his research approach, enabling practical solutions that address real-world medical challenges. Analysis of Bergmans' recent publications reveals a strong focus on medical signal processing, particularly in ECG and fetal monitoring applications. His work combines advanced signal processing techniques like adaptive Kalman filtering with practical healthcare applications. There's also significant research in visible light communications and sensor network technologies, showing the breadth of his expertise across different application domains of signal processing. The consistent theme across his work is developing computationally efficient algorithms that incorporate domain-specific knowledge to solve practical engineering problems. Scientific recognition includes: Senior Member of the IEEE Author of numerous papers and 2 books Holder of approximately 40 US patents Bergmans has established smooth collaborations with strategic industrial and clinical partners, including Philips Research and multiple hospitals in the Eindhoven region. He co-manages BrainBridge, the strategic collaboration between TU/e, Philips Research, and Zhejiang University (China). His research group has secured numerous projects, including recent third-tier projects like MEDEIA, PISANO SPS, and RAISE projects focusing on medical engineering innovations and robust AI for radar signal processing. As a key figure in the Signal Processing Systems group and one of the founders of the Eindhoven MedTech Innovation Center (e/MTIC), Bergmans plays a central role in bridging academic research with industrial and clinical applications. His leadership extends to managing multiple research teams working on healthcare technology, wireless communications, and sensor systems, fostering an environment where theoretical signal processing advances translate into practical medical and technological solutions.
Ling Chang is an Associate Professor at the University of Twente, affiliated with the Faculty of Geo-Information Science and Earth Observation (ITC) and the Department of Earth Observation Science. She holds a Ph.D. from Delft University of Technology (2015) and an M.S.E. from Tongji University (2010). Her research focuses on statistical hypothesis testing, time series modeling, and change detection using satellite remote sensing, particularly InSAR techniques. Key projects include AlignSAR (ESA Open SAR library) and RailRadar (TUDelft-ProRail collaboration). Education: M.S.E. in Geodesy and Survey Engineering, Tongji University, China (2010) Ph.D. in Geodesy, Delft University of Technology, Netherlands (2015) Research interests emphasize InSAR applications in infrastructure monitoring, environmental geology, and disaster risk assessment. Notable achievements include the Prof. J.M. Tienstra Research Prize (2022) and leadership in the NCG talent program (2020). Teaching responsibilities include coordinating the Radar Remote Sensing course. Her work contributes to UN SDGs related to sustainable infrastructure and climate action.
Alessandro Chiumento is an Assistant Professor at the Department of Pervasive Systems, Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS), University of Twente. His research focuses on artificial intelligence, edge AI, wireless communication, and sensor systems for industrial and health applications. Key Research Areas: Reinforcement Learning, Deep Learning, 5G/6G Networks, Human Activity Recognition Recent publications highlight his work in mmWave radar systems for vital sign monitoring, UAV-based communication networks, and AI-driven resource management for IoT. He has contributed to 5G-RedCap optimization, WiFi network performance analysis, and biomedical sensor development. In 2024-2025, his team released comprehensive datasets for mmWave radar applications, explored non-invasive animal health monitoring, and advanced cross-layer QoS optimization frameworks. Earlier works (2016-2023) addressed Bluetooth mesh networking, LTE interference management, and multi-antenna systems for UAVs. Technical Themes: Spectrum Efficiency, Network Topology, Channel Quality Prediction, Autonomous Agents
C. Silveira Vaucher is a Professor specializing in Electrical Engineering, Mathematics, and Computer Science. Their research focuses on advanced radar systems, waveform engineering, and satellite communication technologies. Recent work emphasizes automotive radar interference mitigation and MIMO radar coherence. Active in Automotive Radar and Frequency Modulated Continuous Wave engineering Contributions to MIMO Radar and Small Satellite transmitter design Their publications highlight trends in joint sensing-communication systems and phase-coded waveforms for improved radar performance. Collaborations span international research institutions, particularly in interference analysis and coherent signal processing.
Herman Russchenberg is a Professor at the Delft University of Technology in the Civil Engineering & Geosciences school, specializing in Atmospheric Remote Sensing . With over 229 research outputs and 49 media engagements, his work bridges cutting-edge climate science and public discourse. Key Affiliations : TU Delft Climate Institute, Refreeze the Arctic Foundation collaborator Research Interests center on Atmospheric remote sensing technologies Cloud dynamics and calibration methodologies Climate engineering (e.g., cloud brightening) Aerosol-cloud interaction impacts Weather radar systems . Recent projects include 94 GHz radar calibration and balloon-borne aerosol-cloud studies, advancing understanding of natural and engineered climate solutions. Scientific Recognition : 2017 Finalist for Best Paper Award, European Conference on Antennas and Propagation Public Engagement includes 7 media contributions in 2024 alone, addressing topics like cloud seeding, desert sand climate interventions, and solar radiation modification ethics. His 2023 editorial in Oxford Open Climate Change sparked debates on geoengineering risks and policy implications.
Ruud J.G. van Sloun is an Associate Professor in the Signal Processing Systems group within the Department of Electrical Engineering at Eindhoven University of Technology (TU/e). His research focuses on advanced sensing and signal processing algorithms, particularly deep learning methods for medical imaging applications such as ultrasound and MRI, as well as automotive radar. He holds a MSc and PhD in Electrical Engineering from TU/e, both awarded cum laude. He is affiliated with the Eindhoven MedTech Innovation Center and EAISI Health, collaborating with industry partners like Philips Research and Onera. Education: MSc (2014, cum laude) and PhD (2018, cum laude) in Electrical Engineering from TU/e. Research interests include deep learning for image reconstruction, probabilistic signal processing, and model-based approaches. His work contributes to UN Sustainable Development Goals related to healthcare innovation. Notable grants include ERC Starting Grant, NWO VIDI, and Google Faculty Research Award. He has supervised 17 research projects and authored over 200 publications.
Dr. Gabriele Federico is an Assistant Professor in the Electromagnetic Group at Eindhoven University of Technology (TU/e). He holds a PhD in Electrical Engineering from TU/e (2023) and advanced degrees from the University of Bologna. His research focuses on antenna array design for mm-wave wireless communications, antenna measurements, and RF material characterization. He collaborates with industry partners like The Antenna Company and XLIM Research Institute. Education: PhD in Electrical Engineering, TU/e (2019–2023) P.D.Eng. (Postgraduate Design Engineer), TU/e (2016–2018) M.Sc. in Telecommunications Engineering, University of Bologna (2013–2016) B.Sc. in Electronic and Telecommunications Engineering, University of Bologna (2010–2013) Research Interests: His work emphasizes antenna array optimization for 5G/5G+ systems, dielectric material characterization at mm-wave frequencies, and reconfigurable antenna elements for wide-angle scanning. Key innovations include open hemispherical resonant cavities for material measurements and multi-mode antenna designs. Awards: EuMA Internship Award 2023 IEEE AP-S/URSI 2022 Honorable Mention Award Grants & Projects: He leads the Synthetic Polymer-Based Antenna Array Technology project (2019–2025), focusing on 5G+ communication solutions. His work bridges academia and industry, addressing challenges in antenna miniaturization and performance enhancement. Labs & Teams: Active in the Electromagnetic Group and EM Antenna Systems Lab at TU/e, collaborating with global partners like XLIM (France) and The Antenna Company (Netherlands).
Harijot Singh Bindra is an Assistant Professor in the field of Integrated Circuit Design. His research focuses on analog and mixed-signal circuit design, with a strong emphasis on data converters, low-power electronics, and high-speed signal processing. He has contributed to advancements in ADC architectures, delta-sigma modulators, and radar systems. His work spans technologies like CMOS and FDSOI, addressing challenges in energy efficiency, noise reduction, and high-frequency operations. Notable research areas include sub-sampling ADC front-ends, programmable frequency translators, and latch-based circuits. His publications span IEEE journals and conferences, with contributions to both academic and applied domains. Bindra has also been involved in patent development, including a notable invention related to latch circuitry. His research aligns with applications in telecommunications, radar systems, and agricultural monitoring. Key collaborators include prominent figures like Bram Nauta and Erik Klumperink. Despite no listed student advisees or explicit grants, his prolific output since 2013 reflects sustained engagement in cutting-edge circuit design and signal processing.
Franz Lampel is a Research Fellow at Eindhoven University of Technology's Signal Processing Systems department. He holds a B.Sc. (2015), M.Sc. (2018) from Graz University of Technology, and a Ph.D. (2024) from TU/e. His research focuses on signal processing for joint communication and sensing, waveform design, and radar-communication integration, particularly in automotive applications. He contributes to projects like IT-JCAS (2024–2028) and DIGI-OPT (2018–2026). Education: Bachelor's in Electrical Engineering, Graz University of Technology (2012–2015) Master's in Electrical Engineering, Graz University of Technology (2015–2018) Ph.D. in Joint Radar and Communication Techniques for Automotive Applications, TU/e (2024) Research interests include waveform design for radar-communication coexistence, dispersive channel equalization (e.g., OTFS modulation via Zak transforms), and FMCW radar signal processing. His work bridges theoretical signal processing with practical automotive and communication systems. Recent publications address OTFS equalization, radar dispersion compensation, and OFDM waveform optimization. He collaborates on projects like the Integrated Cooperative Automated Vehicles initiative (2016–2021), focusing on automotive radar systems. His lab affiliations include the Information and Communication Theory Lab at TU/e.
Hossein Aghababaei is an Assistant Professor at the Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente. He specializes in synthetic aperture radar (SAR) data analysis, with a focus on Polarimetric SAR (PolSAR) and SAR tomography (TomoSAR) for 3D forest structure investigation. Research Focus: SAR tomography applications in forestry, remote sensing, and Earth observation. Expertise: Earth and Planetary Sciences, Computer Science, Engineering (Scatterer detection, SAR image modeling). He is affiliated with the Department of Earth Observation Science (ITC-EOS) and the Digital Society Institute.
