Michael G. Rabbat is a researcher at Facebook AI Research in Montreal, Canada, affiliated with the College of Engineering. His work spans machine learning, artificial intelligence, and distributed computing. Key research interests: Federated learning, reinforcement learning, self-supervised learning, and optimization algorithms. Recent publications focus on neural network training acceleration, physics understanding in AI, and efficient distributed systems. His articles from 2025–2022 emphasize robust visual features (DINOv2), communication-efficient training (SlowMo), and privacy-aware federated systems. Collaborative projects include V-JEPA for video modeling and IntPhys for physics benchmarks.
Paolo Sernani is an active researcher in the fields of Machine Learning , Artificial Intelligence , and Smart Home Systems , with over a decade of collaborative publications in computer science and biomedical informatics. His work appears in journals like IEEE Access , Computers in Medicine and Biology , and Applied Artificial Intelligence , as well as conferences including AmI , CBMS , and ETFA . Key collaborations include Aldo Franco Dragoni , Nicola Falcionelli , and Selene Tomassini .
Mariana Medina Sanchez is a leading Researcher at the Institute for Integrative Nanosciences (IIN) under the Leibniz Institute for Solid State and Materials Research Dresden (IFW Dresden). She has served as Group Leader of the Micro- and Nanobiomedical Engineering Group since 2016, following postdoctoral work at IFW-IIN (2014–2016). Her career spans roles at the Catalan Institute of Nanoscience and Nanotechnology (2010–2013) and as a Full-Time Assistant Professor at San Buenaventura University (2005–2009). Her research focuses on biohybrid microrobotics , integrating sperm cells with micro/nanotechnologies for targeted drug delivery and assisted reproduction . She has pioneered innovations in 3D/4D lithography , onboard sensors , and ultrasensitive bioimpedance platforms . Her work has been cited 3046 times with an h-index of 30 . Key publications include breakthroughs in ACS Nano , Nature Nanotechnology , and Advanced Functional Materials . She holds an ERC Starting Grant (2020–present) and has edited special issues on magnetic microrobots and small-scale swimmers . Teaching roles include Lectures on Micro- and Nanobiomedical Engineering at TU Chemnitz (2015–2021). She cofounded the National Nanoscience and Nanotechnology Council of IEEE-Colombia and contributed to 61 journal papers , 8 proceedings , and 55 invited talks globally. Notable awards include the ERC Starting Grant . Her work bridges robotics , materials science , and clinical translation , with emphasis on medical microbots , biohybrid systems , and smart biomedical devices . She actively collaborates across Germany , Spain , and Colombia , advancing ultrasensitive diagnostics and in vivo microrobot applications .
Professor Udo Frese is a faculty member at the University of Bremen, holding the position of Professor of Multisensory Interactive Systems since March 2014. He is associated with the German Research Center for Artificial Intelligence (DFKI) in the Cyber-Physical Systems department and is a member of the research focus 'Minds, Media, Machines'. University of Paderborn (1993-1997): Computer Science Friedrich-Alexander University Erlangen-Nuremberg (2004): Doctorate Professor Frese's research focuses on computer vision, sensor fusion through probabilistic modeling, and algorithms for safety functions with applications in robotics and interaction. His work spans multiple domains including assistive robotics for people with mobility limitations, SLAM (Simultaneous Localization and Mapping) techniques, and human-robot interaction systems. His research group collaborates with DFKI to operate the robot soccer team B-Human, which has achieved remarkable success with multiple world championships. His recent publications demonstrate a strong focus on assistive robotics, with particular emphasis on adaptive control systems for users with limited mobility. His work integrates computer vision, machine learning, and human-centered design principles to develop practical assistive technologies. The research spans from theoretical foundations in probabilistic modeling to practical implementations in real-world assistive applications. Best Technical Paper award at PETRA '24 for 'Probabilistic Combination of Heuristic Behaviors for Shared Assistive Robot Control' Best paper award at EICS 2024 for 'AdaptiX – A Transitional XR Framework for Development and Evaluation of Shared Control Applications in Assistive Robotics' Multiple world championships with robot soccer team B-Human Professor Frese advises several doctoral and master's students including Felix Goldau, Max Pascher, and Moritz Schneider, who contribute significantly to his research in assistive robotics and computer vision. His research is supported through collaborations with DFKI and various projects focused on assistive technologies and robotics. His laboratory at the University of Bremen collaborates closely with DFKI's Cyber-Physical Systems department, operating the successful robot soccer team B-Human. The research group maintains strong connections with both academic and industry partners to advance research in robotics and human-computer interaction.
Prof. Dr. Thomas Köhler is a full Professor of Educational Technology at the Faculty of Education, Dresden University of Technology (TU Dresden), and serves as the Director of the Center for Open Digital Innovation and Participation (CODIP). Since 2006 he has chaired the Faculty’s Doctoral Committee and since 2012 has directed the university’s Media Center, underscoring his sustained leadership in academic governance. Education & Academic Career While the precise degrees are not detailed in the provided text, his long-standing appointment as a chaired professor and extensive research leadership indicate a robust academic trajectory in educational technology and computer-supported learning. Research Interests His work lies at the intersection of educational technology , artificial intelligence in education , and open digital innovation . Key themes include: Technology-enhanced learning environments and instructional design AI-supported formative feedback and learning analytics Digital competency frameworks for engineering students Interdisciplinary approaches in engineering and media education Sustainable development strategies for higher-education institutions Publications & Research Impact Across 206 listed publications, a clear trend emerges: the integration of cutting-edge AI techniques into educational practice, rigorous evaluation of digital competencies, and the promotion of sustainable development goals within university strategies. His 2025 articles alone span nuclear-decommissioning AI applications, SDG-oriented university governance, and the design of measurement instruments for digital skills. Scientific Awards & Distinctions Although no specific awards are enumerated in the supplied text, his continuous appointment to leadership roles (Chairman of Doctoral Committee, Board Chair of GMW e.V., Spokesman of multiple networks) attests to high peer recognition. Projects, Grants & Networks He coordinates or leads several large-scale initiatives: H2020 MOVING project (management TU Dresden since 2016) AGILE PUBLIKA junior research group (project lead since 2017) eScience Research Network Saxony (spokesman 2011–2015) Leibniz Research Alliance Science 2.0 (spokesmen group member) Arbeitskreis eLearning of the Saxon Higher Education Conference (spokesman) Society for Media in Science (GMW e.V.), Chairman since 2012 Laboratories & Teams He heads the Chair of Educational Technology, whose team develops digital learning environments, conducts empirical studies on AI in education, and hosts visiting scholars. CODIP, the Center for Open Digital Innovation and Participation, operates under his direction, fostering interdisciplinary collaboration among technologists, educators, and social scientists.
Professor Janik Wolters is an ECDF-Professor for "Physical Foundations of IT Security" at Technische Universität Berlin, affiliated with the German Aerospace Center (DLR) and the Einstein Center Digital Future (ECDF). His research focuses on quantum communication security, quantum memories, and hybrid quantum systems. Wolters studied physics at TU Berlin and earned his doctoral degree in experimental physics from Humboldt-Universität zu Berlin. He worked in experimental quantum optics groups at Humboldt-Universität, TU Berlin, and the University of Basel. His research explores quantum memories, quantum light sources, and techniques to overcome the 100-kilometer limitation in quantum communication via quantum repeaters. Recent work includes mobile quantum memory systems, space-based quantum technologies, and machine learning integration in optical quantum memory experiments. Key article trends highlight advancements in quantum memory architectures, hybrid quantum systems combining semiconductor quantum dots with atomic vapors, and applications of quantum communication in space. His publications span quantum optics, quantum information theory, and experimental physics. Scientific awards include the Marie Skłodowska-Curie Individual Fellowship. He is based at the DLR Institute for Optical Sensor Systems and collaborates extensively with ECDF and international labs.
Debasree Das is a Research Assistant at the University of Bamberg , working under the Chair of Mobile Systems within the Faculty of Business, Information Systems and Applied Computer Science. She holds a Ph.D. in Computer Science and Engineering from Indian Institute of Technology, Kharagpur (2019-2024) and has held prior roles as a Teaching Assistant at IIEST Shibpur (2017-2018) and Associate at Cognizant Technology Solutions (2018-2019). Ph.D. in Computer Science and Engineering, IIT Kharagpur (2019-2024) M.Tech in Computer Science and Engineering, IIEST Shibpur (2016-2018) B.Tech in Computer Science and Engineering, West Bengal University of Technology (2012-2016) Her research focuses on data anonymization for intermodal trajectories, privacy-utility trade-offs , and ubiquitous computing in transportation systems. She explores spatiotemporal data modeling , contextual mobility analysis , and safety mechanisms for micromobility (e-scooters, bicycles) using causal inferencing and pervasive sensing techniques. Her work bridges human-computer interaction with urban mobility challenges , emphasizing differential privacy and dynamic road safety mapping. Recent publications highlight her contributions to privacy-preserving mobility analytics , causal modeling for driving behavior , and context-aware transportation systems . She has served as a co-organizer for IEEE TrustSense Workshop, Publicity Co-Chair for ICDCN 2026, and TPC member for multiple conferences including COMSNETS and IEEE AIoT. Best Paper Runner Up Award at IEEE MDM 2022 Second Winner Prize at IBM Maitreyee 2022 Institute Silver Medal at IIEST Shibpur 2018 Shri Dewang Mehta IT Award 2016 Inspire Award Warrant 2010 She supervises masters theses on mobility data anonymization and micromobility service optimization , contributes to projects like the Urban Data Platform for Bamberg , and is part of research groups including UbiNET and CNeRG . Her work integrates machine learning , sensor telemetry , and urban dynamics to address modern transportation challenges.
Adam Theo Müller serves as a researcher at Heilbronn University within the Faculty of Technology, affiliated with both the Interdisciplinary Center for Machine Learning (ZML) and the Research Laboratory for AI and Automated Driving. Holding a Master of Engineering degree, he actively contributes to research and teaching initiatives focused on autonomous systems and machine learning applications. His research expertise spans several critical domains in modern AI applications: Autonomous systems with specialized focus on perception systems and sensor fusion techniques Machine vision applications specifically designed for perception tasks in dynamic environments Cognitive robotics and embodied AI development Machine learning approaches for mobile robotic platforms and collaborative robots (cobots) Müller's recent publications demonstrate an interdisciplinary approach, applying machine learning to solve complex engineering challenges across aerospace systems, robotic interfaces, and advanced measurement methodologies. His work consistently bridges theoretical AI concepts with practical engineering implementations. He maintains an active role in academic supervision, mentoring numerous student projects including master's theses and research initiatives. These supervised works cover critical areas such as uncertainty quantification in perception systems, privacy-preserving techniques for autonomous vehicle data, multi-sensor integration, and digital twin development for campus infrastructure. Prior to his position at Heilbronn University, Müller developed professional experience across multiple sectors including mechatronics, aerospace engineering, and machine learning through various industry and research institution roles, establishing a robust interdisciplinary foundation for his current academic work.
Raphael Otte (M.Sc.) is a researcher at the Institute Future Energy (iFE) of the OWL University of Applied Sciences and Arts (TH OWL). He holds a Master's degree in Mechatronic Systems and a Bachelor's in Electrical Engineering/Automation Technology from TH OWL. His work focuses on power electronics for regenerative energy systems, efficiency-optimized switching power supply topologies, and wide-bandgap semiconductor-based prototype development. Key project involvements include: DC-Schiene (2023-2026): Intelligent DC networks for industrial energy efficiency DC INDUSTRY (2016-2019): Open DC networks with electric drives ZIM-PodCopter (2015-2017): Cable-suspended sensor platforms for agriculture E-DEAL (2010-2013): Energy-efficient electric drives with innovative power electronics He works in close collaboration with Prof. Holger Borcherding and specializes in technical building equipment (TGA) applications, particularly in energy-efficient industrial drive systems.
Markus Gehnen is a Professor of Electrical Systems and High-Voltage Engineering at TH Georg Agricola , with a focus on electrical engineering, information technology, and industrial engineering. He serves as Deputy Head of the Electrical Measurement Technology and Electrical Machines Laboratories, including Power Electronics. His research spans transformer monitoring, building automation in residential construction, and lighting technology. Education: RWTH Aachen (PhD in Electrical Engineering, 1993) Professional Timeline: AEG Lichttechnik (1993-1997), TH Georg Agricola (since 1998), Vice Rector (2005/06) His teaching includes electrical systems, high-voltage technology, and building systems technology. Publications emphasize lighting control systems, energy-efficient lighting, resonance phenomena in transformers, and integrated building management. He contributes to symposia on innovative lighting and transformer diagnostics. Key collaborations include Gharepetian (resonance analysis) and Möller (remote control systems). Research keywords: electrical engineering, building automation, high-voltage engineering, lighting technology. Affiliated with laboratories in electrical measurement and power electronics.
Denys J.C. Matthies is an Associate Professor at Technical University of Applied Sciences Lübeck and affiliated with Fraunhofer IMTE Lübeck . He specializes in Human-Computer Interaction , particularly focusing on Wearable Computing , Tactile Feedback Systems , and Activity Recognition through smart footwear and body-worn sensors. Key Collaborations: Augmented Human Lab (NUS), Fraunhofer IGD, City University of Hong Kong Research Themes: Smart wearables, haptic interfaces, physiological sensing, assistive technologies His recent work explores: PhantomFolds (2025) - Spatial tactile feedback via fingernail-mounted LRAs PAVES (2025) - Pneumatic terrain simulation in VR Cyber-Placebo (2024) - Ethical implications of fake-AI in CPHS He has contributed to smart footwear systems like ShoeTect2.0 (2024) and SurfSole (2024), integrating capacitive sensing with neural networks for real-time activity and surface recognition. His work spans medical applications (e.g., 2025 study on hepatic encephalopathy screening) and novel interaction paradigms (e.g., Kavy conversational AI 2024).
Professor Thomas Bergs serves as the Institute Director at the Department of Manufacturing Technology at RWTH Aachen University, Germany. He leads the Production Engineering Profile Area (ProdE) and serves as Speaker of the Steering Committee at the Production Cluster. His office is located at Campus-Boulevard 30, 52074 Aachen, Germany. Professor Bergs' research focuses on advanced manufacturing technologies with particular emphasis on: Tool wear analysis and prediction using computer vision and machine learning Ultra-precision grinding and metal cutting processes Digitalization of manufacturing through physics-informed operator learning Sustainable manufacturing practices and life cycle assessment Process chain optimization for aerospace components His recent publication trends show a strong focus on integrating artificial intelligence and data analytics into traditional manufacturing processes. He has published extensively on tool wear prediction, process optimization, and sustainable manufacturing approaches. His work bridges the gap between theoretical models and practical industrial applications, with particular emphasis on precision manufacturing for high-value components in aerospace and energy sectors. The research demonstrates methodological innovation in multi-sensor data fusion, reinforcement learning for process optimization, and digital twin applications. Professor Bergs has made significant contributions to the field through research on: Computer vision applications for tool condition monitoring Multi-sensor data fusion for quality prediction Physics-informed machine learning for material characterization Life cycle assessment of sustainable packaging solutions Digitalization of metallic materials through multiscale modeling
Dr. Guido Hüttemann is a Lecturer in the Department of Intelligence in Quality Sensing at RWTH Aachen University. His work focuses on integrating intelligent systems into quality control processes and sensor technologies. Role: Lecturer Institution: RWTH Aachen University Department: Intelligence in Quality Sensing His research interests include quality sensing applications in engineering and the development of intelligent systems for industrial monitoring and optimization.
Thomas Wiedemann serves as a post-doctoral researcher at the chair of 'Perception for Intelligent Systems' within the Munich Institute of Robotics and Machine Intelligence (MIRMI) at the Technical University of Munich (TUM), with additional affiliation to the Swarm Exploration Group at the German Aerospace Center (DLR). He earned his Bachelor's and Master's degrees in Mechanical Engineering from TUM (2012, 2014) and completed his Ph.D. in Computer Science at Örebro University, Sweden (2021) through the Center for Applied Autonomous Sensor Systems (AASS). His research centers on mobile robot olfaction and gas source localization , developing autonomous systems for chemical plume tracking using multi-robot coordination and environmental exploration strategies. This work bridges robotics, sensor networks, and artificial intelligence for applications in hazardous environment monitoring and disaster response scenarios. As part of DLR's Swarm Exploration Group at the Institute of Communications and Navigation, he contributes to advancing collaborative robotic exploration frameworks leveraging olfactory sensing capabilities.
Kuo-Yi Chao is a Researcher at the Chair for Robotics, Artificial Intelligence, and Real-Time Systems at the Technical University of Munich (TUM), focusing on multimodal sensor fusion for Vehicle-to-Everything (V2X) applications. He received his B.Sc. and M.Sc. in Electrical Engineering and Computer Technology from TUM. His expertise spans multi-agent systems, visual language models, real-time communication, and digital twin technologies. His 2022 publication in the Journal of NeuroEngineering and Rehabilitation highlights his work on intuitive control systems for robotic prostheses, emphasizing sensor fusion and human-robot interaction. He contributes to teaching through courses like 'Einführung in die digitale Signalverarbeitung (IN2061)' and offers thesis topics in collaborative camera perception, real-time V2X data transmission, and object list generation for autonomous systems.
