Professor Piotr Małka is affiliated with the Krakow University of Technology as a faculty member in the Department of Infotronics and Cybersecurity under the Faculty of Electrical and Computer Engineering . His work focuses on robotics, mechatronics, and infrastructure monitoring. Academic Rank: Professor Contact: piotr.malka@pk.edu.pl Research interests span mobile robot design for pipeline inspection , SLAM techniques in rough terrain, and intelligent infrastructure systems. His publications demonstrate expertise in: Robot kinematics and dynamics Control systems for tracked robots Structural health monitoring Smart water supply infrastructure Virtual prototyping of inspection systems Recent work shows increasing focus on autonomous navigation and cyber-physical systems integration for industrial applications.
Pascal Vasseur is a University Professor at the University of Picardie Jules Verne (UPJV) in the Faculty of Sciences, Computer Science Department. He leads the Robotics Perception group within the MIS Laboratory (Modeling, Information and Systems) and serves as a member of the National University Council (Section 61) since 2016. Additionally, he has been an Associate Editor for IEEE Robotics and Automation Letters since 2016, demonstrating his significant standing in the robotics research community. Professor Vasseur's research focuses on robotics perception systems, with particular expertise in vision (including omnidirectional and event-based cameras), Lidar, and Radar technologies. His work addresses fundamental challenges in pose estimation, mapping, and localization for robotics and automotive applications. His recent publications show a strong emphasis on advanced sensor technologies, multi-sensor calibration techniques, and practical implementations for autonomous systems. His publication record demonstrates consistent high-impact research output, with numerous articles in top robotics and computer vision venues including IEEE Robotics and Automation Letters, IEEE Transactions on Intelligent Vehicles, and CVPR. He has also authored two comprehensive books on Omnidirectional Vision (2023-2024), establishing himself as a leading expert in this specialized area of computer vision. Professor Vasseur has coordinated multiple significant research projects including ANR projects CaViAR and pLaTINUM, the international DrAACaR project, and PHC STAR and AMADEUS projects. He currently serves as scientific officer for the ANR CLARA Project, continuing his leadership in advancing robotics perception research. His research group actively contributes to solving practical challenges in automotive vision systems, drone navigation, and forest environment mapping, with applications spanning autonomous vehicles, robotics navigation, and environmental monitoring systems. The group's work bridges theoretical advances in computer vision with real-world robotics implementations.
Myriam Servières is a Professor of Computer Science at Centrale Nantes, where she has taught since 2006. She currently serves as Director of AAU-CRENAU and Deputy Director of the AAU Laboratory. Her academic journey includes a PhD in Applied Computer Science from the University of Nantes (2002-2005) and an engineering diploma from École Centrale de Nantes (1999-2002). Her research explores the intersection of digital technology and urban environments, with key interests in: Geolocation : Developing advanced positioning systems for urban navigation Augmented/Virtual Reality : Creating multisensory urban simulations 3D Modeling : Reconstructing and analyzing urban spaces Citizen Sensing : Engaging communities in environmental monitoring Her recent publications demonstrate strong focus on VR-based urban perception analysis, pedestrian navigation systems, and geospatial data processing. Work frequently appears in premier journals like ISPRS and IEEE Transactions . She leads significant initiatives including the IRSTV 'Urban Tomography' research axis and the '3D geospatial data' prospective action. Her teaching spans core computer science courses and specialized programs in digital cities. At AAU-CRENAU, she directs research on computational urban analysis, collaborating across disciplines to develop new methods for understanding and designing urban spaces through digital mediation.
Torsten Sattler is a Senior Researcher at the Czech Institute of Informatics, Robotics and Cybernetics (CIIRC) at the Czech Technical University in Prague (CTU), where he heads the Spatial Intelligence group. Previously, he was a tenured Associate Professor at Chalmers University of Technology in Sweden and spent five years as a PostDoc and Senior Researcher at ETH Zurich in Switzerland. He received his PhD from RWTH Aachen University in Germany. His research focuses on the intersection of 3D computer vision and machine learning, with specific interests in image-based localization, 3D mapping and reconstruction, neural scene representations, and applications in robotics and AR/VR. He aims to make localization and mapping algorithms more robust by incorporating higher-level scene understanding. Dr. Sattler has published extensively at top computer vision conferences including CVPR, ICCV, and ECCV, with recent papers focusing on robust visual localization in changing environments, neural scene representations, and 3D reconstruction. His work has direct applications in autonomous systems and augmented reality. Best Paper Candidate at CVPR 2021 Best Paper Award at Photogrammetric Image Analysis 2019 Multiple Outstanding Reviewer Awards from 2015-2021 Ranked among top-10 computer scientists in Czech Republic by Research.com He currently supervises five PhD students and has served in various leadership roles including program chair for ECCV 2024, general chair for 3DV 2022, and area chair for multiple major conferences. His lab benefits from connections to the RICAIP Centre, one of the largest EU projects in AI and Industry 4.0, providing access to state-of-the-art infrastructure and industrial collaborations.
Felipe Ramón Fabresse is a Researcher at the Service Robotics Laboratory (SRL - TIC255) within the University of Seville, Spain, specializing in robotics with emphasis on aerial systems and navigation technologies. His work operates under the broader domain of Information and Communication Technologies (ICT), focusing on practical robotic applications for real-world service environments. He earned his PhD from the University of Seville in 2017 with the thesis "A multi-hypothesis approach for range-only simultaneous localization and mapping with aerial robots," supervised by Dr. Aníbal Ollero Baturone and Dr. Fernando Caballero. This research pioneered methods for autonomous aerial vehicle navigation using sparse range measurements, addressing critical challenges in sensor-limited scenarios. His core research interests include: Robotics Aerial Robotics Simultaneous Localization and Mapping (SLAM) Service Robotics Information and Communication Technologies The Service Robotics Laboratory provides a collaborative framework for advancing robotic perception, control, and human-robot interaction. While specific grant details are unreported, the lab's alignment with ICT research indicates active development of deployable robotic solutions for industrial and service applications.
Prof. Dr.-Ing. Andreas Wenzel is a Professor at Schmalkalden University of Applied Sciences in the Faculty of Electrical Engineering, specializing in Embedded Systems. His office is located in Building M, Room 0401, and he can be reached at +49 3683 688 5113. With a distinguished research career spanning over two decades, Prof. Wenzel has established himself as a leading expert in embedded diagnostic systems with applications across multiple domains including biomedical engineering, industrial automation, and assistive technologies. Prof. Wenzel's primary research interests focus on the development and application of embedded diagnostic systems, with particular emphasis on neural networks for pattern recognition, fuzzy logic systems for classification problems, and real-time monitoring solutions. His work bridges theoretical machine learning approaches with practical engineering applications, resulting in innovative solutions for quality control in manufacturing processes, medical diagnostics, and mobility assistance technologies. He has made significant contributions to EEG data analysis for sleep stage and anesthesia depth monitoring, as well as developing smart systems for injection molding quality assessment and advanced mobility solutions for elderly individuals. Analysis of Prof. Wenzel's publication record reveals a consistent research trajectory focused on applying computational intelligence to solve practical engineering problems. His work demonstrates exceptional versatility across domains while maintaining a cohesive research theme centered on embedded diagnostic systems. From 2012-2016, his research output shows increasing focus on real-time embedded solutions with industrial applications, particularly in manufacturing quality control and assistive technologies, while continuing his foundational work in biomedical signal processing. The interdisciplinary nature of his research is evident in collaborations with medical professionals, industrial partners, and robotics specialists. Prof. Wenzel leads the Embedded Diagnostic Systems Research Group at Schmalkalden University of Applied Sciences, which maintains strong industry partnerships, particularly in plastics manufacturing and medical technology sectors. His team develops practical embedded solutions that address real-world challenges in production quality monitoring, medical diagnostics, and mobility assistance. The research group's work is characterized by its practical orientation, with many projects resulting in deployable systems rather than purely theoretical contributions. Prof. Wenzel's strategic focus on applied research ensures that his work has direct industrial relevance and practical impact.
Thanh Nguyen Canh is a Lecturer at University of Engineering and Technology, Vietnam National University (UET VNU) and Teaching/Research Assistant at Japan Advanced Institute of Science and Technology (JAIST), School of Information Science. Primary affiliation is with the Robotics Lab at both institutions where he conducts research in SLAM systems and computer vision. PhD in Information Science at JAIST (2024.10-present) MS in Information Science at JAIST (2022.9-2024.9) BS in Robotics Engineering at UET VNU (2018.8-2022.8) Research focuses on advancing SLAM technologies through semantic understanding and active exploration. Key specialties include Visual-inertial odometry , probabilistic semantic mapping , and multi-sensor fusion for UAV navigation. Current projects integrate deep learning with traditional SLAM pipelines to create robust environmental representations. Publication activity centers on practical robotics applications, with the 2023 ICCAIS paper demonstrating object-oriented semantic mapping for UAV navigation. Research output emphasizes implementable solutions with active GitHub repositories showing continuous development in SLAM systems and reinforcement learning. Supervision involves teaching robotics curriculum at UET while mentoring research assistants at JAIST. Current projects provide hands-on experience with ROS, point cloud processing, and deep learning frameworks. Laboratory work occurs within the Robotics Lab environment at JAIST/UET, utilizing GitHub-hosted tools like probabilistic_semantic_mapping and S3M_SLAM for collaborative development. The lab maintains strong focus on real-world robotics applications with particular emphasis on aerial vehicle navigation systems.
Adriano Jorge Cardoso Moreira is an Associate Professor with Habilitation at the Department of Information Systems, School of Engineering, University of Minho, Portugal. He holds multiple leadership roles including Scientific Coordinator of Urban Computing at Centro de Computação Gráfica and Director of the MAP-tele PhD Program. His research is conducted primarily through the Urban Computing Lab , focusing on smart place technologies. Education: PhD in Electrical Engineering (1997) and Bachelor's in Electronic and Telecommunications Engineering (1989), both from University of Aveiro, Portugal. Research Focus: His work spans indoor positioning, mobile/context-aware systems, urban computing, and wireless network simulation. Key innovations include fingerprinting algorithms for localization, multi-sensor fusion techniques, and human mobility analysis. Research outputs consistently address real-world industrial challenges such as warehouse management, factory automation, and urban infrastructure. Research Output Trends: Recent publications (2021-2023) emphasize practical applications of Wi-Fi/LoRaWAN fingerprinting, machine learning for sensor calibration, and industrial vehicle tracking. Over 70% of recent works involve experimental validation in real environments, reflecting a strong applied research focus. Key thematic clusters include radio map optimization, multi-sensor datasets, and scalability of positioning systems. Awards & Recognition: First Prize, EvAAL-ETRI Indoor Localization Competition (Off-site track, 2015 & 2017) Second Prize, EvAAL-ETRI Indoor Localization Competition (2016) IEEE Senior Member status Patent in computational geometry Projects & Funding: He leads/participates in numerous EU/national projects including: ORIENTATE (2021-2023): Low-cost indoor positioning for factories Lab4U&Spaces (2021-2023): Urban space solutions AR WARE (2018-2022): AR for warehouse management SAMU (2015-2018): Smart autonomous mobile units Lab & Team: He established/leads the Urban Computing Lab developing technologies for smart environments. Previously headed the Computer Communications and Pervasive Media Group (until 2016). Current team includes PhD/Master students working on wireless positioning and mobility analysis.
Prof. Reiner Marchthaler is a Professor at Esslingen University of Applied Sciences within the Faculty of Computer Science and Information Technology. He serves as Deputy Director of the Institute for Intelligent Systems (IIS), Scientific Director of the Green IT 2026 Conference, and Liaison Lecturer for the Friedrich Ebert Foundation. His academic leadership spans autonomous systems research and educational initiatives in embedded technologies. His research centers on Embedded Systems and Sensor Data Fusion, with pioneering work on Kalman filters for autonomous systems. He maintains the authoritative resource kalman-filter.de and has developed real-time capable SLAM algorithms, camera-based reference systems, and parking space detection frameworks. His expertise extends to entropy-based safety evaluation in autonomous driving and semantic segmentation using mixed real/synthetic data. Analysis of his 2020-2025 publications reveals dominant trends in autonomous driving systems, emphasizing real-time sensor fusion, deep learning for perception, and safety validation. Key subfields include adaptive Kalman filtering (ROSE-Filter), landmark-based navigation, neural network training with synthetic data, and maximum entropy safety frameworks. His work bridges theoretical innovation with automotive applications, particularly in model vehicle testing environments. Prof. Marchthaler leads research at the Institute for Intelligent Systems, directing the Green IT 2026 initiative and advising the Friedrich Ebert Foundation. His team develops ROS-based validation environments for autonomous algorithms and maintains the Kalman filter knowledge portal. Current projects focus on connected traffic systems using conventional infrastructure landmarks and entropy-optimized safety protocols for production vehicles.
