جست‌وجوی استاد و پژوهشگر

Lukas Luftمشاهده پروفایل

پژوهشگر

• Robot Localization and Mapping
• Causality and Foundations of Quantum Physics
• Probabilistic Methods
• +۳ مورد دیگر

Lukas Luft is a postdoctoral researcher at the Autonomous Intelligent Systems group within the Department of Computer Science at the University of Freiburg. His work spans robotics and quantum physics, focusing on probabilistic methods for robot localization, multi-robot systems, and causal inference. Post Doc (2020–present) PhD in Computer Science, University of Freiburg (2020) Master and Bachelor in Physics, RWTH Aachen and University of Freiburg His research in Robot Localization and Mapping includes advanced probabilistic techniques like Bayes filters, decentralized algorithms for multi-robot systems, and change detection in environments using full posterior distributions. He also explores Causality and Foundations of Quantum Physics , applying entropic inequalities and information theory to causal discovery and non-locality. The articles highlight his contributions to robotics, particularly in sensor modeling for Lidar, simultaneous localization and mapping (SLAM), and efficient probabilistic methods. In quantum physics, his work addresses causal structures and entropic information, bridging AI with foundational physics. Luft has collaborated with leading researchers, including Prof. Wolfram Burgard and Bernhard Schölkopf, and contributed to key conferences like Robotics: Science and Systems (RSS) and IEEE IROS.

• Computer Vision
• Machine Learning
• Robotics
• +۳ مورد دیگر

Xinguo He is a Researcher at the Chair of Media Technology (LMT) within the Technical University of Munich (TUM), where he is pursuing his Ph.D. degree after joining the chair in November 2022. He earned his B.Eng. in automation (2019) and M.Eng. in control engineering (2022) from South China University of Technology. His research spans Computer Vision, Machine Learning, Robotics, and Control Engineering, with specific focus on Haptic Communication and Video Communication systems. These interests directly align with the chair's core research areas including indoor mapping, localization, navigation, and human activity understanding through computer vision and machine learning methodologies. As an active member of the Munich Institute of Robotics and Machine Intelligence (MIRMI), He contributes to major initiatives such as the Centre for Tactile Internet with Human-in-the-Loop (CeTI) and the 5G Testbed Bayern project focused on eHealth applications.

• Robotics
• Artificial Intelligence
• Computational Neuroscience
• +۷ مورد دیگر

Robin Dietrich is a Researcher at the Department of Informatics 6 - Chair of Robotics, Artificial Intelligence and Real-time Systems at the Technical University of Munich . His work bridges computational neuroscience and robotics, focusing on translating neural mechanisms from mammalian brains into algorithms for mobile robot navigation. B.Sc. and M.Sc. in Computer Science Research on hippocampal temporal dynamics for neuromorphic SLAM Specializes in spiking neural networks for navigation and radar processing Research Interests : Robin's research explores the intersection of robotics, artificial intelligence, and computational neuroscience . His work specifically investigates spiking neural networks, FMCW radar data processing, and neuromorphic algorithms for autonomous systems. Recent projects focus on uncertainty quantification, evolutionary optimization, and multi-robot exploration using biologically inspired models. Publication Trends : Robin's publications (2019-2025) demonstrate a consistent focus on neuromorphic computing for robotic perception , with increasing specialization in spiking neural networks for radar processing and biologically inspired navigation algorithms . Key collaborations include contributions to multi-robot exploration metrics and hardware acceleration frameworks. Teaching Contributions : Robin has taught Digital Signal Processing and Real-Time Systems lectures since 2019, co-led seminars on Bio-inspired Data Processing , and supervised practical courses on Intelligent Mobile Robots using ROS.

• Virtual Reality
• Augmented Reality
• Computer Vision
• +۴ مورد دیگر

Prof. Dr. Didier Stricker is a leading academic in computer science, serving as Scientific Director at the German Research Center for Artificial Intelligence (DFKI) and Professor at the University of Kaiserslautern-Landau (RPTU). His career spans over two decades, including leadership roles at Fraunhofer IGD and founding the Augmented Vision research unit at DFKI/RPTU, which now includes ~30 researchers. Education: Electrical Engineering (Technical University of Grenoble, Karlsruhe) PhD: Computer Vision-based Calibration and Tracking Methods for Augmented Reality (2002, TU Darmstadt) His research focuses on virtual and augmented reality , computer vision , human-computer interaction , and on-body sensor networks . He leads major EU/national projects like LUMINOUS (Language-Augmented XR) and SHARESPACE (Ethical Hybrid Shared Spaces), with industrial partnerships including Sony, Google, and John Deere. Recent publications emphasize 3D reconstruction , neural network optimization , and XR systems . Key trends include event camera processing , scene flow estimation , and multimodal AI for industrial applications . He holds patents in AR tracking and has received the 2006 Innovation Prize from the German Society of Computer Science. Scientific Awards : Innovation Prize (2006) Best Paper/Demonstration Awards at ISMAR, EUSIPCO, CVPR, and ICRA As a reviewer for journals and conferences in VR/AR and computer vision, he contributes to shaping research standards. His lab ( AG Augmented Vision ) combines academic and industrial collaborations to advance cognitive interfaces and extended reality systems.

Andreas Harthمشاهده پروفایل

استاد

• Decentralized information systems
• World Wide Web technologies
• Blockchain environments
• +۷ مورد دیگر

Prof. Dr. Andreas Harth holds the Chair of Business Information Systems, especially Technical Information Systems, at Friedrich-Alexander University Erlangen-Nuremberg (FAU), where he has been a faculty member since 2018. He also serves as a department head at the Fraunhofer IIS-SCS in Nuremberg. His academic work spans both theoretical research and practical applications in decentralized information systems, with strong connections to industry through numerous collaborative projects. Harth completed an apprenticeship as a banker before studying computer science. He earned his doctorate from the Digital Enterprise Research Institute at the National University of Ireland, Galway, and completed his habilitation at the Karlsruhe Institute of Technology. His academic journey included teaching and research stays at the universities of Heidelberg, Innsbruck, Stanford, and Southern California, providing him with a global perspective on information systems research. His research focuses on developing methods and technologies for decentralized information systems found in the World Wide Web and blockchain environments, with applications in companies. He investigates data integration using Semantic Web and Linked Data technologies, process modeling languages, and their applications in the Internet of Things, Web of Things, and Industry 4.0 contexts. His work bridges theoretical computer science with practical business applications, particularly in data sovereignty and decentralized architectures. Analysis of his recent publications reveals a strong trend toward Solid protocol applications, knowledge graph technologies, and the integration of large language models with semantic web technologies. His research increasingly focuses on practical implementations in enterprise settings, healthcare data management, and manufacturing systems, demonstrating the real-world applicability of his theoretical work. As a member of FAU's research focus on Digitalization and Innovation, Harth collaborates with strategic partners including the Fraunhofer Institute for Information Systems (IIS) and major German industrial companies. His work contributes significantly to FAU's position as one of Germany's most research-intensive universities, particularly in the fields of business informatics and decentralized systems.

Torsten Sattlerمشاهده پروفایل

استاد پژوهشی

• 3D computer vision
• Machine learning
• Image-based localization
• +۱۰ مورد دیگر

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.

• Medical Robotics
• Artificial Intelligence
• Radiosurgery
• +۳ مورد دیگر

Prof. Achim Schweikard is a Full Professor at the University of Lübeck's Institute for Robotics and Cognitive Systems, where he has led pioneering research since 2002. His academic journey spans Stanford University's neurosurgery and computer science departments and Technical University of Munich, establishing him as a leading figure in medical technology translation. His research focuses on Medical Robotics and Artificial Intelligence with transformative clinical applications. Key achievements include inventing correlation-based tracking for cancer radiosurgery (now global standard of care) and developing stereotactic arrhythmia radioablation (STAR) protocols. Current projects address critical challenges in cardiac radioablation through the RAVENTA multicenter trial, MATRIX-VT imaging fusion study, and SonoBox robotic ultrasound system for pediatric diagnostics. His publication record shows sustained high impact with 15+ articles in 2023-2025 in top journals including Radiotherapy and Oncology and Heart Rhythm. These works demonstrate progression from foundational robotics to clinical implementation, with recent focus on cardiac motion estimation, target transfer automation, and S-ICD patient treatment solutions. As Academic Director of UNI Luebeck's Grad School (2025), he oversees doctoral training while leading the Robotics Laboratory (RobLab). The lab maintains active grants supporting: RAVENTA trial: German multicenter feasibility study for ventricular tachycardia radioablation DYNAMIC phantom development for end-to-end treatment validation ECG-gated 4D CT motion modeling for precision targeting Landmark-based ultrasound-CT fusion techniques Students gain comprehensive experience across the medical technology pipeline - from hardware prototyping to clinical trial participation - within an internationally collaborative environment spanning the STOPSTORM.eu consortium and multiple EU research networks.

Andreas Wenzelمشاهده پروفایل

استاد

• Embedded Systems
• Diagnostic Systems
• Neural Networks
• +۶ مورد دیگر

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.

Reiner Marchthalerمشاهده پروفایل

استاد

• Embedded Systems
• Sensor Data Fusion
• Kalman Filters
• +۲ مورد دیگر

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.