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نمایش ۳۱-۴۵ از ۱۹۱ استاد راهنما

اطلاعات پروفایل‌ها از صفحات عمومی دانشگاه‌ها گرفته شده و ممکن است به‌روز نباشد.

Ralf Steinmetzمشاهده پروفایل

استاد

Technical University of DarmstadtGermany

Prof. Ralf Steinmetz is a Full Professor of Multimedia Communications at Technische Universität Darmstadt since 1996 and head of the Multimedia Communications Lab. His research focuses on adaptive multimedia systems, self-organizing networks, mobile/sensor networking, and educational technologies. He has held leadership roles at IBM's European Networking Center and Fraunhofer IPSI. His work spans cybersecurity, IoT, disaster communication systems, and industrial networking. Education : Dr.-Ing (PhD) in Electrical Engineering, TU Darmstadt (1986) Habilitation in Computer Science, Goethe University Frankfurt (1994) Research Interests : He pioneers innovations in networked multimedia systems , including fault-tolerant communication, aerial-ground disaster monitoring (e.g., CAMON system), and 5G/Industry 4.0 infrastructure. His work emphasizes resilience, adaptive protocols, and cyber-physical integration. Recent Work Trends : Publications from 2022-2025 highlight advancements in: Wireless communication protocols (ESP-NOW, LoRa) Cybersecurity (intrusion detection via machine learning) Disaster response networks (aerial-ground cooperation) Time-sensitive networking for industrial applications Key Contributions : Developed Nature 4.0 sensor systems for biodiversity monitoring Pioneered P4-programmable network hardware solutions (P4-CODEL, P4-BNG) Advanced UAV-based emergency communication frameworks

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Fabian Fassnachtمشاهده پروفایل

استاد

Free University of BerlinGermany

Prof. Dr. Fabian Fassnacht holds the Professorship for Remote Sensing and Geoinformatics at the Institute of Geographical Sciences, Freie Universität Berlin. His research focuses on applying remote sensing technologies to understand ecological patterns and processes in vegetation ecosystems, particularly forest systems and urban trees. He specializes in developing workflows for quantifying forest attributes and creating synthetic remote sensing data to improve ecological understanding and monitoring. Education: PhD in Forestry Sciences (University of Freiburg, 2010-2014) Key Projects: FORZA (forest decline analysis), INSANE (spatial forest products), ErWiN (wildfire dynamics), SYSSIFOSS (synthetic forest data), SaMovar (invasive species monitoring) Research Focus: Multi-scale vegetation monitoring, 3D forest modeling, upscaling ecological processes, and wildfire risk assessment using LiDAR and UAV technologies His work addresses critical challenges in remote sensing applications across diverse ecosystems, including semi-arid forests and temperate woodlands. He has coordinated numerous research initiatives funded by BMBF, DAAD, DFG, and other international agencies. Current efforts involve integrating deep learning with traditional remote sensing methods to enhance forest inventory models and ecological assessments.

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Aderemi Aaron-Anthony Atayeroمشاهده پروفایل

پژوهشگر

University of TrierGermany

Aderemi Aaron-Anthony Atayero is an academic affiliated with the Department of Electrical Engineering and Information Engineering at Covenant University, Nigeria. His research focuses on telecommunications, wireless communication systems, IoT applications, and machine learning, with a strong emphasis on path loss modeling, signal processing, and smart city technologies. He has contributed to over 30 publications since 2005, collaborating extensively with researchers like Segun I. Popoola, Sanjay Misra, and Simon K. Hinga. His work spans theoretical and applied domains, including 5G mmWave models, botnet detection in IoT networks, and smart city infrastructure. Notable projects include the development of a low-intensity light imaging probe for medical applications and a cellular RSS dataset for roaming analysis. His research has practical implications for urban communication systems, healthcare technology, and cybersecurity.

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Xinwei Wangمشاهده پروفایل

استاد

University of TrierGermany

Xinwei Wang is a Professor at Nanjing University of Aeronautics and Astronautics with an extensive publication record spanning over two decades. Their research primarily focuses on autonomous systems, UAV trajectory planning, medical imaging, and computer vision applications. Wang has established significant collaborative networks with researchers including Yan Zhou, Liang Sun, Xichao Su, and Lei Wang across multiple Chinese institutions. Wang's research interests center on the intersection of robotics, artificial intelligence, and practical engineering applications. Their work demonstrates particular expertise in UAV coordination systems, medical diagnostic technologies, and underwater imaging solutions. Recent publications reveal a growing emphasis on explainable AI systems for medical applications and safety-critical trajectory planning for autonomous vehicles. The publication trends show a consistent output of high-impact research, with recent work increasingly focusing on practical implementations of AI systems in medical diagnostics, autonomous vehicle navigation, and aerospace applications. Wang's research bridges theoretical control systems with real-world engineering challenges, particularly in safety-critical domains requiring precise motion planning and reliable decision-making. Wang has contributed significantly to both theoretical frameworks in optimal control and practical implementations in medical imaging and autonomous systems. Their work on UAV cooperative task assignment and flight deck operations demonstrates strong connections to aerospace engineering applications, while medical imaging research shows interdisciplinary collaboration with healthcare professionals.

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Georg Stauchمشاهده پروفایل

استاد

Julius-Maximilians-Universität WürzburgGermany

Georg Stauch is a Professor at the University of Würzburg, holding the Chair of Geomorphology within the Institute of Geography and Geology, Faculty of Philosophy. His research spans multiple continents with particular focus on the Tibetan Plateau, Gobi Desert, and Central European reservoir systems. He employs advanced remote sensing techniques including Google Earth Engine and UAV photogrammetry to investigate landscape evolution and human-environment interactions. Stauch's research focuses on geomorphological processes in arid and high-mountain environments, with particular emphasis on sediment dynamics, climate change impacts, and anthropogenic influences. His work integrates field observations , remote sensing data , and sediment analysis to understand landscape evolution across various temporal scales. Recent research has increasingly incorporated microplastic analysis as a novel tool for dating sedimentary archives and understanding pollution history. His publication record reveals strong trends in utilizing multi-decadal satellite imagery to track dune migration rates across the Tibetan Plateau and Gobi Desert regions, while simultaneously investigating reservoir sedimentation as archives of human industrial activity in Central Europe. The integration of traditional geomorphological methods with modern cloud computing approaches represents a distinctive methodological signature across his recent work. Stauch actively contributes to educational innovation through projects like smartphone-based 3D landform mapping and XR technologies for geographical spatial analysis. His research group participates in multiple collaborative projects examining disaster risk, resilience, and environmental change across diverse global settings.

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Andreas Braunمشاهده پروفایل

مدرس ارشد

University of TübingenGermany

Andreas Braun is a Senior Lecturer at the Department of Geography, University of Tübingen, Germany. He leads lectures and courses on physical geography, geospatial methods, and remote sensing applications. Currently serving since January 2022, his academic responsibilities include teaching, thesis supervision, and research in geoinformatics with a focus on humanitarian response applications. PhD in Geography (2014-2019), University of Tübingen Baden-Württemberg Certificate in University Didactics (2015-2017) Professional experience at Stuttgart's Land Surveying Office (2013) His research bridges geospatial technologies with humanitarian applications, emphasizing remote sensing for environmental monitoring in refugee camps, urban structure analysis, and climate change adaptation. Key areas include SAR data utilization, geosimulation for landscape dynamics, and machine learning applications in geospatial projects. Scientific publications span topics like urban heat island effects in Vietnam, refugee camp monitoring using satellite imagery, and landscape change modeling. His work appears in journals such as IEEE Journal of Selected Topics in Applied Earth Observations , Remote Sensing , and Journal of Flood Risk Management . Teaching activities cover physical geography methods, GIS, remote sensing, and applied geoinformatics for both B.Sc. and M.Sc. programs. He supervises interdisciplinary projects connecting geography with social sciences, focusing on urban planning, climate adaptation, and environmental justice.

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Michael Lyuمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Michael Lyu is a Professor at The Chinese University of Hong Kong specializing in software engineering with a focus on cloud reliability, AIOps, and log analysis. His research bridges the gap between theoretical advances and practical industrial applications in large-scale cloud systems. His research interests span Software Engineering , Cloud Computing Reliability , AIOps , and Log Analysis . Dr. Lyu's work addresses critical challenges in modern cloud operations, including failure diagnosis, anomaly detection, and reliability engineering. His recent research has pivoted toward leveraging large language models for software engineering tasks, particularly in code generation and log analysis. His publication portfolio demonstrates consistent contributions to major software engineering conferences (ASE, ICSE, ESEC/FSE) from 2018-2025, with a noticeable increase in LLM-related research since 2023. The trend shows a clear evolution from traditional software engineering topics toward AI-driven approaches for cloud operations. ICSE 2021 Keynote: "Reliability-Driven AIOps for Cloud Resilience" ASE 2023: Maat: Performance Metric Anomaly Anticipation for Cloud Services ASE 2024: LILAC: Log Parsing using LLMs with Adaptive Parsing Cache Dr. Lyu actively mentors students, with numerous co-authored publications showing his advisees as first authors. His work receives significant attention in both academic and industrial software engineering communities, addressing practical problems faced by large-scale cloud service providers. His research group appears focused on developing data-driven approaches for improving cloud system reliability through advanced analytics of logs, traces, and KPIs.

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Christian Benzمشاهده پروفایل

پژوهشگر

Bauhaus University WeimarGermany

Christian Benz is a Researcher at the Computer Science Department, Faculty of Media, Bauhaus-University Weimar since 2019. He holds an M.Sc. and B.Sc. in Computer Science from TU Darmstadt, with specialization in machine learning applied to image data. His research focuses on structural health monitoring, crack detection, and 3D reconstruction using computer vision techniques. He concurrently works part-time as a Computer Vision Scientist at ZEISS since 2023. Research interests include crack segmentation , multi-view learning , point cloud processing , and deep learning for infrastructure inspection . Notable projects include the AISTEC initiative for evaluating aging infrastructure using digital technologies. His work bridges computer vision with civil engineering applications, particularly in bridge and building safety assessment. Publications emphasize interdisciplinary approaches to structural defect detection, leveraging CNNs, attention mechanisms, and novel benchmarks like OmniCrack30k. His methods address challenges in concrete surface analysis, UAV-based imaging, and semantic segmentation during bridge inspections. Professional activities include lab coordination in the 3D-RealityCapture-ScanLab and participation in the Bauhaus Path Planning Challenge. His research contributes to advancing automated inspection tools for civil infrastructure safety.

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Ingrid Ullmannمشاهده پروفایل

پژوهشگر

University of Erlangen–NurembergGermany

Ingrid Ullmann is a Researcher and Research Group Leader (Wave-Based Sensing Techniques) at the Institute of Microwaves and Photonics (LHFT) within the Department of Electrical-Electronic-Communication Engineering at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU). She holds a Dr.-Ing. (PhD) from FAU, awarded in 2021 for her thesis on 'Novel Concepts for Radar Imaging in Heterogeneous Media'. Her academic journey includes a 2016 M.Sc. in Electrical Engineering from the same institution. Her research focuses on radar imaging (millimeter-waves, terahertz), ultrasound imaging, non-destructive testing, and biomedical engineering applications. She leads two laboratories: the Radar Imaging Laboratory and the Medical Imaging Laboratory, advancing innovations in security screening, medical diagnostics, and automotive radar systems. Her work integrates machine learning with radar techniques to enhance imaging resolution and analysis efficiency. Ullmann’s publications (over 50 entries from 2017–2025) emphasize radar-based human motion tracking, material reconstruction, and UAV applications for environmental monitoring. Key trends include: 1) fusion of radar and ultrasound for enhanced visibility, 2) machine learning-driven signal processing in biomedical contexts, and 3) development of compact radar systems for space debris tracking and historical document analysis. She actively supervises student theses in radar imaging, medical engineering, and security systems. While no explicit awards are listed, her contributions to IEEE journals and conference proceedings highlight her technical leadership. Collaborations with Erlangen University Hospital and industry partners (e.g., Siemens) underscore her interdisciplinary reach.

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Ingo Neumannمشاهده پروفایل

استاد

Leibniz University HannoverGermany

Prof. Dr.-Ing. Ingo Neumann is a Professor of Engineering Geodesy and Geodetic Analysis Methods at Leibniz University Hannover's Faculty of Civil Engineering and Geodetic Science. He serves as Executive Director of the Geodetic Institute and leads research in geodetic sensor systems, structural monitoring, and multi-sensor fusion. His work focuses on advancing terrestrial laser scanning (TLS), UAV-based calibration, and machine learning applications in civil infrastructure analysis. Research interests include deformation monitoring, sensor calibration, and geospatial data processing. Notable projects involve fusion of SAR/InSAR data with TLS for ground movement analysis, and development of automated damage detection algorithms for port and marine structures. He teaches courses on sensor technology, geodetic measurement methods, and industrial surveying. Publications span 2006–2025, with recent emphasis on robust outlier detection, Kalman filter applications, and B-spline modeling for structural analysis. His work integrates geodesy with computer vision and machine learning to enhance infrastructure monitoring precision.

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Anders Katharinaمشاهده پروفایل

استاد

Technical University of MunichGermany

Prof. Katharina Anders holds the Professorship for Remote Sensing Applications at the Technical University of Munich (TUM), within the TUM School of Engineering and Design. Her research focuses on methodological advancements in remote sensing data analysis, particularly for observing Earth surface dynamics in contexts like natural hazards, climate change, and human-environment interactions. She earned her PhD in Geoinformatics from Heidelberg University, with a research stay at TU Delft. Key contributions include 4D observation techniques for geo-environmental monitoring and automated change detection systems using LiDAR and photogrammetry. Education: Studied Geography, Computer Science, and Environmental Physics at Heidelberg University Doctorate in Geoinformatics (cum laude) from Heidelberg University Research stay at TU Delft Research interests emphasize cross-scale analysis of landscape dynamics, with a focus on integrating high-resolution 3D/4D time series and machine learning for environmental monitoring. Her work bridges remote sensing, geoinformatics, and environmental science, addressing challenges like coastal erosion, permafrost thaw, and infrastructure safety. Her award-winning papers and projects include advancements in LiDAR-based change detection, fusion of multisource data, and open educational resources like the E-TRAINEE platform for time series analysis. Recent publications highlight innovations in 4D object segmentation, UAV photogrammetry, and snow cover dynamics tracking. Notable awards include the Baden-Württemberg Foundation Fellowship (2022) and the ISPRS Geospatial Week Best Paper Award (2019). Her research has been applied to diverse case studies, from Arctic permafrost monitoring to Tyrolean rockfall prevention.

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Boris Jutziمشاهده پروفایل

استاد

Technical University of MunichGermany

Prof. Dr. Boris Jutzi is a leading academic in photogrammetry and remote sensing, currently serving as Professor at Karlsruhe Institute of Technology (KIT) and acting head of the Chair of Photogrammetry and Remote Sensing at Technical University of Munich (TUM). His research focuses on active optical sensors, computer vision, laser scanning, and 3D reconstruction techniques. He holds a diploma in electrical engineering from University of Kaiserslautern, a PhD from TUM, and venia legendi from KIT. Affiliations: KIT Institute of Photogrammetry and Remote Sensing, TUM Chair of Photogrammetry and Remote Sensing Education: Diploma in Electrical Engineering (University of Kaiserslautern) Doctorate (TUM) Venia Legendi (KIT) His research interests include: Neural Radiance Fields (NeRF) for 3D reconstruction LiDAR technology and applications UAV-based remote sensing Geospatial data fusion Computer vision in environmental monitoring Awards: Faculty Teaching Award (2020) Best Paper Awards (2019, 2016, 2014, 2006) His work emphasizes novel sensor integration and automated scene analysis , with contributions to urban and environmental 3D modeling. Current projects include underwater scene reconstruction via NeRFs and large-scale digital twin datasets (e.g., TUM2TWIN).

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Sven Langeمشاهده پروفایل

پژوهشگر

Chemnitz University of TechnologyGermany

Dr.-Ing. Sven Lange is a post-doctoral researcher at Technische Universität Chemnitz (TU Chemnitz), affiliated with the Chair of Automation Technology and the Chair of Neurorobotics. His work spans research, education, and project management in robotics. Research interests include: Factor-graph optimization for SLAM and sensor fusion Nonlinear least squares methods in robotics Robust navigation for autonomous systems GNSS signal processing in urban environments Educational robot design for undergraduate courses Integration of multi-modal error models in state estimation Key publication trends focus on factor graphs, outlier mitigation, and sensor fusion techniques for UAVs, GNSS, and indoor navigation. His work emphasizes parameter-free algorithms and open-source implementations. Projects include DLR SpaceBot Cup robotics, smartLoc GNSS navigation, and TUC-Bot educational platforms. He has contributed to sensor fusion frameworks for Ceres and GTSAM solvers.

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Franz-Josef Behrمشاهده پروفایل

استاد

Stuttgart University of Applied SciencesGermany

Prof. Dr.-Ing. Franz-Josef Behr serves as Senior Professor of Geospatial Information at Stuttgart University of Applied Sciences, specializing in Spatial Data Infrastructure (SDI), Standards, Open Source solutions, data modelling, and disaster mapping. His academic leadership includes serving as Study Dean for the Master Programme Photogrammetry and Geoinformatics (2009-2022) and founding the internationally recognized AGSE conference series focused on geoinformatics for societal and environmental challenges. Behr's research centers on geospatial interoperability, with expertise spanning SDI implementation, OGC standards evolution, and open source geospatial technologies. His work bridges theoretical frameworks with practical applications in disaster management, urban planning, and international development, particularly through capacity-building initiatives in Indonesia and India. Current investigations examine OpenStreetMap integration for official cadastres and modern API-based service architectures replacing traditional OGC web services. Recent publications reveal strong trends toward practical implementations of open standards in governmental systems, UAV data processing for developing nations, and disaster response applications. His work consistently emphasizes interoperability, open data principles, and technology transfer to address real-world challenges in geospatial information management. Scientific recognition includes: Best Poster Award at ISPRS Conference, Prague (2016) Academic leadership extends globally through roles as Co-chair of the ICA Commission on SDI and Standards (2017-2023), membership in ISO/TC 211 standards committees, and service on Kerala's Digital University Board of Studies. He has significantly advanced geospatial education through the AGSE conference network spanning 12 countries and numerous international workshops. As founder and chair of the AGSE conference series since 2009, Behr has cultivated a global network connecting academia, government, and industry across India, Peru, Kenya, Malaysia, Germany, Iran, Namibia, and Nepal. This initiative specifically focuses on applying geoinformatics to societal challenges including disaster management, sustainable development, and environmental monitoring through practical open-source implementations.

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Uwe Rascherمشاهده پروفایل

استاد

Jülich Research CenterGermany

Prof. Dr. Uwe Rascher is the Head of the Shoot Dynamics group at the Institute of Bio- and Geosciences (IBG) , Plant Sciences (IBG-2) within the Jülich Research Centre . His research bridges biophysical processes in photosynthesis with remote sensing applications. Research Focus: Spatiotemporal dynamics of photosynthesis Non-destructive physiological monitoring Solar-induced chlorophyll fluorescence (SIF) for ecosystem analysis Drought and stress response in crops Machine learning for agricultural decision support Integration of leaf-to-canopy scale observations Scientific Trends: Analysis of SIF for photosynthesis quantification, development of hyperspectral imaging systems, cross-scale stress detection (drought, heat), machine learning applications in plant phenotyping, and climate research collaborations. Technical Contributions: Development of HyScreen, FloX, and FluoMap systems for field spectroscopy, UAV-based sensor validation, and standardized ground measurement networks. His work emphasizes sensor fusion, light distribution models, and fractal geometry for fluorescence downscaling.

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