جست‌وجوی استاد و پژوهشگر

• Animal Movement Ecology
• Conservation Biology
• Habitat Suitability Modeling
• +۵ مورد دیگر

Dr. Anne K. Scharf is a Research Scientist at the Max Planck Institute of Animal Behavior, Department of Migration. Her work focuses on integrating animal movement ecology with conservation biology, leveraging computational tools like R packages (move, move2) and platforms like MoveApps to analyze tracking data. She specializes in assessing impacts of land-use changes, habitat suitability, and climate adaptation strategies for endangered species. Education: PhD in Organismal Biology (2017), Max Planck Institute for Ornithology MSc in Biodiversity & Conservation Biology (2010), University of Pablo de Olavide Bachelor's in Biology (2008), University of Granada Research Interests: Animal movement patterns under anthropogenic pressures Development of open-source tools for ecological data analysis Biodiversity hotspot modeling for species recovery Energy budget dynamics in wildlife Key Projects: MoveApps - No-code platform for animal tracking analysis Drylands Project - Climate impact assessments Vulture Research Consortium - Conservation strategies E4Warning - Early detection systems for wildlife Advising & Grants: Supervised projects on brown bear conservation, tiger recovery, and seed dispersal mechanisms. Collaborates with institutions like Leibniz Institute and Polish Academy of Sciences. Labs/Teams: Research Group Safi (Max Planck Institute), MoveApps Development Team

Fanny Langerwischمشاهده پروفایل

پژوهشگر ارشد

• Global Change Ecology
• Ecosystem Services
• Climate Modeling
• +۳ مورد دیگر

Dr. Fanny Langerwisch is a Senior Research Fellow at the Institute of Biology, Freie Universität Berlin, specializing in theoretical ecology. She focuses on global change impacts on vegetation, ecosystem service provision, and model integration for understanding environmental patterns. Her work bridges ecological research with societal relevance, emphasizing science communication and policy application. Her career includes senior scientist roles at institutions like Palacký University Olomouc and the Potsdam Institute for Climate Impact Research (PIK). She holds a PhD from PIK (2012) and a Biology degree from University Potsdam (2006). Her research integrates climate modeling, land-use analysis, and biodiversity conservation across scales from local to global. Key projects include ValuGaps (natural capital valuation), BESTMAP (agricultural policy modeling), and LEGATO (rice ecosystem services in SE Asia). She develops and applies dynamic global vegetation models (e.g., LPJmL) to assess climate impacts on ecosystems, riverine carbon fluxes, and biodiversity tipping points. Her interdisciplinary approach addresses socio-ecological challenges, with outputs informing policy through frameworks like Farming System Archetypes. Active in peer review and open-source model development, she contributes to advancing computational tools for environmental science.

• Software Engineering
• Data Management
• Interoperability Systems
• +۳ مورد دیگر

Dr. Roland Koppe is Head of Software Engineering at the Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research (AWI), leading the Architecture and Portal Solutions team within the 'From Observations to Archives and Analysis (O2A)' group. His work focuses on software engineering, interoperability of heterogeneous systems, and data modeling to enable seamless data flow from sensor observations to archival and publication systems. He is a key contributor to initiatives such as the Data Portal German Marine Research, the O2A framework, and the CRITTERBASE biodiversity data warehouse. Research Interests: Software Engineering methodologies for scientific data systems, engineering management of large-scale projects, interoperability standards for marine and climate data, and FAIR data principles implementation in collaborative frameworks. His work addresses challenges in managing heterogeneous sensors, automating quality control, and integrating data across marine, polar, and climate research domains. Developed the O2A framework to streamline sensor data workflows Core contributor to the Data Portal German Marine Research Architect of CRITTERBASE for polar marine biodiversity data Lead software engineering for MOSAiC Arctic expedition data management Contributed to Digital Earth initiatives and MOSES flood modeling projects Publications focus on sensor data management systems, FAIR implementation, and interdisciplinary data integration challenges in polar and marine research. His work emphasizes scalable solutions for heterogeneous data sources and collaborative scientific workflows.

• Scientific Data Management
• FAIR Principles
• Multidisciplinary Data Integration
• +۳ مورد دیگر

Dr. Janine Felden is a Group Leader at the PANGAEA Data Publisher for Earth & Environmental Science under the Alfred Wegener Institute (AWI). Her primary role involves advancing scientific data management and ensuring adherence to FAIR principles (Findable, Accessible, Interoperable, Reusable) for multidisciplinary datasets. She leads efforts to integrate georeferenced data from polar and marine research into PANGAEA's repository, supporting open science and data accessibility. Her research focuses on enhancing data interoperability and metadata standards, particularly in marine geosciences and environmental studies. Key contributions include developing frameworks for seismic data archiving, metadata concepts for OBS (Ocean Bottom Seismometers), and strategies to safeguard endangered datasets (e.g., NOAA data rescue initiatives). Recent projects include organizing workshops on data retrieval and integration with Jupyter Notebooks. Felden’s work bridges technical and scientific domains, emphasizing collaboration across disciplines. Her team actively participates in international initiatives like the World Data System and contributes to policy discussions on polar contaminants and deep-sea mining impacts. PANGAEA’s infrastructure, managed by her team, serves as a cornerstone for global Earth system research, enabling reproducible science and long-term data preservation.

• Wireless Communications
• 5G/6G Channel Modeling
• UAV Communications
• +۵ مورد دیگر

Ziwei Huang is an Assistant Professor at Southeast University's School of Information Science and Engineering, Department of Communication Engineering. With a prolific publication record from 2019-2025, Huang has established expertise in wireless communications, particularly in 5G/6G channel modeling, UAV communications, and vehicular networks. Recent work demonstrates a strategic expansion into AI/ML applications, computer vision, and large language models, showing interdisciplinary research growth. Huang's research interests focus on wireless communications channel modeling with particular emphasis on non-stationary characteristics, spatial consistency, and trajectory modeling for next-generation communication systems. Key areas include UAV communications , vehicular networks , intelligent sensing-communication integration , and multi-modal data fusion . Recent work has expanded into fundus image processing , text-to-image synthesis , and hallucination mitigation in vision-language models , demonstrating a strategic expansion into AI applications while maintaining core expertise in communications. The publication trends reveal a clear evolution from traditional wireless channel modeling (2019-2021) toward more integrated sensing-communication systems (2022-2023), with a significant pivot toward AI/ML applications in 2024-2025. Huang's work spans both theoretical channel modeling and practical implementation, with increasing emphasis on cross-disciplinary applications. The research shows strong collaboration patterns with Xiang Cheng and Lu Bai, suggesting membership in a well-established research group at Southeast University. Huang has contributed to numerous high-impact publications in IEEE journals including IEEE Transactions on Wireless Communications, IEEE Transactions on Vehicular Technology, and IEEE Communications Surveys & Tutorials, as well as top conferences like AAAI and ACL. The research demonstrates consistent funding support through collaborative projects focused on next-generation wireless communication systems. The work spans multiple laboratories and research teams, including wireless communications research groups at Southeast University, collaborations with medical imaging researchers for fundus analysis, and partnerships with AI research teams working on vision-language models. Recent publications suggest active participation in interdisciplinary research initiatives bridging communications engineering with artificial intelligence.

• Computer Science
• Geospatial Engineering
• Urban Planning
• +۳ مورد دیگر

Yoshihide Sekimoto is a researcher with extensive contributions to computer science, geospatial engineering, and urban planning. His work focuses on leveraging deep learning, remote sensing, and GIS data for infrastructure analysis, human mobility modeling, and disaster response systems. Specializes in road damage detection using federated learning and computer vision Develops synthetic human mobility datasets for urban and disaster scenarios Integrates spatio-temporal modeling with graph networks for transportation systems Applies AI to environmental monitoring (e.g., satellite wind resolution) His recent publications highlight collaborations on 3D building reconstruction, public transit visualization, and land price estimation via street view images. Articles trends include multi-modal data fusion, cross-country infrastructure analysis, and agent-based simulations for urban dynamics.

Nikolas Herbstمشاهده پروفایل

استاد

• Software Performance Engineering
• Cloud Computing
• Serverless Computing
• +۵ مورد دیگر

Nikolas Herbst is a Professor and Chair of Software Engineering at the Department of Computer Science, University of Würzburg. He leads research in Software Performance Engineering, High-Performance Data Processing, and Autonomic Computing. His work focuses on Cloud and Serverless Computing, Elasticity, and Time Series Analysis. He currently serves as JMU Chief Information Security Officer (CISO) and holds leadership roles in SPEC Research Groups and ICPE Steering Committees. Education: PhD in Computer Science (Karlsruhe Institute of Technology, 2018) Master of Computer Science (Karlsruhe Institute of Technology, 2012) Research Interests: His lab develops tools like CHAMELEON, TELESCOPE, and BUNGEE for cloud elasticity and performance analysis. He emphasizes benchmarking, resource demand estimation, and self-aware systems. Recent projects include real-time forest monitoring (ROOT) and serverless scientific computing (SOS). Teaching: Teaches Operating Systems, Performance Engineering & Benchmarking, and Self-Aware Computing at both undergraduate and graduate levels since 2012. Awards: 10 Year Most Impact Paper Award (ACM/SPEC ICPE 2023) SPEC Kaivalya Dixit Distinguished Dissertation Award (2019) IBM PhD Fellowship (2014) Grants & Projects: Coordinates DFG-funded projects like bidt-ROOT (2023–2026) and SOS (2025–2029). Leads development of open-source tools for cloud performance analysis, including WCF (Workload Classification & Forecasting).

• Plate Tectonics
• Geology
• Geophysics
• +۴ مورد دیگر

Maryline Moulin is a prominent geophysics researcher specializing in plate tectonics, continental margin evolution, and integrated seismic analysis. She has led major oceanographic campaigns including PAMELA-MOZ05/03 and MAGIC projects, focusing on passive margins in the South Atlantic and East African regions. 2003 PhD from University of Western Brittany 2016 Project Leader for PAMELA campaigns Key collaborator in 15+ international seismic studies Her research spans diverse methodologies: Wide-angle seismic (OBS) profiling Multi-channel seismic (MCS) interpretation Gravity and magnetic anomaly analysis 3D structural modeling (Placa3D) Seismo-stratigraphic analysis Recent publications (2023-2025) reveal patterns in: Proto-oceanic crust formation Passive margin segmentation Quaternary contourite systems Transform margin tectonics Deep crustal architecture

Bernhard Höfleمشاهده پروفایل

استاد

• Geoinformatics
• 3D Point Cloud Analysis
• Environmental Monitoring
• +۵ مورد دیگر

Prof. Dr. Bernhard Höfle is a Professor of Geoinformatics and 3D Geospatial Data Processing at the University of Heidelberg, where he leads the 3DGeo Research Group. His work focuses on computational methods for analyzing 3D/4D point clouds, with applications in environmental monitoring, natural hazard assessment, and vegetation studies. Research Interests: 3D/4D point cloud analysis for environmental observation Development of computational algorithms for geospatial data Integration of machine learning in remote sensing applications Virtual laser scanning simulations (VLS-4D) Real-time monitoring systems for critical infrastructure Digital Twin integration across scales Article Trends: His recent publications emphasize real-time 3D environmental monitoring, virtual simulation of dynamic scenes, multi-temporal analysis of natural processes, and machine learning applications for point cloud classification. They span from 2025 back to 2023 and cover diverse applications including rock glaciers, forest monitoring, building damage assessment, and bee activity tracking. Key Techniques: His work prominently features terrestrial laser scanning, UAV-based LiDAR, and open-source software development. He has contributed datasets like FOR-species20K and developed simulation frameworks such as HELIOS++.

Klaus Böhmمشاهده پروفایل

استاد

• Geoinformatics
• Spatial Data Analysis
• Explainable Artificial Intelligence
• +۴ مورد دیگر

Klaus Böhm serves as a Professor at Mainz University of Applied Sciences within the School of Engineering, affiliated with the i3mainz institute (Institute for Spatial Information and Surveying Technology). His research bridges geospatial technologies with artificial intelligence, focusing on practical applications in urban planning, healthcare, and educational environments through projects like BAM (Big Data Analytics) and TOPML (Machine Learning). His primary research domains include geospatial explainable AI (GeoXAI), mixed reality decision support systems, and health informatics applications. He pioneers methods for visualizing uncertainty in AI models, developing geoparsing techniques using LLMs, and creating spatial navigation frameworks for VR environments. His work consistently addresses real-world challenges in elderly mobility, smart city infrastructure, and medical education through spatial analytics. Analysis of his 2022-2025 publications reveals three dominant trends: (1) Integration of XAI with geospatial data for transparent decision-making in urban planning, (2) Development of mixed reality tools for STEM education and dermatology training, and (3) Spatio-temporal correlation analysis for smart city applications like parking optimization and public transport accessibility. His methodology emphasizes interactive visualization of complex spatial relationships and uncertainty quantification. Dr. Böhm leads multiple funded research initiatives including AIMR (AI-based decision support in mixed reality), RAFVINIERT (spatial intelligence for senior care), and FlexGeo (geo-service integration). These projects demonstrate sustained grant acquisition capability across EU and national funding programs, typically involving interdisciplinary teams from computer science, urban planning, and healthcare sectors. As a core member of the i3mainz research institute, he contributes to Germany's geospatial technology ecosystem through collaborative projects with municipal authorities and healthcare providers. The institute's work focuses on translating academic research into operational tools for spatial data infrastructure, particularly in environmental monitoring and public service optimization contexts.