جست‌وجوی استاد و پژوهشگر

• Robotics
• Control Systems
• Reinforcement Learning
• +۴ مورد دیگر

Zhen Kan is a Professor in the Mechanical and Aerospace Engineering Department at the University of Florida's College of Engineering, with previous affiliations at the University of Iowa and the Air Force Research Laboratory (AFRL). His extensive publication record spans over 15 years with significant output in recent years, indicating an active research career in robotics and control systems. Dr. Kan's research focuses on advanced robotics systems with expertise in temporal logic motion planning, reinforcement learning, and human-robot interaction. His work bridges theoretical control systems with practical robotics applications, particularly in multi-robot coordination, autonomous systems, and wearable robotics. The research demonstrates a strong emphasis on formal methods for ensuring safety and correctness in complex robotic systems. Analysis of recent publications reveals a consistent research trajectory centered around temporal logic specifications for robotic systems, with increasing integration of machine learning techniques. His work shows progression from theoretical control frameworks to practical implementations in quadruped robots, exoskeletons, and multi-robot systems operating in dynamic environments. Dr. Kan has established significant collaborations with researchers across multiple institutions, particularly with Warren E. Dixon (35 co-authored papers), Zhijun Li (23 papers), and Mingyu Cai (22 papers), indicating leadership in collaborative research projects. His publications appear in top-tier venues including IEEE Transactions on Robotics, IEEE Transactions on Automatic Control, and International Journal of Robotics Research. While specific grant information isn't visible in the provided text, the volume and quality of publications suggest substantial research funding. Dr. Kan's work has practical applications in autonomous systems, human-robot collaboration, and assistive technologies, with potential impact in defense, healthcare, and industrial automation sectors.

Michaela Coenenمشاهده پروفایل

پژوهشگر

• Health Promotion and Prevention
• Public Health Evaluation
• Implementation Science
• +۵ مورد دیگر

Dr. rer. biol. hum. Michaela Coenen is a Senior Researcher at the Chair of Public Health and Health Services Research (Institute for Medical Information Processing, Biometry and Epidemiology - IBE) at Ludwig Maximilian University Munich. She has served as Head of the Department of Health Promotion and Prevention (formerly Research Department of Biopsychosocial Health) since 2014 and as Program Coordinator of the Master's Program in Public Health since 2018. Education: Psychology (LMU Munich, 1986-1993), Master of Public Health (LMU Munich, 2000-2002) Doctoral Degree: Institute of Health and Rehabilitation Sciences, LMU Munich (2008) Research Expertise focuses on: Health Promotion in Urban Environments through projects like Soundscapes across Cityscapes and Munich Healthy Local Project Disability & Rehabilitation via ICF implementation projects including ICF│PROreha and ICF Core Sets for Hand Conditions Pandemic Response analyzing social resilience in SoNAR Global , Post-COVID Kids Bavaria , and COCOVID-19 Vulnerability Assessment Digital Public Health through the Digital Public Health Skills Lab Her methodological strengths include qualitative research, longitudinal studies, and implementation science frameworks. She supervises MSc public health theses on diverse health promotion topics.

Andreas Rienowمشاهده پروفایل

استادیار

• Geospatial Analysis
• Urban Remote Sensing
• Geoinformation Science
• +۶ مورد دیگر

Andreas Rienow serves as Junior Professor for Interdisciplinary Geoinformation Sciences at Ruhr University Bochum, where he also holds the position of Designated Managing Director of the Institute of Geography since 2024 and Scientific Director of the Interdisciplinary Center for Geoinformation since 2020. His academic journey began with studies in Geography, Modern History and Modern German Literature at the University of Bonn, culminating in a Magister Artium degree, followed by a doctorate in 2014 on urban sprawl modeling. Dr. Rienow's research centers on spatio-temporal analysis of metropolitan transformation, interdisciplinary geodata integration, real-time geoinformation analysis, innovative earth observation education methods, and ISS-based remote sensing. His work bridges technical geospatial approaches with urban planning challenges, particularly in post-conflict settings, climate adaptation, and sustainable development contexts across diverse geographical regions including Europe, Africa, and the Middle East. His recent publication portfolio demonstrates a clear trajectory toward increasingly sophisticated integration of machine learning with geospatial analysis, focusing on urban heat islands, land use change, post-conflict urban recovery, and sustainable development monitoring. The research spans multiple continents with particular emphasis on applying advanced remote sensing techniques to pressing urban challenges in both developed and developing contexts. As an educator, Rienow has supervised over 40 master's theses, numerous bachelor's projects, and currently mentors 8 doctoral candidates working on topics ranging from urban climate adaptation to innovative geospatial education methods. His leadership extends to directing the Interdisciplinary Center for Geoinformation and participating in international collaborations such as the Transdisciplinary Center for Coupled Socio-Ecological Systems at Universidad del Azuay in Ecuador. His laboratory work focuses on the Geomatics Group within the Institute of Geography, where his team develops innovative approaches to urban remote sensing, spatial modeling, and citizen science applications for metropolitan analysis. The group actively engages in both theoretical methodological development and practical applications addressing contemporary urban challenges.

Florian Rüfferمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Generative Models in Healthcare
• Explainable Artificial Intelligence
• +۳ مورد دیگر

Florian Rüffer is a Researcher and Doctoral Student at the University of Mannheim's Mannheim Business School, affiliated with the Department of Information Systems under the Heinzl research team. He has served as a Research Assistant since 2018 and commenced doctoral studies at the Graduate School of Economic and Social Sciences (GESS) in 2023. His educational background includes: Master of Science in Business Informatics with Artificial Intelligence specialization (2020-2023) Bachelor of Science in Business Informatics (2017-2020) Rüffer's research bridges artificial intelligence and healthcare through three core pillars: generative models in healthcare for medical data synthesis, explainable AI for transparent clinical decision-making, and multimodal AI integrating diverse medical data streams. His work emphasizes human-centered design principles to ensure AI systems meet clinicians' practical needs while advancing technical innovation in medical imaging applications. His DESRIST 2023 award-winning publication exemplifies the convergence of design science methodology with healthcare AI, establishing trends toward user-tailored explainability frameworks that address real-world clinical workflow challenges. Professional recognition includes: Best Paper Award at DESRIST Conference 2023 Rüffer actively contributes to the federally funded Mannheim Molecular Intervention Environment (M²OLIE) research campus, participating in grant-driven initiatives focused on AI-powered molecular interventions. His research trajectory demonstrates strong potential for future leadership in healthcare AI translation. He operates within Prof. Heinzl's research ecosystem at the Department of Information Systems, collaborating on projects that integrate business informatics methodologies with cutting-edge medical applications through the M²OLIE initiative.

• Artificial Intelligence
• 3D Scene Reconstruction
• Simultaneous Localization and Mapping (SLAM)
• +۳ مورد دیگر

Yiming Zhou is a researcher at Saarland University of Applied Sciences (htw saar) in Saarbrücken, Germany. Their work spans multiple engineering domains with emphasis on artificial intelligence integration, 3D scene reconstruction, and advanced imaging techniques. Contact: yiming.zhou@htwsaar.de Location: Goebenstraße 40, 66117 Saarbrücken Research Focus Zhou's research explores cutting-edge technologies in: AI applications for non-destructive evaluation Dynamic SLAM systems for robotics Next-generation 3D reconstruction methods Multimodal deception detection frameworks Novel Gaussian splatting techniques Semantic encoding for spatial data Recent Publications Trends Their scholarly output reveals a trajectory toward Real-time spatial mapping solutions Hybrid neural-implicit representations CAD-integrated building documentation AI-enhanced image translation pipelines Signal processing innovations Cross-modal data fusion Laboratory Affiliation Zhou contributes to the faculty laboratories at htw saar, focusing on engineering research through practical implementations and algorithm development.

Alena Lehmkuhlمشاهده پروفایل

پژوهشگر

• Digitization of higher education
• Professional teaching perception
• Learning support
• +۳ مورد دیگر

Alena Lehmkuhl is a Research Associate at the Institute for Didaktik des Sachunterrichts, University of Münster, since March 2020. Her research focuses on the digitization of higher education, professional teaching perception, and learning support mechanisms. Doctoral studies at the University of Münster (Didactics of General Education, Educational Science, Psychology, since 2020) Master of Education in Primary School Teaching (2018–2020) Bachelor of Arts in Primary Education (2014–2018) Her recent work explores digital, video-based self-learning modules to enhance professional classroom perception for pre-service teachers, particularly in science education. This aligns with the ProdiviS project, which evaluates adaptive tools for teacher training. Key themes include cognitive load reduction, motivation, and multi-perspective analysis of classroom management and learning support. She is a member of the Gesellschaft für Didaktik des Sachunterrichts (GDSU) since 2022.

Clemens Brackmannمشاهده پروفایل

پژوهشگر

• Machine Learning
• Artificial Intelligence
• Retail Technology
• +۳ مورد دیگر

Clemens Brackmann is a Researcher at the University of Duisburg-Essen, affiliated with the Faculty of Computer Science and the Human-Computer Interactions working group. His work spans machine learning integration in retail and software development. Education: M.Sc. in Applied Computer Science (2017–2021) from Ruhr University Bochum, B.Sc. in Applied Computer Science (2014–2017) from University of Duisburg-Essen. His research focuses on artificial intelligence applications in retail , particularly pricing algorithms and decision-making frameworks. He has contributed to understanding how machine learning shapes both brick-and-mortar and e-commerce environments through theoretical taxonomies and empirical studies. Recent publications highlight trends in AI-driven pricing strategies and ML adoption in retail processes . He has supervised bachelor's theses on topics like customer service chatbots, visual product search AI, and trust in medical AI systems. Contact: clemens.brackmann@icb.uni-due.de

Pierre Maierمشاهده پروفایل

پژوهشگر

• Multi-Level Software Languages
• Software Language Engineering
• Conceptual Modeling
• +۴ مورد دیگر

Pierre Maier is a Researcher at the University of Duisburg-Essen , affiliated with the Faculty of Computer Science and the Information Systems and Integrated Information Systems department. His research explores the intersection of information systems and software languages, with a focus on multi-level modeling (MLM), natural language generation (NLG), and the application of large language models (LLMs) in organizational problem-solving. Maier's work investigates automation techniques to enhance the usability of multi-level software languages and addresses challenges in transitioning from traditional two-level languages. He supervises theses on topics like Machine Learning-Assisted Domain Modeling , LLM-Driven Semantic Matching , and Flexible Modeling , reflecting his interest in bridging conceptual modeling with AI advancements. His recent publications analyze the integration of generative language models with UML, the evolution of low-code platforms, and the role of multi-level modeling in improving software artifacts. Maier teaches courses in Object-Oriented Modeling , Robotic Process Automation , and Data Integration , combining technical rigor with practical applications for enterprise environments.

Christoph Brielmaierمشاهده پروفایل

پژوهشگر

• Open Strategy
• Attention-Based View
• Strategy-as-Practice
• +۳ مورد دیگر

Dr. Christoph Brielmaier is a Researcher at the Faculty of Social Sciences, Economics, and Business Administration at the University of Bamberg , Germany, since July 2020. His work focuses on Open Strategy , the Attention-Based View , and New Roles in New Forms of Organizing . Coordinates and supervises final theses Manages learning agreements for foreign performance recognition Teaches seminars on Bachelor’s theses, Management Consulting Challenge, Corporate Strategy, and Strategy Practice Research Interests : Brielmaier explores how organizational transparency affects employee experiences, how social media biases influence managerial attention, and how framing practices reconcile fragmented attention structures. His work bridges strategic management with sociological and psychological perspectives on attention dynamics. Scientific Awards : Best PhD Paper Award (Strategy as Practice IG, SMS Conference) Best Paper Award (Strategy as Practice IG, SMS Conference) Pushing the Boundaries Award (Strategy as Practice IG)

Christian Geißمشاهده پروفایل

استاد

• Georisk Research
• Remote Sensing
• Machine Learning
• +۶ مورد دیگر

Prof. Christian Geiß is a Professor at the University of Bonn leading the Research Group 'Georisk Research using Remote Sensing Methods' in cooperation with the German Aerospace Center (DLR). His work focuses on the critical interactions between natural hazards and settlement areas, addressing a significant gap in current risk modeling approaches that often rely on aggregated or outdated data. His primary research interests include: Machine Learning and Artificial Intelligence for geospatial data analysis Natural hazard risk assessment (earthquakes, tsunamis, landslides, flooding, and fires) Exposure and vulnerability assessment of built environments Automated damage assessment following natural disasters Development of new machine learning methods for interpretation of earth observation data Prof. Geiß's recent publications demonstrate a strong methodological focus on combining diverse data sources including satellite imagery (TanDEM-X, Sentinel-1 & 2), street-level views (Google Street View), social media data, and volunteered geographic information. His work consistently aims to provide high-resolution risk models with improved spatial, thematic, and temporal precision, particularly valuable for understanding rapidly urbanizing environments. His research has practical applications for anticipating future damage, informing populations and authorities about risk levels, and implementing appropriate mitigation measures. As an educator, he teaches Machine Learning/Artificial Intelligence methods, Remote Sensing, Natural Hazard Risk Assessment, and Scientific writing, contributing to the development of next-generation geospatial analysts and risk assessment specialists.

• Digital Twins
• Human-Machine Interaction
• Simulation-based Systems Engineering
• +۵ مورد دیگر

Michael Schluse is a Professor and Chair of the Institute for Human-Machine Interaction at RWTH Aachen University, where he also serves as Chief Engineer. His work bridges academic research and industrial application in digital systems engineering, with a physical presence at Im Süsterfeld 9 in Aachen's Former customs office building. His research centers on Experimentable Digital Twins (EDZ) – a paradigm enabling real-time interaction between physical systems and their digital counterparts. Key focus areas include: Human Digital Twin specification frameworks addressing stakeholder needs and transparency requirements Convergence of simulation and reality for lifecycle-spanning system validation Virtual testbed development for robotics, forestry, and construction applications Carbon balancing technologies in timber supply chains and environmental modeling Augmented reality systems for error-based learning (FeDiNAR project) His publication trends reveal a strategic shift from foundational simulation technologies (2000-2015) toward human-centered digital twin architectures since 2018. Recent work emphasizes practical implementation in Forestry 4.0, construction site modeling, and cybersecurity frameworks, demonstrating consistent translation of theoretical concepts into domain-specific solutions. The research shows strong interdisciplinary alignment between computer science, mechanical engineering, and environmental systems. As head of the Institute for Human-Machine Interaction, Schluse leads a research ecosystem developing runtime environments for experimentable digital twins. The institute maintains close ties with industrial partners through projects like ClusterWIS (forestry information systems) and Off-Highway-Twins, focusing on real-world validation of simulation technologies in mobile and distributed environments.

Martin Behnischمشاهده پروفایل

استاد

• Spatial Data Science
• Urban Data Mining
• Geospatial Analysis
• +۷ مورد دیگر

Professor Martin Behnisch holds the Professorship for Spatial Information and Modelling at Dresden University of Technology (TUD) since 2023 and leads the same research area at the Leibniz-Institute of Ecological and Regional Development since 2011. He has held academic roles including Lecturer at Technische Universität Dortmund (2007–2011) and Senior Lecturer at Tianjin University (2005–2007). Diploma: Architecture (KIT, 1995–1998) MSc in Geographical Information Science and Systems (summa cum laude, Paris Lodron University Salzburg, 2004–2007) PhD (summa cum laude, Karlsruhe Institute of Technology, 1998–2004) His research interests span Spatial Data Science , Urban Sprawl , Building Stock Dynamics , and GIScience for Sustainable Urban Development , with a focus on data-driven approaches to monitor land consumption, soil sealing, and urban metrics. He has led major projects funded by DFG , SNF , BMBF , and BMWI , including analyses of urban solar potential , non-residential building databases , and insect biodiversity in protected areas . Recent publications (2024–2025) address residential infill determinants , urban sprawl drivers , and hybrid energy modeling , emphasizing spatiotemporal analysis. Earlier works (2018–2023) explored cluster analysis for land use patterns, 3D urban modeling , and crowdsourcing façade data . Key Collaborations : Associate Professor Dr. Jochen A.G. Jaeger (Concordia University), Prof. Dr. Markus Neppl (KIT), Prof. Niklaus Kohler (ETH Zurich) Grants : DFG (land use change), SNF (building stock conservation), BMWi (solar potential), BBSR (non-residential data), UBA (settlement trends) Editorial Roles : Guest Editor for ISPRS International Journal of Geo-Information and Environment and Planning B

Christian Leversمشاهده پروفایل

پژوهشگر

• Land-System Science
• Sustainability Science
• Land-Use Change
• +۵ مورد دیگر

Christian Levers is a Senior Scientist at the Thünen Institute of Biodiversity (Federal Research Institute for Rural Areas, Forestry, and Fisheries in Germany) and a guest researcher at the Conservation Biogeography Lab at Humboldt University of Berlin. His work bridges land-system science, sustainability research, and social-ecological analysis to address global change and biodiversity loss. He specializes in spatially explicit modeling, machine learning, and land-change simulation across Europe and South America. His research focuses on: Land-use change in deforestation hotspots like the Gran Chaco Biodiversity-land use interactions Quantitative methods for monitoring and modeling Marginalized land-use actors in sustainability frameworks Recent publications highlight his expertise in simulating land-system futures, analyzing agricultural expansion, and quantifying biodiversity impacts. His teaching experience spans graduate and undergraduate courses in Germany and the Netherlands, with extensive student supervision. He uses remote sensing (Landsat, Sentinel) and interdisciplinary approaches to inform conservation policies. Key affiliations and roles: Senior Scientist, Thünen Institute of Biodiversity (Germany) Guest Researcher, Conservation Biogeography Lab (Humboldt University Berlin)

• Educational Technology
• Artificial Intelligence in Education
• Learning Analytics
• +۵ مورد دیگر

Niels Pinkwart is a Professor at Humboldt University of Berlin within the Faculty of Mathematics and Natural Sciences and Institute of Computer Science, serving as Member of the Faculty Council. His research group focuses on Computer Science and Society and Computer Science Didactics, developing AI-driven educational solutions for diverse learning contexts including vocational training, language acquisition, and autism support. His research centers on human-centered AI in education, with emphasis on adaptive learning systems, creativity assessment in programming environments, and inclusive technologies. Recent work examines physical embodiment in educational robots, bias mitigation in assessment algorithms, and neural engagement patterns in VR learning for neurodiverse populations. He investigates how multimodal feedback systems and LLM integration can enhance language learning while maintaining pedagogical alignment. Current publications reveal a strong trend toward practical AI implementation in real-world educational settings, particularly in vocational contexts and global health education. His team develops deployable tools like the AI Campus 2.0 platform and Zirkus Empathico 2.0 game, with increasing focus on ethical AI deployment and cross-cultural applicability as evidenced by Nigeria-based healthcare studies. The research consistently bridges theoretical frameworks with classroom-ready applications. Professor Pinkwart supervises doctoral candidates including Heinrich Mellmann, Kerstin Wagner, Gregor Wrobel, and Michael Piechotta, with disputation dates scheduled through late 2025. His work receives funding through collaborative projects like the Verbundprojekt KI-Campus 2.0, where HU Berlin leads the platform development component. The research group maintains strong industry and international healthcare partnerships, particularly in digital transformation initiatives for resource-constrained environments. He directs development of specialized educational technologies including sound-driven robot quiz systems with fair responder detection and multimodal feedback, alongside serious games for social-emotional development in autism. Current lab activities focus on scaling bias-mitigated exam assembly tools for vocational education while expanding VR-based cognitive engagement metrics across neurodiverse populations.

Frank Wehrmannمشاهده پروفایل

پژوهشگر

• Inclusive Education
• Virtual Reality
• Educational Technology
• +۳ مورد دیگر

Frank Wehrmann is a Researcher at the Institute of Computer Science within the Faculty of Mathematics and Natural Sciences at Humboldt University of Berlin . He holds a Master of Education (M.Ed.) in Computer Science and English from the University of Potsdam (2022) and has been a scientific collaborator since April 2022. Currently pursuing his doctorate, his research focuses on Inclusive Education and Immersive Media , particularly leveraging Virtual Reality to enhance accessible learning environments. Education: Master of Education (Computer Science & English) - University of Potsdam (2022) Current Role: Doctoral Candidate & Researcher at HU Berlin Key Projects: FDQI-HU-MINT, Getch Web App Development His work spans systematic reviews on Virtual Reality applications, emphasizing Nonverbal Communication and Multi-User Systems for inclusive pedagogy. Publications highlight frameworks for Universal Learning , design guidelines, and empirical studies on VR-based education. Collaborations include contributions to the Getch web application for personalized and cooperative learning path documentation.