جست‌وجوی استاد و پژوهشگر

Dirk Elingمشاهده پروفایل

استاد

• Engineering Surveying
• Geodetic Monitoring
• Building Information Modeling (BIM)
• +۴ مورد دیگر

Prof. Dr.-Ing. Dirk Eling is a Professor in the Department of Geodesy at Bochum University of Applied Sciences, where he leads courses including Fundamentals of Engineering Surveying, BIM, and Geodetic Monitoring. He coordinates the Laboratory for Instrument Testing and Length Metrology, providing calibration services for surveying equipment. His research focuses on: Geodetic structural monitoring (e.g., automated tachymetric systems at Christ Church Schwelm since 2019) Building Information Modeling (BIM) applications in infrastructure (project lead for BIM.Ruhr since 2020) Terrestrial laser scanning for deformation analysis (e.g., Westhofen weir monitoring since 2014) Publication analysis reveals consistent emphasis on precision measurement technologies, with recent works exploring BIM integration and terrestrial laser scanning for infrastructure diagnostics. Earlier research centered on photogrammetry and statistical error modeling. He has supervised over 30 Master's students on topics including: BIM implementation in bridge rehabilitation Automated monitoring systems Point cloud processing for deformation analysis Geodetic instrumentation accuracy

Lynn Kaackمشاهده پروفایل

استادیار

• Climate Change Mitigation
• Machine Learning
• Public Policy
• +۳ مورد دیگر

Lynn Kaack is an Assistant Professor of Computer Science and Public Policy at the Hertie School in Berlin. Her research focuses on applying machine learning and statistical methods to inform climate mitigation policy in the energy sector and AI policy related to climate action. She co-founded and chairs Climate Change AI, an organization advancing machine learning applications for climate solutions. Previously, she was a Postdoctoral Researcher and Lecturer at ETH Zürich’s Energy Politics Group. She holds a PhD and Master’s in Machine Learning from Carnegie Mellon University and degrees in Physics from the Free University of Berlin. Education: PhD in Engineering and Public Policy, Carnegie Mellon University Master’s in Machine Learning, Carnegie Mellon University MS and BS in Physics, Free University of Berlin Research Interests: Her work bridges computer science and public policy, emphasizing data-driven approaches for climate policy design. Key areas include energy system decarbonization, AI ethics in environmental governance, and scalable solutions for urban sustainability. She develops tools to analyze policy text, monitor transport emissions, and model building energy efficiency at city scales. Key Contributions: Kaack leads the Horizon Europe project AI-EFFECT and contributes to initiatives like the POLIANNA dataset for policy design analysis. Her work on spatiotemporal machine learning for urban traffic and solar panel detection exemplifies her focus on actionable climate data science. Awards: No specific awards listed, though her impactful contributions to Climate Change AI and policy-relevant research are notable. Teaching & Leadership: Teaches courses on Deep Learning and AI & Climate Change at the graduate level. Serves as faculty advisor for the Hertie School’s Climate Policy initiatives and collaborates with global institutions on sustainability projects.

• Stochastic Control
• Financial Mathematics
• Mathematics
• +۳ مورد دیگر

Dr. Christian Laudagé is affiliated with the Department of Stochastic Control and Financial Mathematics at RPTU Kaiserslautern-Landau. His work focuses on stochastic control theory and its applications in financial mathematics. He is based at Building 48, Room 611, located at Gottlieb-Daimler-Straße in Kaiserslautern. Contact details include the phone number +49 (0)631 205 3851 and email christian.laudage@rptu.de. His research interests center on advancing methodologies in stochastic processes and their practical implications in financial systems. While specific publications are not listed here, his department’s focus areas suggest involvement in topics such as risk management, mathematical modeling in finance, and computational stochastic methods. No academic awards, grants, or advised students are explicitly mentioned in the provided information. His professional activities likely include teaching and research within the university’s mathematics programs.

• Computer Science Education
• Culturally Responsive Computing
• Augmented Reality for Education
• +۴ مورد دیگر

Dr. Wei Yan is an Associate Professor in the Department of Computer & Information Science & Engineering at the University of Florida's Herbert Wertheim College of Engineering. With an extensive publication record spanning computer science education, augmented reality applications, and culturally responsive computing, Dr. Yan has established a significant research presence with numerous publications in top-tier conferences and journals from 2023-2025. Dr. Yan's research interests focus on culturally responsive computing education, particularly with Indigenous communities including the Navajo Nation. Their work bridges the gap between technical computing concepts and culturally relevant pedagogy, with a special emphasis on spatial reasoning and mathematics education through augmented reality technologies. The research program has produced innovative AR classroom applications that help students understand complex spatial transformations and matrix algebra through interactive 3D visualizations. Through collaborations with researchers like Ashish Amresh, Paige Prescott, Maya Israel, and Heather Burte, Dr. Yan has developed several educational technology interventions that address inclusion in computer science education. Their publications reveal a strong commitment to broadening participation in computing, particularly among underrepresented groups, with a focus on teacher professional development and curriculum design that respects cultural contexts. Dr. Yan's technical expertise spans both educational technology development and core computer science topics, as evidenced by publications ranging from spatial reasoning in AR classrooms to advanced topics in integer coding and neural image compression. This interdisciplinary approach allows for the development of sophisticated educational tools grounded in solid computer science principles. Current research directions include AI-enhanced educational applications, culturally responsive computing curriculum development, and the integration of conversational AI with augmented reality for improved learning experiences. The work has significant implications for how computing education can be made more accessible and relevant to diverse student populations.

• Computer Vision
• Deep Learning
• Object Detection
• +۴ مورد دیگر

Zheng Ge is an active researcher specializing in computer vision and deep learning, with a prolific publication record spanning from 2018 to 2025. They have authored or co-authored 81 publications in top-tier venues including CVPR, ICLR, ECCV, and NeurIPS, demonstrating consistent research productivity and impact in the field of artificial intelligence. Dr. Ge's primary research interests focus on computer vision with particular emphasis on object detection, 3D perception, and multimodal learning systems. Their work bridges theoretical advancements with practical applications, especially in video understanding, image generation, and large vision-language models. Recent research directions show a strong focus on developing more efficient and capable multimodal systems that can handle complex visual tasks with human-like understanding. The analysis of their recent publications reveals a clear trend toward building more sophisticated multimodal systems that integrate vision, language, and temporal understanding. Their work on video generation, perception modeling, and instruction tuning demonstrates a strategic focus on advancing the capabilities of multimodal large language models while addressing practical challenges in scalability and robustness. While specific awards are not documented in the available publication records, Zheng Ge's consistent presence in top-tier computer vision and machine learning conferences indicates significant recognition within the research community. Their work has contributed to advancing state-of-the-art techniques in multiple subfields of computer vision. Dr. Ge appears to be actively collaborating with a large research team, frequently working with researchers such as Xiangyu Zhang, Jianjian Sun, Chunrui Han, and Liang Zhao. These collaborations span multiple institutions and research groups, suggesting a well-integrated position within the computer vision research ecosystem. While specific grant information isn't available in the publication metadata, the scale and scope of their projects indicate substantial research funding support. Based on publication patterns and technical focus, Zheng Ge appears to be part of a large research organization or lab specializing in computer vision and multimodal AI systems. Their work on technical reports for video foundation models and large-scale multimodal systems suggests involvement in industry-leading AI research initiatives with strong engineering capabilities.

Mahshid Birkholzمشاهده پروفایل

پژوهشگر

• Construction Management
• Civil Engineering
• Lean Construction
• +۳ مورد دیگر

Mahshid Birkholz is a Researcher at the Bauhaus-Universität Weimar, affiliated with the Faculty of Civil and Environmental Engineering. Her research focuses on the impacts of lean principles in BIM-based construction projects, lean implementation in infrastructure projects, and optimizing construction processes. She is based at Marienstraße 7a, Room 201 in Weimar, reachable via email or phone +49 (0) 3643 / 58-4571 (by appointment). Her research activities emphasize practical applications of lean methodologies and BIM integration to enhance construction efficiency. Teaching responsibilities include contributions to the Project Management course within the Faculty's curriculum. She collaborates with senior academics like Prof. Jürgen Melzner and Prof. Hans-Joachim Bargstädt, contributing to interdisciplinary projects on construction operations and safety. No scientific awards or grants are explicitly listed in the provided materials. Her work forms part of the faculty's broader initiatives in sustainable construction and technological innovation in the built environment.

Ronny Helbingمشاهده پروفایل

پژوهشگر

• Construction Management
• Construction Safety
• Legal Aspects in Construction
• +۳ مورد دیگر

Ronny Helbing is a Researcher at the Faculty of Civil and Environmental Engineering, Bauhaus-Universität Weimar. He specializes in construction operations, legal frameworks (e.g., Building Law, Contract Management), and occupational health and safety. His work integrates practical construction methodologies with regulatory compliance. He teaches courses such as Construction operations, construction methods and occupational health and safety , emphasizing machine operation, cost calculation, and process optimization. Additional teaching areas include Risk and Chance Management and Legal Contract Management . Ronny contributes to research projects like BIMwissT (Machine Readable Modeling) and DROHNIS, focusing on BIM-based construction noise analysis and automated quality inspection planning. No awards or grants are explicitly mentioned in the provided data. He is affiliated with the Construction process control and Building in Existing Contexts research groups, collaborating with faculty members like Prof. Melzner and Prof. Bargstädt. His office is located at Marienstraße 7a, Room 201, Weimar.

• Historical Sociology of Social Sciences in Africa
• Knowledge and Power Relations
• Global Sociology
• +۳ مورد دیگر

Dr. SAWADOGO Natewindé holds the position of Assistant Professor in Sociology at Université Ouaga II, affiliated with the Faculty of Humanities and Social Sciences. He is a core member of the 'Connaissances' Research Section within the Africa Multiple Excellence Pole at Université Joseph Ki-Zerbo. His academic leadership includes roles as Deputy Director of the Institute for Initial and Continuing Education (Université Ouaga II), Deputy Coordinator of the CEFORGRIS African Excellence Center, and Facilitator of the 'Savoirs en Afrique' research section. Education: Holds a PhD in Sociology (2013, University of Nottingham), MSc in Science, Technology & Society (2008, Nottingham), MA in Political Sociology (2006, UCAD Senegal), and earlier degrees from the University of Ouagadougou. Research Interests: Focus on historical sociology of social sciences in Africa, knowledge-power dynamics, global sociology, global health systems, and regional scientific collaboration. Specializes in epistemological/methodological frameworks for African social research. Key Contributions: Led/co-led over 10 research projects including CEFORGRIS (£2.5M), UNESCO West Africa Science Report (2020), and innovation systems studies. Published widely in sociology, medical anthropology, and development studies. Awards: Recipient of Wellcome Trust Doctoral/Master's scholarships and multiple CODESRIA grants. Serves on editorial boards for African Journal of Science, Technology, Innovation & Development and the Journal of Creativity, Innovation and Social Entrepreneurship. Grants & Collaborations: Over £3M in research funding, with partnerships across Africa, Europe, and North America. Active in Royal Society Panafrican programs and German-African academic initiatives.

Nan Liuمشاهده پروفایل

پژوهشگر

• Cognitive Neuroscience
• Neural Dynamics
• Perception
• +۳ مورد دیگر

Dr. Nan Liu is a Researcher at the Institute of Neuroscience and Medicine (INM) , specifically within the Cognitive Neuroscience (INM-3) department at the Research Center Jülich GmbH . Their work focuses on neural dynamics, perception, and cognitive processes using advanced neuroimaging techniques. Key research areas include face perception, motor region connectivity, spatial cognition, and reference frame processing. Dr. Liu's recent studies explore theta and alpha oscillations in ambiguous stimuli perception, information flow in motor regions, and overlapping neural responses in visuospatial and arithmetic tasks. Contact: +49 2461/61-4208 | Email Office: Building 05.7, Room 3014, Wilhelm-Johnen-Straße, 52428 Jülich Research emphasizes interdisciplinary approaches, combining EEG, fMRI, and computational modeling to map brain functions. Recent articles highlight contributions to understanding neural synchronization in perception, motor cortex connectivity, and spatial cognition mechanisms.

Christoph Gengnagelمشاهده پروفایل

استاد

• Structural Design
• Digital Prototyping
• Material Systems
• +۳ مورد دیگر

Prof. Christoph Gengnagel is a Professor of Structural Design and Engineering at the School of Architecture, Berlin University of the Arts (UDK Berlin), and Managing Director of the Institute for Architecture and Urban Planning. He holds a PhD from the Technical University of Munich and has over 20 years of professional experience as a structural engineer. His research focuses on computational design, material systems, and transdisciplinary prototyping. He co-founded the Hybrid Plattform, a collaborative research initiative between UdK Berlin and TU Berlin, and received the Velux Visiting Professorship at CITA in 2013. Education: Bachelor’s/Master’s in Structural Engineering and Architecture, Bauhaus University Weimar PhD in Structural Engineering, Technical University Munich (2005) Research Interests: Prof. Gengnagel explores physical and digital prototyping, novel material systems (e.g., polymer concrete, natural-fiber composites), and computational design methodologies. His work emphasizes sustainability, active bending structures, and the integration of virtual reality tools in architectural design. Notable Projects: FibreCast (DFG-funded, 2016–2018) Hybrid Plattform (EU-funded, 2011–2015) Rethinking Prototyping (Einstein Stiftung Berlin, 2012–2015) Awards: Velux Visiting Professorship (2013) Labs/Teams: Hybrid Plattform, Structural Morphology Group, and collaborations with Bollinger + Grohmann Ingenieure.

Ioannis Brilakisمشاهده پروفایل

استاد

• Construction Engineering
• Construction Automation
• Digital Twins
• +۵ مورد دیگر

Ioannis Brilakis is the Laing O’Rourke Professor of Construction Engineering and Director of the Construction Information Technology Laboratory at the University of Cambridge’s Department of Engineering. He holds a PhD from the University of Illinois, Urbana-Champaign and has held academic roles at the University of Michigan, Georgia Tech, and visiting appointments at Stanford and Technical University of Munich (TUM) as a Visiting Professor and Hans Fischer Senior Fellow (2019–2021). His work focuses on construction automation, digital twins, and infrastructure sensing technologies. Research interests include generating/updating digital twins for infrastructure, computer vision for construction site analysis, automated design/construction tasks, and project management technologies. Awards include the NSF CAREER Award, ASCE J. James R. Croes Medal, and ASCE John O. Bickel Award. Collaborations include projects funded by EPSRC, H2020, InnovateUK, and industry partners like BP and Trimble. His lab develops AI-driven solutions for infrastructure monitoring and BIM integration. Recent work emphasizes climate resilience of critical infrastructure and graph-based construction scheduling analysis.

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۵ مورد دیگر

Hui Fang is a researcher at Loughborough University , Department of Computer Science, UK. Their work spans Artificial Intelligence , Machine Learning , and Remote Sensing , with recent focus on Medical Imaging , Natural Language Processing , and Urban Mobility . Publications highlight innovations in MRI Reconstruction , Legal Judgment Prediction , and Video SAR Analysis . Research Interests include Graph Neural Networks , Transformer Models , and Data Mining applied to domains like Agricultural Technology , Healthcare Systems , and Smart Cities . Methodologies emphasize Interpretable AI , Federated Learning , and Multimodal Integration . Key 2024-2025 Trends involve Transformer-Based Architectures for Medical Imaging , Information Bottleneck in Spatio-Temporal Networks , and Bootstrapping Techniques for Information Extraction . Collaborative projects with Dongdong Weng , Zhu Xiao , and Yong He demonstrate interdisciplinary applications in Transportation , Healthcare , and Agriculture . Recent Co-authored Publications span IEEE Transactions , Neurocomputing , and Remote Sensing Journals , addressing Dynamic Phasor Modeling , 4D Facial Capture , and Virtual Reality Usability .

• Wireless Communication
• Machine Learning
• Signal Processing
• +۳ مورد دیگر

Yoan Shin is a researcher active in wireless communication, machine learning, and remote sensing. His work spans indoor localization, SAR ship detection, UAV object detection, and IoT resource allocation. Key research areas: Wireless Sensor Networks, Deep Learning, SAR Imagery, UAV Systems, IoT Recent publications focus on hybrid Wi-Fi/PDR indoor tracking (2023), enhanced RT-DETR architectures for UAV imagery (2024), and SAR ship detection optimization (2024). Trends show expertise in sensor fusion, attention mechanisms, and domain-specific neural networks. Collaborates extensively with researchers like Chushi Yu, Thu L. N. Nguyen, and Oh-Soon Shin. No explicit awards or teaching roles listed.

• Cybersecurity
• Authentication Systems
• Blockchain Technology
• +۶ مورد دیگر

Jun-Ho Huh is a Professor at Sungkyunkwan University's College of Information and Communication Engineering, Department of Computer Science and Engineering. His extensive research portfolio demonstrates leadership in cybersecurity, authentication systems, and AI applications across multiple domains including financial technology, maritime security, and agricultural technology. Dr. Huh's research interests span cybersecurity, authentication systems, blockchain technology, artificial intelligence, edge computing, and IoT security. His work bridges theoretical computer science with practical applications in smart systems engineering. His research has significant implications for improving security in emerging technologies like DeFi, autonomous systems, and smart infrastructure. Analysis of Dr. Huh's recent publications reveals a strong focus on practical applications of AI and security technologies. His work covers diverse areas including cybersecurity for maritime autonomous systems, authentication mechanisms, financial technology applications, and agricultural technology solutions. The publications demonstrate consistent productivity and relevance in addressing contemporary challenges in computer science and engineering. Dr. Huh has made significant contributions to authentication systems research, particularly in biometric and behavioral authentication methods. His work on keystroke dynamics, voice spoofing detection, and wearable device authentication has advanced the field of usable security. His research extends to practical applications in smart factories, agricultural technology (AgTech), and financial technology. The integration of blockchain with AI for various applications represents a significant thread throughout his recent work, demonstrating interdisciplinary approaches to solving complex technological challenges.

Ralf Möllerمشاهده پروفایل

استاد

• Artificial Intelligence
• Humanities-Centered AI
• Causal and Probabilistic Models
• +۵ مورد دیگر

Prof. Ralf Möller is a Professor of Artificial Intelligence in Humanities at the University of Hamburg's Faculty of Humanities, Department of Philosophy. He leads the Institute of Humanities-Centered Artificial Intelligence (CHAI) and serves as spokesperson for the 'Data Linking' research field within the Cluster of Excellence ‘Understanding Written Artefacts’ (UWA, 2019–2025). His research focuses on intellectics, causal and probabilistic-relational models, and AI applications in humanities, emphasizing sustainable data management and multimodal foundation models. He heads the Data Linking Lab and the CHAI Institute, overseeing projects like the TAMAR initiative for manuscript research. His work bridges technical AI advancements with humanities needs, addressing challenges in data curation, federated information systems, and ethical AI integration. He contributes to interdisciplinary collaborations, including ethics committees and cultural heritage preservation initiatives. Key research themes include lifted inference in probabilistic graphical models, temporal data prediction, and synergistic OCR-LLM systems for damaged documents. His projects emphasize scalability, sustainability, and human-centered design principles. Supervising doctoral candidates in AI and humanities intersections, he advocates for AI systems grounded in cultural and ethical considerations. Labs/Teams: CHAI Institute, Data Linking Lab. Current Projects: UWA Cluster (2019–2025), Data Linking Infrastructure development, Humanities-Centered AI applications. Grants include leadership roles in institutional and collaborative research funding.