جست‌وجوی استاد و پژوهشگر

• Computer Vision
• Medical Imaging
• Deep Learning
• +۴ مورد دیگر

Zhifeng Wang is a Professor at the National University of Defense Technology's School of Computer Science, specializing in computer vision, medical imaging, and artificial intelligence. His research spans multiple application domains with a recent focus on medical image synthesis, 3D reconstruction, and fluid dynamics simulation. Research interests include developing advanced AI techniques for medical imaging applications, particularly in vascular structure analysis and synthesis. His work bridges computer vision with healthcare applications, focusing on creating anatomically accurate 3D representations without invasive procedures. He has made significant contributions to diffusion models, neural radiance fields (NeRFs), and meta-learning frameworks for cross-domain applications. His publication record shows a clear progression from foundational work in graph algorithms and communications systems to cutting-edge medical AI applications. Recent work demonstrates expertise in combining state space models with diffusion techniques for medical image generation, showing particular strength in maintaining anatomical continuity in 3D vascular structures. While specific awards aren't documented in the provided information, his publications in top venues including CVPR 2025 indicate significant recognition in the computer vision community. His collaborative work spans multiple institutions and research domains, suggesting an active research group with diverse funding sources. His laboratory appears to focus on medical imaging AI, with particular emphasis on non-invasive diagnostic techniques. Current projects involve developing sophisticated diffusion models that can generate high-fidelity angiographic images from non-contrast inputs, potentially reducing patient exposure to harmful contrast agents.

• 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.

• Artificial Intelligence
• Explainable AI
• Medical Imaging Analysis
• +۷ مورد دیگر

Daniel Sonntag is a Research Professor at the German Research Center for Artificial Intelligence (DFKI) in Kaiserslautern, Germany, with extensive contributions to artificial intelligence, particularly in medical applications and human-AI interaction. His work spans multiple domains including explainable AI, medical imaging analysis, eye tracking technology, and clinical decision support systems. His research interests focus on developing interpretable AI systems for healthcare applications, with particular emphasis on ophthalmology and radiology. He investigates how to make AI systems more transparent and trustworthy through concept bottleneck models, multi-agent systems, and interactive learning approaches. His work bridges the gap between theoretical AI advancements and practical clinical applications, ensuring that AI tools are both effective and understandable for medical professionals. Sonntag's publication record demonstrates a consistent trend toward more interactive and interpretable AI systems, with recent work focusing on multi-agent RAG systems for radiology report generation, clinical decision support tools for ophthalmology, and biodiversity monitoring through soundscape analysis. His research shows a strong interdisciplinary approach, combining computer vision, natural language processing, and human-computer interaction to solve complex problems in healthcare and environmental monitoring. His work has appeared in leading venues including IUI, ICMI, KI, and various IEEE and ACM conferences, reflecting his contributions to both the theoretical foundations and practical applications of artificial intelligence.

Christoph Reichمشاهده پروفایل

استاد

• Middleware
• Network Technologies
• IT Security
• +۵ مورد دیگر

Christoph Reich is a Professor at Furtwangen University (HFU), Germany, actively engaged in research and teaching within network technologies, IT security, and cloud computing systems. His academic profile reflects strong industry-relevant expertise in cyber-physical systems and industrial digitalization. Research interests include: Middleware Network Technologies IT Security Cloud Computing Quality of Service Ambient Assisted Living Distributed Software Architectures IT Management Recent publications (2020-2023) demonstrate concentrated focus on machine learning and blockchain applications in Industry 4.0 contexts. Key thematic clusters include distributed decision trees with corruption resistance, verifiable ML models via blockchain, real-time anomaly detection in industrial networks, and secure ML pipelines for manufacturing. Work consistently addresses security vulnerabilities, robustness requirements, and quality-of-service metrics in cyber-physical production systems. Scientific awards: None listed in available documentation. No information provided regarding student advising, research grants, laboratory affiliations, or collaborative teams. Office hours are conducted by appointment at Campus Furtwangen, Room C 2.08.

Piotr Kuroczyńskiمشاهده پروفایل

استاد

• Digital 3D reconstruction
• Cultural heritage documentation
• Heritage Building Information Modeling (HBIM)
• +۷ مورد دیگر

Prof. Dr.-Ing. Piotr Kuroczyński serves as Professor of Applied Computer Science and Visualization in Civil Engineering and Head of the Architecture Institute at Mainz University of Applied Sciences. His academic career spans multiple prestigious institutions including Technical University of Darmstadt where he researched and taught at the unit Information and Communication Technology in Architecture, and Warsaw University of Technology where he lectured in Computer Aided Design. His research interests focus on the intersection of digital technology and cultural heritage preservation. Kuroczyński specializes in Heritage Building Information Modeling (HBIM), digital 3D reconstruction of architectural monuments, and virtual research environments for object-based research. His work establishes documentation standards and semantic data modeling approaches for accurately representing historical structures, particularly focusing on Jewish cultural heritage sites including synagogues across Europe. He explores how digital methodologies can enhance our understanding of architectural history while preserving endangered cultural assets. Kuroczyński's publications reveal a consistent emphasis on 3D reconstruction as a scholarly research methodology rather than merely a visualization tool. His work addresses the challenges of creating FAIR (Findable, Accessible, Interoperable, Reusable) research data within digital humanities, with particular attention to historical accuracy, source documentation, and methodological transparency. His research bridges architectural history, computer science, and cultural heritage preservation through innovative digital approaches. His scientific recognition includes: The Werner Weber Award for Best Full Paper at EuroMed2016 Conference 3rd prize for German Pavilion at EXPO 2015 Milan 2nd place in ECB Visitor Center competition Winner of "Built on IT" competition Diploma with distinction from TU Darmstadt As editor-in-chief of the book series Computing in Art and Architecture at Heidelberg University Library and co-founder of the Digital 3D-Reconstruction Working Group, Kuroczyński has significantly shaped research infrastructure in digital heritage. He leads the DFG-funded 3D Viewer project creating infrastructure for digital 3D reconstructions and has received fellowships from Getty Foundation, National Endowment for the Humanities, and Volkswagen Foundation. His leadership extends to coordinating the CoVHer project on computer-based visualization of architectural cultural heritage and directing the Digital Urban History Lab for historical urban development research. Kuroczyński heads the Architecture Institute at Mainz which operates as a hub for interdisciplinary research connecting computer science, architecture, and cultural heritage preservation. The institute develops innovative methodologies for documenting historical structures, with particular focus on the 3R principle (Reduce, Reuse, Recycle) in architectural resource management and the development of standardized approaches for Heritage BIM. Current projects include the Mastering Heritage BIM workshop series and the CIPA Seoul 2025 initiative advancing documentation standards for cultural heritage.

Jakub Rosenthalمشاهده پروفایل

استاد

• Design and Product Development
• Computational Strength Verification
• Fatigue Strength
• +۳ مورد دیگر

Jakub Rosenthal serves as Professor at the Faculty of Mechanical Engineering and Environmental Technology of Amberg-Weiden University of Applied Sciences, where he also holds the position of Internship Coordinator for programs MA, MB, MO, KT, and IPM. His office is located in Building D, Room 252 in Amberg, with contact details including phone +49 (9621) 482-3339 and email j.rosenthal@oth-aw.de. Office hours for SS 2025 are Tuesdays 09:45-10:30 by appointment. His research spans critical mechanical engineering domains with emphasis on: Design and Product Development Computational Strength Verification methodologies Material Fatigue Strength analysis Mechanical Machine Elements design Advanced Computer-Aided Design (CAD) systems Finite Element Method (FEM) applications in Structural Mechanics No scientific awards were documented in available materials. Information regarding student supervision, research grants, laboratory facilities, or collaborative teams was not provided in the source documentation.

Jens Bechtholdمشاهده پروفایل

استاد

• Mechanical Engineering
• Automation Technology
• Automotive Systems
• +۵ مورد دیگر

Prof. Dr.-Ing. Jens Bechthold is a Professor in the Department of Mechanical Engineering and Automation Technology at South Westphalia University of Applied Sciences (Soest campus), a position he has held since 2010. He chairs the Mechanical Engineering Examination Committee and maintains industrial collaborations through past roles at Winergy AG and Ipsen International GmbH. His affiliations include: Full-time Professor at South Westphalia University (2010-present) Former Development Engineer at Ipsen International GmbH (2007-2010) Former Calculation Engineer at Winergy AG (2006-2007) His research spans mechanical engineering , automation , and sustainable technology , with specialized focus areas: Electric mobility and automotive system design Experimental validation of simulation models Wind turbine gearbox dynamics and vibration analysis Additive manufacturing/3D printing applications He directs the Laboratory for Design Engineering and 3D Printing Lab , facilitating hands-on student projects. He actively supports the R4 Team Westfalen, a student group competing in humanitarian rally events. His 13 publications demonstrate consistent output in mechanical systems validation, CAD education, and renewable energy technology, with recent work exploring electric vehicle innovation. Professor Bechthold teaches courses including Machine Elements, Automotive Technology, Fatigue Strength, and Design for 3D Printing. He holds a European patent for industrial furnace gas processing systems.