جست‌وجوی استاد و پژوهشگر

Bernd Schweibenzمشاهده پروفایل

استاد

• Construction Management
• Digitalization in Construction
• Life Cycle Costs
• +۳ مورد دیگر

Prof. Bernd Schweibenz is a Professor of Construction Operations and Management at the Department of Civil Engineering, University of Applied Sciences Potsdam. He also serves as an Academic Advisor for Civil Engineering programs and is a member of the Departmental Council. His career includes roles at Biberach University of Applied Sciences (2008–2012) and the Technical University of Munich (1999–2005). He is a certified consulting engineer specializing in construction management, supplementary claims, and organizational consulting. Research focuses on: Optimization of manufacturing and business processes Digitalization in construction management (BIM) Recruitment and personnel development in construction Life cycle cost analysis of buildings Publications span topics like Generation Y workforce expectations, PPP project frameworks, and construction documentation technologies. He actively contributes to industry standards through roles in associations like VDI and VSVI. His consulting practice addresses organizational challenges in the construction sector. Professional memberships include the Association of Consulting Engineers (VBI), Association of German Engineers (VDI), and Research Association for Road and Transport Engineering (FGSV). His career bridges academia with practical expertise in public infrastructure, audit practices, and construction technology.

Volker Skwarekمشاهده پروفایل

استاد

• Cybersecurity
• Distributed Systems Security
• IoT and Sensor Networks
• +۳ مورد دیگر

Prof. Volker Skwarek is a Professor for Technical Informatics at the Department of Industrial Engineering and Management, Hamburg University of Applied Sciences. He leads the research group DLT³-Hamburg and heads the research and transfer center for digital business processes. His work focuses on cybersecurity in distributed systems, IoT security, and blockchain applications in industrial environments. He has held leadership roles including Deputy Head of the Department HWI and coordinates the graduate focus area 'Information Science'. Research interests include ultra-low-power IoT systems, self-sovereign identity frameworks, and secure blockchain-sensor integrations. Prof. Skwarek has authored over 30 peer-reviewed articles, 2 books, and multiple patents. He actively contributes to international standardization of blockchain technologies and serves on editorial boards for distributed ledger journals. His projects span smart grid security, decentralized energy trading systems, and forensic blockchain analysis. Notable projects include WaterGridSense 4.0 (smart grid resilience), LegalBlock (legal frameworks for smart contracts), and TrustedCamApp (secure video streaming in sensor networks). He emphasizes practical applications alongside theoretical advancements, collaborating closely with industry partners to address real-world challenges in digital security and automation. Prof. Skwarek holds national/international awards for research and education innovation. His teaching includes courses on technical informatics, programming in C, and cybersecurity fundamentals. He advocates for continuous professional development through academic-industry partnerships and standardization initiatives.

Anna Stöcklمشاهده پروفایل

استادیار

• Insect Neurobiology
• Visual Systems
• Animal Behavior
• +۳ مورد دیگر

Anna Stöckl is a junior professor and Research Fellow at the Zukunftskolleg, University of Konstanz, leading an Emmy Noether research group. Her work focuses on insect vision and flight control, particularly in moths. She studies how these insects navigate dynamic light environments using their nervous systems, despite limited neural resources. Her ERC-funded 'DynamicVision' project combines neuroanatomical studies, electrophysiology, and behavioral experiments, leveraging the University's Imaging Hangar facility for large-scale flight analysis. Awards include the prestigious ERC Starting Grant and leadership of an Emmy Noether group. Research interests center on sensory-motor integration, visual processing, and ecological adaptations in insects. Her methods bridge lab and field studies, emphasizing naturalistic conditions. Science communication efforts include TED-Ed videos and participations in science slams, reflecting her commitment to public engagement.

Marcus Magnorمشاهده پروفایل

استاد

• Computer Science
• Computer Graphics
• Visual Computing
• +۷ مورد دیگر

Prof. Dr.-Ing. Marcus Magnor is a full professor of Computer Science at Technische Universität Braunschweig (TU Braunschweig) and holds an adjunct professorship in the Department of Physics and Astronomy at the University of New Mexico, USA. He leads the Computer Graphics Lab at TU Braunschweig and has held roles such as Department Chair (2015–2019) and Vice Chair (2019–2023). His research focuses on visual computing, encompassing image processing, computer graphics, astrophysics visualization, and computational photography. Magnor has received accolades including the Wissenschaftspreis Niedersachsen and is an alumnus of the Alexander von Humboldt Foundation. Education: BA in Physics (1995, Würzburg University), MS in Physics (1997, University of New Mexico), PhD in Electrical Engineering (2000, Erlangen University), and habilitation in Computer Science (2005, Saarland University). He conducted postdoctoral research at Stanford University and the Max-Planck-Institut Informatik. Research emphasizes interdisciplinary applications, such as planetary nebulae visualization, flame dynamics, and garment motion capture. He has organized major conferences like Vision, Modeling, and Visualization (VMV) and served on editorial boards for journals like Computer Graphics Forum. His contributions span over 100 publications in top-tier venues, addressing topics like light field coding, free-viewpoint video, and 3D reconstruction. Awards and Honors: Fulbright Scholar (former), Elected Member of Braunschweigische Wissenschaftliche Gesellschaft, and Leadership roles in initiatives like EXC PhoenixD and the L3S Research Center. Professional Service: Technical Program Co-Chair for conferences, guest editorships, and leadership in university administrative roles. His work bridges academic research with applications in astrophysics, medical imaging, and visual entertainment technologies.

• Cognitive Science
• Psychology
• Computational Modeling
• +۵ مورد دیگر

Andrew Perfors is a Professor of Psychology at the University of Melbourne, leading the Complex Human Data Hub and the Computational Cognitive Science Lab within the Melbourne School of Psychological Sciences . His research focuses on applying quantitative methods to understand higher-order cognition, including concepts, language, decision-making, and misinformation dynamics. He employs computational models and experimental approaches to investigate how cognitive constraints and social environments shape human behavior at individual and group levels. Education: PhD in Brain & Cognitive Sciences (MIT, 2008), MA in Linguistics (Stanford, 2000), BSc in Symbolic Systems (Stanford, 1999). Research Themes: Cognitive modeling of decision-making, cultural evolution, language acquisition, and misinformation spread. His work bridges computational methods with psychological experimentation, exploring topics like sampling assumptions in reasoning, trust in information sources, and the cognitive basis of gender categorization. Key Projects: Active grants include Understanding Information and Trust (2018–2025), Bridging the Meaning Gap (2023–2027), and Anti-trans Disinformation Campaigns analysis. Recent work addresses misinformation mitigation strategies and the cognitive naturalness of trans-inclusive gender categories. Grants & Collaborations: Funded by ARC and NHMRC. Collaborations include work on contact-tracing technologies during the pandemic and cross-cultural studies on privacy calculus. Labs & Teams: Directs the Complex Human Data Hub, focusing on societal challenges like misinformation and cultural dynamics. Leads interdisciplinary teams in the Computational Cognitive Science Lab, integrating psychology, computer science, and linguistics.

Steffen Lepaمشاهده پروفایل

مدرس

• Media Reception Studies
• Sound and Music Perception
• Digital Media Transformation
• +۲ مورد دیگر

Dr. Steffen Lepa is a Post-Doc Researcher and Lecturer at TU Berlin's Audiocommunication department, where he leads the Computational Musicology team. His research examines media reception patterns, sound perception, and digital transformation of music culture using empirical and computational methods. Lepa's work bridges media studies and acoustics, with current projects investigating how audio technologies shape musical experiences. His recent publications focus on cross-cultural soundscape analysis, digital music platforms, and accessible music technologies for special education. Recent articles demonstrate consistent focus on perceptual validation of audio technologies across different cultural contexts and user groups. Methodological innovations include development of research tools like Spotivey for integrating streaming data with behavioral studies.

Eamonn Bellمشاهده پروفایل

استادیار

• Digital Humanities
• History of Computing
• Digital Musicology
• +۴ مورد دیگر

Eamonn Bell is an Assistant Professor in the Department of Computer Science at Durham University, specializing in digital humanities with a focus on the history of digital audio media, particularly the CD format and early computational applications in music studies. He holds a PhD in Music Theory from Columbia University (2019), where he completed his dissertation on 'The Computational Attitude in Music Theory' under Joseph Dubiel, and previously earned a joint honors degree in Mathematics and Music from Trinity College Dublin (2013). His research interests span digital humanities, media archaeology, and the intersection of computing history with musicology. Bell has conducted significant research on the CDLink platform developed by The Voyager Company, exploring how early web technologies enabled time-synchronized interactions with audio CDs. His scholarly work examines the historical development of digital audio formats, particularly the Compact Disc, and their cultural implications. Bell's publications reveal a consistent focus on the materiality of digital media, particularly how the CD format transformed music consumption and production. His research analyzes the technical specifications of CD encoding (including interleaving and error correction), the historical context of CD adoption, and the cultural narratives surrounding digital audio. He has also written extensively about AI's relationship to musical knowledge and creativity, situating contemporary discourse within historical contexts of computational approaches to music. Government of Ireland Postdoctoral Fellowship (2019) for 'Opening the 'Red Book': The digital Audio CD format from the viewpoint between musicology and media studies' Research funded by UK Research and Innovation (UKRI) and the Irish Research Council Bell maintains an active scholarly presence through his personal website and academic publications, contributing to ongoing conversations about digital preservation, media archaeology, and the historical understanding of contemporary digital music practices. His work bridges technical understanding of media formats with critical cultural analysis.

• Computer Vision
• Machine Learning
• Signal Processing
• +۶ مورد دیگر

Qian Huang is a Professor in the Department of Computer Science at Sun Yat-sen University's School of Computer Science and Engineering. With over 350 publications spanning from 1992 to 2025, Dr. Huang has established themselves as a leading researcher in multiple interdisciplinary fields at the intersection of computer science, engineering, and applied mathematics. Dr. Huang's research spans several critical domains in modern computing. Their primary interests include computer vision with applications in medical image analysis, machine learning with emphasis on transformer architectures and federated learning, signal processing for video compression, and wireless communications for IoT applications. Recent work demonstrates significant contributions to nuclei segmentation in cervical cell images, advanced video compression techniques using spatiotemporal modeling, and predictive maintenance systems for industrial equipment that incorporate uncertainty quantification. An analysis of Dr. Huang's 15 most recent publications reveals a strong trend toward interdisciplinary research that bridges theoretical computer science with practical applications. Their work consistently addresses real-world challenges in healthcare diagnostics, industrial automation, and communication systems. The publications demonstrate expertise in developing novel deep learning architectures while maintaining theoretical rigor in mathematical foundations. Multiple publications in IEEE Transactions journals across various domains Regular contributions to top-tier conferences including ICASSP, ICIP, NeurIPS, and CVPR Collaborations with researchers from leading institutions globally Dr. Huang's research program appears well-funded through collaborations with industrial partners and Chinese national research grants, though specific grant information isn't detailed in the publication record. Their work on federated learning frameworks and medical image analysis suggests strong connections with healthcare technology companies and medical research institutions. The extensive publication record across multiple domains indicates leadership of a substantial research group with expertise spanning computer vision, machine learning, and signal processing.

• Artificial Intelligence
• Machine Learning
• Remote Sensing
• +۶ مورد دیگر

Xing Jin is a Researcher affiliated with the University of Health and Rehabilitation Sciences in Qingdao, China. His work spans multiple domains including Artificial Intelligence , Machine Learning , and Remote Sensing , with a focus on Facial Expression Recognition , Environmental Monitoring , and Cybersecurity . Recent research involves Transformer-based models for emotion detection under the Internet of Medical Things (IoMT) , UAV remote sensing for water quality analysis, and Q-learning applications in public goods game theory. His 2025 publications highlight deep learning architectures , generative verification , and multi-turn reinforcement learning for LLM agents. He has no explicitly stated scientific awards or advising roles in the provided data. His collaborative work includes cybersecurity mechanisms for HTML5-based mobile apps , energy-efficient cloud computing , and biomedical signal processing to study anesthesia effects. Key co-authors include Zhen Wang , Wenlei Shi , and Dan Pei . His 2025 articles address environmental informatics , generative modeling , and medical AI .

• Hepatocellular Carcinoma
• Immunotherapy in Oncology
• Liver Diseases
• +۳ مورد دیگر

Johann von Felden is a Professor in the Department of Gastroenterology and Hepatology at the University of Hamburg’s Medical School (Medizinische Fakultät). His primary affiliation is with the University Medical Center Hamburg-Eppendorf (UKE), where he leads research in hepatocellular carcinoma (HCC), immunotherapy, and biomarker development. His work focuses on improving patient outcomes through precision medicine, prognostic scoring systems (e.g., ALBI, Child-Pugh), and understanding molecular mechanisms in liver cancer progression. Research interests include the efficacy of systemic therapies like atezolizumab/bevacizumab, genetic and epigenetic drivers of HCC, and the role of cytokines, extracellular vesicles, and circulating tumor cells in disease monitoring. Collaborations span clinical trials, translational research, and genomic analyses to address treatment resistance and toxicity. Publications highlight innovations in biomarker discovery, such as unannotated small RNA clusters and metabolomic signatures, as well as optimizing treatment strategies for HCC patients with cirrhosis or autoimmune liver disease. His work emphasizes translating findings into clinical practice, including refining prognostic tools and identifying patients eligible for immunotherapy rechallenge or sequential treatments.

Thomas Schierlمشاهده پروفایل

پژوهشگر

• Video Coding
• Wireless Communication Protocols
• Multimedia Systems
• +۳ مورد دیگر

Dr. Thomas Schierl is the Head of the Video Communication and Applications Department at Fraunhofer Heinrich Hertz Institute (HHI) in Berlin. Since 2010, he has led research groups in multimedia communications and video coding, co-developing key video coding standards such as H.264 SVC and HEVC. He currently heads the Video Coding & Analytics department since 2015, focusing on video compression, wireless transmission, and standardization. Education: Diplom-Ingenieur (Computer Engineering) from Berlin University of Technology, 2003 Dr.-Ing. in Electrical Engineering and Computer Science, Berlin University of Technology, 2010 Research interests span video over wireless networks, system integration of video codecs, and cellular network protocols. He contributed to MPEG-2 Transport Stream standards and co-authored IETF RFCs for video payload formats. In 2014, he received the Emmy Award for MPEG-2 Transport Stream development. Active in standardization bodies: JCT-VC, MPEG, IETF, 3GPP, and DVB. His work includes high-level syntax for HEVC parallelism and V2X resource pooling for 5G NR. Labs/Teams: Leads the Video Coding & Analytics team at HHI, specializing in cutting-edge video compression and communication technologies.

Ralf Schaeferمشاهده پروفایل

پژوهشگر

• Digital Video Coding
• Image Processing
• Video Analytics
• +۴ مورد دیگر

Ralf Schaefer is a renowned academic and Division Director at the Fraunhofer Heinrich Hertz Institute (HHI) in Berlin, where he leads the Video Division with 90 researchers and oversees 50 undergraduate students. His career spans decades of innovation in video and imaging technologies. Education: Electrical Engineering at Technical University Berlin (TUB), earned doctorate (Dr.-Ing.) in 1984 for work on digital video coding of TV signals. Research Interests: Focus on end-to-end video technologies, including digital video coding , image acquisition/display systems , algorithm development , and ASIC implementation . His work bridges theoretical research and industrial applications in vision technologies and smart data solutions . Leadership Roles: Founded three technology centers: CINIQ Center for Data and Information Intelligence , Innovation Center for Immersive Imaging Technologies (3IT) , and the Tomorrow's immersive Media Experience (TiME) Lab . Active member of the German Society for Information Technology (ITG) and Society for Television and Motion Picture Technology (FKTG) , leading ITG’s “Digital Coding” expert group for over 20 years. Scientific Recognition: Honored with prestigious awards including the ITG Paper Award and the Richard Theile Medal , reflecting his influence in video coding and media technologies.

• Healthcare Applications
• ECG Signal Processing
• Sleep Apnea Detection
• +۵ مورد دیگر

Nuno Gonçalo Coelho Costa Pombo is an active researcher and faculty member at the University of Beira Interior, Portugal, where he works in the School of Technology and Management within the Department of Computer Science. His academic career spans over a decade with consistent publication output from 2014 through 2025, demonstrating sustained research productivity and evolving expertise across multiple domains. Dr. Pombo's research interests center on the intersection of computer science and healthcare applications. His work prominently features ECG signal processing for medical diagnostics, with significant contributions to sleep apnea detection systems and clinical decision support systems . He has pioneered approaches in activities of daily living recognition using sensor data from mobile devices, which has important applications in elderly care and chronic disease management. His research methodology often combines machine learning techniques with Internet of Things (IoT) frameworks to create healthcare monitoring solutions that balance effectiveness with user privacy concerns. Recent work has expanded into educational technology applications, including augmented reality for programming instruction and futuristic thinking development in education. An analysis of Dr. Pombo's publication trends reveals a natural progression from foundational research in activity recognition to increasingly sophisticated healthcare applications. His early work focused on basic activity recognition frameworks, while more recent publications demonstrate advanced applications in specific medical conditions including diabetes management, mental health support, and cardiovascular diagnostics. The interdisciplinary nature of his research is evident in his extensive collaborations across engineering, medical, and social science domains, reflecting a holistic approach to healthcare technology development. Dr. Pombo maintains an active supervision role, with numerous publications featuring co-authors who appear to be students or early-career researchers. His work has been supported by research initiatives focused on healthcare technology innovation, though specific grant details are not evident from publication records. The consistent output across reputable venues including IEEE Access, Sensors, and international conferences demonstrates sustained research impact in his field.

• Internet of Things
• Edge Computing
• Smart Agriculture
• +۵ مورد دیگر

Professor Yi-Bing Lin is a distinguished faculty member in the Department of Computer Science at National Yang Ming Chiao Tung University, Taiwan, where he leads pioneering research in Internet of Things (IoT) systems and applications. His work primarily focuses on developing the IoTtalk platform and its numerous derivatives across various domains including smart agriculture, smart homes, environmental monitoring, and creative applications. His research interests span Internet of Things, Edge Computing, Smart Agriculture, Sensor Networks, AI Integration, Wireless Networking, and Smart Home Systems. Professor Lin has developed the IoTtalk framework that enables rapid development of IoT applications with numerous specialized implementations including VoiceTalk, SensorTalk, AgriTalk, and many others that address specific domain challenges. His work emphasizes practical implementations with real-world impact, particularly in precision agriculture where his team has developed systems for orchid disease detection, rice blast monitoring, turmeric farming, and watermelon ripeness prediction. Analysis of his recent publications (2023-2025) reveals a strong trend toward integrating AI with IoT systems, particularly for agricultural applications and smart environments. His work increasingly incorporates advanced techniques like continuous wavelet transform, deep learning, and computer vision to solve practical problems in precision farming and environmental monitoring. The publications also show growing interest in creative applications of IoT technology for performing arts, interactive experiences, and educational contexts. Professor Lin has received recognition through consistent high-volume publication output in top-tier venues including IEEE Internet of Things Journal, IEEE Access, and Sensors. His collaborative network is extensive, with frequent co-authorship with researchers like Yun-Wei Lin, Wen-Liang Chen, and Min-Zheng Shieh. His advising has produced numerous researchers who continue to work in IoT and related fields, with many former students maintaining collaborative relationships. Professor Lin's research has been supported by multiple grants enabling the development of practical IoT systems with real-world implementations. His lab has developed numerous specialized IoT applications through the IoTtalk framework, creating a cohesive research ecosystem. Current work shows expansion into new application domains including interactive miniature worlds, simultaneous performance across locations using IoT-based motion capture, and IoT-based musical instruments like piano playing robots and violin robots, demonstrating the versatility of his research approach.

• Cloud Computing
• Blockchain Technology
• Data Security
• +۵ مورد دیگر

Xiaojun Zhang is a Professor actively contributing to cloud computing, blockchain technology, data security, and educational technology. His work spans cybersecurity, signal processing, and wireless systems. Key Research Areas: Privacy-preserving data aggregation, machine learning for biomedical imaging, blockchain-based integrity auditing, and educational metacognition studies. Recent Article Trends (2022–2025): Focus on secure federated learning, data denoising algorithms, and blockchain applications in smart grids, healthcare, and education. Collaborations include institutions in China and international researchers.