جستجوی استاد راهنمای دانشگاهی

Th. Udelhovenمشاهده پروفایل

استاد

• Remote Sensing
• Geoinformatics
• Environmental Monitoring
• +۶ مورد دیگر

Th. Udelhoven is a Professor and Head of the Environmental Remote Sensing & Geoinformatics Department at Trier University's Faculty of Regional and Environmental Sciences in Germany. He maintains an active research program in remote sensing technologies and environmental monitoring with extensive publications spanning over two decades. His research interests focus on Remote Sensing , Geoinformatics , Environmental Monitoring , Satellite Data Analysis , and Land Degradation Assessment . His work integrates advanced hyperspectral imaging, UAV technology, and spatial analysis techniques to address environmental challenges related to soil science, precision agriculture, and forest ecology. His methodological expertise spans from traditional remote sensing techniques to cutting-edge machine learning applications in geospatial analysis. Analysis of his recent publications reveals a strong emphasis on practical applications of remote sensing technologies for environmental monitoring, with particular focus on agricultural systems, soil health assessment, and land cover change detection. His research demonstrates consistent innovation in applying remote sensing technologies to solve real-world environmental problems across diverse geographical contexts from European agricultural landscapes to African and Asian ecosystems. Professor Udelhoven actively teaches courses including Pattern Recognition in long term global satellite archives, Statistik I: Statistische Grundlagen für die Bio- und Geowissenschaften, and Umweltwissenschaftliche Projektstudie, demonstrating his commitment to education in environmental sciences and geoinformatics. He has mentored numerous students who appear as co-authors on his publications, particularly in areas of crop monitoring, land cover analysis, and soil science applications. His collaborative research extends across multiple institutions and international boundaries, reflecting the global relevance of his work in environmental monitoring and sustainable land management.

Nathir Rawashdehمشاهده پروفایل

استادیار

• Image Processing
• Autonomous Vehicles Perception
• Mobile Robot Applications
• +۷ مورد دیگر

Nathir Rawashdeh is an Assistant Professor in the Department of Applied Computing at Michigan Technological University , with an affiliated appointment in Electrical and Computer Engineering . He is a Senior Member of the IEEE and a member of the Institute of Computing and Cybersystems (ICC) and Great Lakes Research Center . Education: Ph.D., Electrical Engineering, University of Kentucky, 2007 MS, Electrical and Computer Engineering, University of Massachusetts, Amherst, 2003 BS, Electrical Engineering, University of Kentucky, 2000 Dr. Rawashdeh's research focuses on unmanned vehicle perception , image analysis , control systems , and mechatronics , with applications in autonomous driving, winter weather adaptation, and industrial automation. His work includes sensor fusion, deep learning, and AI-enhanced manufacturing solutions. Recent publications highlight advancements in winter weather autonomous driving , UV disinfection robotics , and AI-driven industrial inspection systems . His research spans mechatronics curriculum development, industry 4.0 integration, and cross-cultural educational initiatives. Scientific Awards: Senior Member of the IEEE Dr. Rawashdeh has secured over $2 million in funding from organizations including the NSF , Ford Motor Co. , NIST , and the European Commission . His grants support projects like GPU clusters for research, winter weather autonomous driving standards, and UV sterilization robotics. He leads the Mobile Robotics Lab at Michigan Tech, focusing on collaboration and innovation in autonomous systems and mechatronics research.

• Signal and Image Processing
• Machine Learning
• Computer Science
• +۶ مورد دیگر

Yannick Berthoumieu is a Professor at the Université de Bordeaux , affiliated with the IMS Bordeaux laboratory. He leads the MOTIVE team under the Signal and Image Processing research group. His work spans Signal and Image Processing , Machine Learning , and Remote Sensing , with a focus on SAR image analysis, generative models, and geometric learning.

Franc Solinaمشاهده پروفایل

استاد

• Computer Vision
• Human-Computer Interaction
• 3D Documentation
• +۶ مورد دیگر

Franc Solina is a Full Professor at the Faculty of Computer and Information Science , University of Ljubljana, Slovenia. He holds a Ph.D. from the University of Pennsylvania and has been active in academia since the 1990s. Education: Dipl.Ing. (1979) and M.S. (1982) in Electrical Engineering, University of Ljubljana Ph.D. (1987) in Computer and Information Science, University of Pennsylvania Research Interests: His work spans Computer Vision (superquadric modeling, underwater archaeology documentation), Human-Computer Interaction (interactive art installations, sign language technology), and Air Transport Applications (machine learning for aircraft trajectory prediction). He also explores Color-Based Applications and Visual Expression in art-technology intersections. Publication Trends: Franc's 15 most recent articles focus on superquadric modeling (1990-2004), underwater archaeology (2013-2015), and machine learning applications (2020). His work bridges theoretical computer vision with practical implementations in art and aviation. Students: He has supervised notable students like Marko Hrastovec (2018 thesis on aircraft trajectory prediction) and Tim Oblak (2020 work on superquadric deep learning). Labs & Teams: A key member of the University of Ljubljana's Computer Vision Laboratory , he collaborates with international researchers in projects like the Slovenian sign language web dictionary and air traffic safety initiatives .

• Machine Learning
• Statistics
• Model-Based Clustering
• +۵ مورد دیگر

Brendan Murphy is a Full Professor in the School of Mathematical Sciences at University College Dublin since 2015, previously holding a Professor role at the same institution (2007-2015) and a Lecturer position at Trinity College Dublin (1999-2007). He is a Principal Investigator at the Insight Centre for Data Analytics and actively works in Machine Learning & Statistics. Research Focus: His work centers on Model-based clustering Mixture models Applications in sports analytics, food science, microbiome studies, and public health Bayesian statistical methods High-dimensional data analysis Article Trends: Murphy's recent publications (2024-2025) emphasize soft clustering techniques, Bayesian mixture models, and their applications across diverse domains including metabolomics, political science, and oceanography. His work addresses challenges in variable selection, robust classification, and multi-omics integration.

Pinar Okumusمشاهده پروفایل

دانشیار

• Structural Engineering
• Earthquake Engineering
• Concrete Structures
• +۵ مورد دیگر

Pinar Okumus serves as Associate Professor in the Department of Civil, Structural and Environmental Engineering at the University at Buffalo's School of Engineering and Applied Sciences. Her research focuses on advancing infrastructure resiliency through low-damage seismic systems, prefabricated concrete structures, and high-performance materials for rapid construction and repair of bridges and buildings. Her academic credentials include: PhD in Civil Engineering, University of Wisconsin, Madison (2012) MS in Civil Engineering, University of Wisconsin, Madison (2008) BS in Civil Engineering, Middle East Technical University (2006) Dr. Okumus' research integrates nonlinear structural analysis, material-scale testing, and in-situ monitoring to develop rapidly deployable infrastructure solutions. Her work emphasizes practical applications of pre-tensioned, post-tensioned, and reinforced concrete components for extreme event resilience, with particular focus on coastal infrastructure vulnerability and seismic retrofitting. The Dr. Okumus Research Group employs advanced methodologies including machine learning for structural assessment and optical fiber technologies for long-term monitoring. Recent publications (2023-2025) reveal strong thematic trends in corrosion effects on coastal infrastructure, 3D-printable cementitious composites for rapid repair, and tessellated structural-architectural systems. Her work increasingly incorporates machine learning for shear strength prediction and crack pattern analysis while maintaining core expertise in post-tensioned systems and seismic retrofit solutions. Research funding is secured through competitive grants from the National Science Foundation and Federal Highway Administration, supporting experimental validation of novel concepts like self-centering shear walls and ultrahigh-performance concrete retrofits. The group actively collaborates with transportation agencies to translate laboratory findings into field applications for bridge and building systems. The Dr. Okumus Research Group operates as an interdisciplinary team investigating structures that enable rapid reoccupation after extreme events. Current projects focus on modular systems with interlocking components, optical sensing integration for tendon force monitoring, and material innovations for climate-resilient infrastructure, maintaining strong connections with industry partners for practical implementation.

• Audio-Visual Speech Recognition
• Machine Learning
• Signal Processing
• +۹ مورد دیگر

Satoru Hayamizu is a Professor at Waseda University 's Green Computing Systems Research Organization , with a career spanning over four decades. His research focuses on Audio-Visual Speech Recognition , Machine Learning , and Medical Informatics , as evidenced by 126 publications and an h-index of 18. Education: The University of Tokyo (PhD in Mechanical Engineering) Prior affiliations: Gifu University (2002-), National Institute of Advanced Industrial Science and Technology (1981-2001) Research Interests include: Audio-visual speech recognition with sparse representation and DNN techniques Development of low-cost CNN-based road condition detection systems Swallowing function evaluation using acoustic and image processing Human behavior analysis for service operation estimation Research Trends reveal consistent work in multimodal signal processing (2006-2024), deep learning applications (2012-2024), and medical diagnostic systems (2006-2017). His publications show integration of sparsity modeling (2012-2021), industrial equipment diagnostics (2018-2021), and social impact technologies (2013-2024). Research Projects funded by Japan Society for the Promotion of Science include: Swallowing timing estimation (2018-2021) Multimodal silent speech recognition (2016-2020) ICT-based piano learning systems (2013-2016) Keyword display mechanisms (2010-2012) Labs & Collaborations include partnerships with Satoshi Tamura (co-author on 12+ papers), Hidekazu Fukai , and Chiyomi Miyajima . His work bridges academic research and industrial applications , particularly in manufacturing AI (2024 book) and Timor-Leste infrastructure monitoring.

Wlodek Kuleszaمشاهده پروفایل

استاد

• Systems Engineering
• Measurement and Instrumentation
• Sensor Networks
• +۳ مورد دیگر

Wlodek Kulesza is a Senior Professor in the Department of Mathematics and Natural Sciences at the Blekinge Institute of Technology in Karlskrona, Sweden. He has held academic positions since 2001, including a Professorship in Multi-sensor Systems since 2007. Research: Multisensory systems for health and security applications Teaching: Research Methodology, Philosophy of Science, and Sensors Signals and Systems Expertise: Systems engineering, sensor fusion, IoT, and measurement data handling Research Focus : His work in systems engineering emphasizes multisensor integration for applications spanning healthcare, security, wind energy safety, and subsea cable monitoring. He has pioneered approaches to stereovision calibration, localization algorithms, and real-time safety systems. Awards : Andy Chi Best Paper Award (2009, IEEE Transactions in Measurement and Instrumentation) Collaborations : Visiting Professor at Chinese and Polish universities, with extensive cross-border educational workshops and remote lab federations (e.g., PILAR/VISIR projects).

Shafaeat Hossainمشاهده پروفایل

استاد

• Machine Learning
• User Authentication in Smart Devices
• Behavioral Biometrics
• +۱ مورد دیگر

Shafaeat Hossain is a Professor in the Department of Computer Science at Southern Connecticut State University (SCSU) . He holds a Ph.D. in Computational Analysis and Modeling from Louisiana Tech University (2014) and advanced degrees from the University of Dhaka. His research focuses on machine learning , user authentication in smart devices , behavioral biometrics , and multi-biometric verification . B.S. in Computer Science and Engineering, University of Dhaka (2006) M.S. in Computer Science, Louisiana Tech University (2012) Ph.D. in Computational Analysis and Modeling, Louisiana Tech University (2014) His work bridges machine learning with security applications , particularly in touchscreen gesture analysis , continuous authentication , and behavioral biometrics for smartphones. He explores multi-biometric fusion strategies to enhance security and user convenience, while also investigating game theory in social networks and NLP for deep authorship attribution . Recent publications highlight advances in capacitive swipe authentication , zoom gesture analysis , and Wi-Fi indoor positioning . Collaborative studies address sleep apnea diagnosis and smartwatch dynamics in verification systems. SCSU Faculty Scholar Award (2023) SCSU Mid-Level Faculty Research Fellowship (2019) Senior Member, IEEE He has secured grants totaling over $25,000 from SCSU, CSU-AAUP, and UConn for projects on child safety in digital authentication and multi-biometric security enhancement . His scholarship spans IEEE Access , Computers & Security , and top-tier conferences like IEEE IJCNN and SMARTCOMP .

• agent and multi-agent systems
• online auctions
• machine learning
• +۶ مورد دیگر

Patricia Anthony serves as Associate Professor at Lincoln University's School of Landscape Architecture in New Zealand, where she holds an ORCID identifier 0000-0002-4991-3340. Her academic appointments include Faculty Postgraduate Chair for the Faculty of Environment, Society and Design (2021-2024) and current affiliation with the Centre for Geospatial and Computing Technologies (2025-present). Previously, she served as Head of Department (2016-2017), Department Postgraduate Coordinator (2014-2016), and SHIFT Coordinator (2017-2020). Her educational background comprises a Ph.D. from the University of Southampton, United Kingdom; an M.Sc. from Birkbeck, University of London, United Kingdom; and a BSc (High Honors) from the State University of New York, United States. She is proficient in Malay language, with reading, writing, and speaking capabilities. Dr. Anthony's research centers on agent and multi-agent systems, utilizing artificial intelligence techniques including machine learning, evolutionary computation, and text processing as decision-making strategies for agents. She is recognized as a leading researcher applying intelligent agents across diverse domains such as online auctions, agriculture, education, and social media analysis. Her specialized work in sentiment analysis and emotion identification enables agents to detect emotional states in textual communications, with recent applications in earthquake tweet analysis. Her publication record demonstrates consistent scholarly output with over 130 publications, showing particular strength in applying multi-agent systems to practical challenges. Recent work reveals three major research streams: trust and reputation management in IoT environments (accounting for approximately 30% of recent publications), agricultural technology applications including mastitis detection and water resource management (approximately 40%), and social media analysis focusing on elderly technology adoption and cyber aggression classification (approximately 30%). Adjunct Professor, Hubei University of Technology, Wuhan, China Program Committee/Senior Program Committee member for Pacific Rim International Conferences on Artificial Intelligence (PRICAI) 2016, 2018, 2019 Co-chair for International Carnahan Conference on Security Technology (ICCST) 2014, 2016, 2018, 2020 Member of Institute of Electrical and Electronics Engineers (IEEE) Reviewer for Engineering Applications of Artificial Intelligence, Malaysian Journal of Computer Science, and Adaptive Behaviour Dr. Anthony has supervised numerous postgraduate students across multiple research areas related to multi-agent systems, with completed projects spanning cyber aggression classification, agricultural technology, IoT security, and elderly technology adoption. She serves as an examiner for advanced computing courses including Advanced Database (COMP643), Advanced Programming (COMP642), and Studio Project (COMP639), demonstrating her integration within the university's computing curriculum despite her Landscape Architecture appointment. Her research aligns with Sustainable Development Goal 11 (Sustainable Cities and Communities), reflecting her commitment to applying computational techniques to address real-world challenges in urban and community contexts. She actively collaborates across disciplines through the Centre for Geospatial and Computing Technologies, bridging computational methods with landscape architecture applications.

Chang Liuمشاهده پروفایل

پژوهشگر

• Medical Image Processing
• CT Image Analysis
• AI Applications in Healthcare
• +۳ مورد دیگر

Chang Liu is a Research Associate at NHR@FAU (Center for National High Performance Computing Erlangen) at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), where he joined the AI group in April 2025 to support AI-oriented projects across diverse research fields. Prior to this position, he was a doctoral researcher at the Pattern Recognition Lab at FAU until March 2025. Chang Liu earned his degree in Medical Engineering at FAU. His academic journey at FAU began in September 2016 as a student, progressed to a researcher at the Pattern Recognition Lab starting in March 2020, and culminated in his doctoral research until March 2025. Dr. Liu's research focuses on medical image processing and analysis, with particular emphasis on the automated segmentation of computed tomography (CT) images and the generation of high-quality CT images. His work bridges computer science and medical applications through artificial intelligence to solve complex healthcare problems. Beyond his core research, he has contributed to applying AI technologies in diverse fields including second language education and nail disease diagnosis, demonstrating his interdisciplinary approach to problem-solving. His expertise spans data augmentation techniques, multi-organ segmentation, CT reconstruction, and radiation dose optimization. His publication record reveals consistent advancement in medical image analysis techniques, particularly in CT imaging and segmentation. His work shows a progression from foundational deep learning applications to more sophisticated approaches incorporating anatomical knowledge and addressing practical clinical constraints like limited annotations and radiation safety. Dr. Liu has mentored numerous students through their thesis work, guiding them in cutting-edge research at the intersection of AI and medical imaging. His advisees have completed projects on breast cancer risk stratification, medical segmentation annotation, U-Net architecture configuration, and other innovative topics in medical image analysis. As part of NHR@FAU, Dr. Liu works with the AI group to enhance research projects using modern high-performance computing systems, applying his expertise in medical image analysis to support diverse research fields across FAU.

Ning Yuمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +۶ مورد دیگر

Ning Yu serves as an Associate Professor in the Department of Computing Sciences within the School of Arts & Science at State University of New York Brockport. He earned his Ph.D. in Computer Science from Georgia State University and joined SUNY Brockport in 2017 after serving as a Tenure-Track Assistant Professor at the University of South Carolina Upstate. Georgia State University, Computer Science, Ph.D. Southern Illinois University Carbondale, Computer Science, M.S. Dr. Yu's research spans artificial intelligence, network and information security, big data analytics, deep learning, and cloud computing with significant applications in bioinformatics. His work demonstrates a clear progression from foundational AI and security research toward specialized applications in healthcare and energy systems. The most recent publications show increased focus on graph-based deep learning approaches for biomedical problems, particularly in cancer genomics and drug response prediction. His scholarly impact includes over 40 publications in prestigious venues including ACM/IEEE Transactions, BMC, PLoS, and Information Sciences. The publication trend reveals consistent output with increasing emphasis on interdisciplinary applications, particularly at the intersection of AI and biomedical research. Teacher of The Year, School of Science and Art, SUNY Brockport 2022-2023 Influential Professor 2022, SUNY Brockport, Fall 2023 Provost Post-Tenure Scholarship Award, $3,500, SUNY Brockport, Spring 2024 Google Research Credits Grants (2018, 2020-2021) WORLDWIDE TOP 10 FINALISTS, IBM 2017 Watson Analytics Global Competition As an educator, Dr. Yu has mentored numerous undergraduate researchers who have presented at national conferences including NCUR and SURC. He founded SUNY Brockport's first ACM SIGAI Student Chapter and has secured significant funding including a multi-campus SUNY IITG grant for AI education development. His research group actively recruits students for projects involving cloud development (Azure/GCP/AWS), CI/CD, Docker/K8s, and software architecture. Prior to academia, Dr. Yu accumulated 10 years of professional experience in software development and system networking with certifications from Cisco, Microsoft, and Google.

Sanka Rasnayakaمشاهده پروفایل

مدرس

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۶ مورد دیگر

Sanka Rasnayaka is a Lecturer at the School of Computing, National University of Singapore , where he has worked since 2022. He previously served as a full-time Teaching Assistant and PhD candidate at the same institution. PhD in Computer Science (2021), National University of Singapore B.Sc. Engineering (Honours) in Computer Science and Engineering (2016), University of Moratuwa, Sri Lanka Research interests focus on Artificial Intelligence and Computer Vision , specifically in biometrics, privacy, and human perception. Current projects explore: Biometrics & Continuous Authentication (gait, keystroke dynamics) Large Language Models for Software Engineering Physics-Informed Generative AI for flood modeling Recent publications demonstrate expertise in: Biometric authentication systems Privacy-preserving AI Transformer architectures for behavioral analysis Generative AI in environmental modeling Teaching includes foundational courses like CS1101S Programming Methodology (co-teaching since 2022) and CS2040 Data Structures and Algorithms (AY2410). He also developed workshops on Generative AI, LLMs, and Computer Vision. Projects supervised: CRISP Platform for classroom management Live Annotation Tool for educators AI Pal for customized LLM assistants Scientific awards include multiple Teaching Excellence Awards (2024-2025) and scholarships from NUS (2017-2021).

Christopher F Barnesمشاهده پروفایل

دانشیار

• Synthetic Aperture Radar (SAR)
• Signal Processing
• Data Mining
• +۵ مورد دیگر

Christopher F. Barnes is an Associate Professor in the School of Electrical and Computer Engineering at the Georgia Institute of Technology, with adjunct status as a Principal Research Engineer at the Georgia Tech Research Institute (GTRI). He holds a Ph.D. from Brigham Young University (1989) and has over 27 years of experience in radar signal processing, software engineering, and applied research. His research focuses on synthetic aperture radar (SAR) analysis, data mining, and image/video-driven technologies with applications in remote sensing, medical imaging, and seismology. Dr. Barnes' expertise includes radar imaging algorithms, software architectures for radar systems, and object-oriented programming. He pioneered methods for three-dimensional coherently fused SAR imaging and developed image-driven systems for hurricane damage assessments and bioinformatics. His work in video tracking and content-based search leverages residual vector quantization and machine vision techniques. Notable achievements include the Georgia Tech Outstanding Professional Education Award (2009) and an Interdisciplinary Research Initiative Award (2006). His contributions span over 140 publications and one patent, with research supported by defense and academic collaborations. Dr. Barnes teaches SAR at professional and graduate levels and advises research in video-driven data mining and medical imaging applications. His current projects explore AI-driven SAR analysis and advanced radar system architectures.

Solveig Bruvollمشاهده پروفایل

دانشیار

• Autonomous Systems
• Cybersecurity
• Military Technology
• +۴ مورد دیگر

Solveig Bruvoll is an Associate Professor at the University of Oslo (15% position) and holds a 100% research position at the Norwegian Defence Research Establishment (FFI). She specializes in Autonomous Systems and Cybersecurity , focusing on security in military operations and software resilience. Her work bridges engineering, mathematics, and defense applications. Research interests include autonomous vehicle security, defense simulation, and mathematical modeling. She teaches the course TEK5510 and has published extensively in conferences like IEEE CNS and journals such as Journal of Defense Modeling and Simulation . Her FFI affiliation emphasizes practical military technology and operational analysis. Publications highlight contributions to path planning algorithms, command agent modeling, and cybersecurity frameworks for autonomous systems. She collaborates on NATO projects, as seen in her work on M&S support for operational tasks. No awards are explicitly listed, but her research impacts critical defense and civilian infrastructure security domains.