جست‌وجوی استاد و پژوهشگر

Ardhendu Beheraمشاهده پروفایل

استاد

• Computer Vision
• Deep Learning
• Multimodal AI
• +۴ مورد دیگر

Ardhendu Behera is a Professor of Computer Vision & AI at Edge Hill University and co-director of the Intelligent Visual Computing Research Centre. He holds a post-doctoral background from the University of Leeds and has contributed to interdisciplinary research in AI-driven healthcare, autonomous systems, and defense applications. His work bridges computer vision with multimodal AI, emphasizing real-world impact through collaborations with institutions like the University of Bristol, IISc Bangalore, and UCL. Prof Behera’s research spans deep learning, healthcare diagnostics, and autonomous vehicle systems. He has pioneered AI tools for dementia monitoring (via social robotics and multimodal data) and developed algorithms for traffic scene analysis, driver behavior recognition, and medical imaging. His recent projects include breast cancer detection networks and plant disease recognition systems using transfer learning. Key Awards: Fellow of the UK Higher Education Academy (HEA) Editorial Roles: Associate Editor for IEEE Transactions on Image Processing Outreach: Media coverage on BBC News, ITV, and The Times for dementia research; keynote speaker at NCVPRIPG 2019 and ICIoT 2019 His research emphasizes interdisciplinary collaboration, with over 100 peer-reviewed publications in top-tier venues like CVPR, ECCV, and IEEE journals. He actively mentors students in PhD/MRes programs focusing on AI and computer vision applications.

• Computer Vision
• Machine Learning
• Medical Imaging
• +۲ مورد دیگر

Lazaros T. Tsochatzidis is a researcher with significant contributions to computer vision , machine learning , and their applications in medical imaging and autonomous driving . He has published extensively in top-tier venues like Pattern Recognition , IEEE Access , and Robotics and Autonomous Systems , often collaborating with researchers such as Ioannis Pratikakis and Konstantinos Zagoris . Research Interests Specializes in LiDAR-based 3D object detection for autonomous vehicles Developed domain adaptive object detection techniques using mean teacher models Innovated part-aware graph fusion for skeleton-based action recognition Expert in medical image analysis for breast cancer diagnosis Contributed to historical document transcription and sclera segmentation research Scientific Awards No explicit awards mentioned in available data Notable Collaborations Long-term collaboration with Konstantinos Zagoris (6 co-authored papers) Extensive work with Ioannis Pratikakis (11 co-authored publications) Multidisciplinary collaborations with experts in medical imaging , autonomous systems , and biometric security

Alpay DORUKمشاهده پروفایل

مدرس

• Information Security
• Cryptology
• Embedded Systems
• +۵ مورد دیگر

Alpay DORUK is a Lecturer and the Head of the Cyber Security Department at the Faculty of Engineering and Natural Sciences, Bandirma Onyedi Eylul University. Previously, he served as a Lecturer at Tekirdag Namik Kemal University (2011–2020) and a Research Assistant at Izmir Institute of High Technology (1999–2011). His expertise spans Information Security, IoT, and Embedded Systems, with a focus on ontology engineering, machine learning applications, and sensor networks. Research highlights include developing ontology-based frameworks for IoT sensors and web services, designing wheelchair control systems using image processing, and analyzing superconductor properties via SEM image statistics. He has supervised over a dozen academic projects and one Master’s thesis on facial movement tracking using image processing. Active in academic administration, he coordinated Erasmus and Farabi programs and led departmental initiatives as Department Head. His refereeing roles include peer review for journals like Turkish Journal of Electrical Engineering and conferences such as ICECENG. He has authored/co-authored two books on cybersecurity and computer engineering, and contributed to international projects like the Sayısal Kontrol Sistemleri software development (2006–2010). Recent work emphasizes IoT device monitoring, blockchain-inspired data structures, and machine learning for automotive efficiency analysis. His teaching spans operating systems, software engineering, and agile development, reflecting his blend of theoretical and applied expertise.

Zoran Ivanovskiمشاهده پروفایل

استاد

• Image Processing
• Speech Recognition
• Medical Imaging
• +۳ مورد دیگر

Professor Zoran Ivanovski is a Full Professor and Head of the Institute of Electronics at the Faculty of Electrical Engineering and Information Technologies, University Saints Cyril and Methodius in Skopje, North Macedonia. He has held this position since 2016, advancing from Assistant Professor (2006–2011) to Associate Professor (2011–2016). His academic journey includes a Ph.D. in Electronics (2006), M.Sc. in Electronics (2000), and B.Sc. in IT and Automation (1990), all from the same university. His research focuses on image processing , speech recognition , medical imaging , and machine learning applications . Notable projects include real-time traffic analysis systems, automated media transcription, and quality control for medical imaging. He leads initiatives such as the Road Tax Payment Control System (funded by EBRD) and systems for object recognition using LIDAR and RGB-D data. Recent publications span hybrid CNN-DSP algorithms, real-time vehicle detection, and medical imaging advancements. His work emphasizes practical applications in healthcare, transportation, and assistive technologies.

• Agricultural Robotics
• Computer Vision
• Machine Learning
• +۴ مورد دیگر

Gert Kootstra is an Associate Professor in Agricultural Biosystems Engineering at Wageningen University & Research. His research focuses on robotics, computer vision, and machine learning applied to agricultural challenges, including plant phenotyping, UAV path planning, and automated harvesting systems. He leads projects involving 3D plant reconstruction, multi-object tracking in greenhouses, and deep learning for agricultural automation. His work bridges theoretical advancements with practical applications in precision agriculture and autonomous agricultural systems. Education: Not explicitly stated in the text, but his academic rank implies advanced qualifications in agricultural engineering or robotics. Research Interests: Robotics, computer vision, deep learning, UAV-based monitoring, plant phenotyping, and autonomous systems for agriculture. His projects often involve collaboration with industry and other academic institutions to solve real-world agricultural challenges. Recent Trends in Articles: Recent publications emphasize 3D plant segmentation, UAV navigation, and machine learning for object tracking in complex environments. He explores adaptive path planning for drones, automated harvesting techniques using learning from demonstration, and frameworks for uncertainty-aware object assessment in uncontrolled settings. Advising & Grants: Supervises multiple PhD candidates (e.g., Yuan J., Cakaj H., Versmissen T.) in projects funded by grants related to plant phenotyping, UAV applications, and robotics. Collaborates on initiatives like the PicknPack project for automated food processing. Labs & Teams: Involved in robotics and agricultural technology groups at Wageningen, focusing on developing tools for precision agriculture and sustainable farming practices.

• Pattern Analysis
• Machine Learning
• Data Mining
• +۸ مورد دیگر

David Stirling is an Honorary Fellow in the School of Electrical, Computer and Telecommunications Engineering at the University of Wollongong. He previously served as an Associate Professor in the same school from 2017 to 2021. His research focuses on Pattern Analysis, Machine Learning, Data Mining, and their applications in healthcare, transportation safety, and industrial processes. Key areas include radiomics for cancer survival prediction, driver fatigue detection through body posture analysis, and frailty assessment in older adults using inertial sensors. Stirling has supervised over 19 higher-degree research students, with topics ranging from medical image analysis to autonomous control systems. He has secured multiple grants, including projects on ergonomic design for vehicle seats and intelligent sensing technologies. Notable collaborations involve the Centre for Intelligent Mechatronics Research and industry partners like ABB and NSW Government. His work spans interdisciplinary applications such as landslide susceptibility modeling, power grid resilience analysis, and robotic control systems. Stirling actively contributes to advancing technologies in healthcare monitoring, autonomous systems, and data-driven decision support in oncology.

Bhuvendhraa Rudrusamyمشاهده پروفایل

استادیار

• Artificial Intelligence
• Computer Vision
• IoT
• +۷ مورد دیگر

Bhuvendhraa Rudrusamy is an Assistant Professor at the School of Engineering & Physical Sciences, Heriot-Watt University. His research focuses on interdisciplinary areas including Artificial Intelligence, Computer Vision, IoT, Robotics, and Disease Modeling. He actively supervises PhD students in topics such as 3D Image Registration and Smart Fleet Management. His work contributes to UN Sustainable Development Goals related to Industry, Innovation, and Infrastructure (Goal 9), and Good Health and Well-being (Goal 3). Notable research includes data-driven approaches to epidemiological modeling and IoT-based systems for vehicle safety. Recent publications highlight contributions to Bayesian inference for differential equations, multi-robot coordination frameworks, and distracted driver detection using AI. His research emphasizes practical applications in smart systems, autonomous robotics, and public health strategies. Bhuvendhraa collaborates internationally and engages in academic outreach, including workshops on energy storage and global challenges in engineering education.

John McPheeمشاهده پروفایل

استاد

• Biomechanical Engineering
• Robotics
• Control Systems
• +۷ مورد دیگر

John McPhee is a Professor in the Department of Systems Design Engineering at the University of Waterloo, with a cross-appointment in other academic groups. His research focuses on biomechanical systems, robotics, control systems, and musculoskeletal modeling with applications in wearable devices, surgical simulation, and sports biomechanics. He leads the Motion Research Group, developing advanced technologies for exoskeletons, prostheses, and human motion analysis. Key research themes include optimizing implant positioning for joint replacements, energy-efficient exoskeleton design, and predictive multibody dynamics modeling. His work integrates machine learning with physics-based simulations for applications in healthcare, transportation, and sports engineering. Recent studies emphasize environment-aware control systems for wearable robots and data-driven approaches for muscle-torque estimation using sEMG signals. McPhee collaborates on interdisciplinary projects involving robotics, biomechanics, and computational modeling. His research outputs highlight advancements in exoskeleton safety standards, automated anatomical landmark detection, and optimal control strategies for autonomous systems. The work demonstrates a strong focus on real-world applications in rehabilitation, surgical planning, and performance enhancement.

Paraskevi Zachariaمشاهده پروفایل

استادیار

• Production Planning and Control
• Robotics
• Automation Systems
• +۳ مورد دیگر

Paraskevi Zacharia is an Assistant Professor at the Department of Industrial Design and Production Engineering, University of West Attica. She holds a Dipl.-Ing. in Mechanical Engineering & Aeronautics from the University of Patras (2002), followed by two Ph.D.s: one in Mechanical Engineering & Aeronautics (2009) and another in Business Administration (2016). Her research focuses on Production Planning and Control, integrating Robotics, Automation Systems, and Artificial Intelligence to optimize multi-criteria manufacturing processes involving robots and human workers. Education: Dipl.-Ing. in Mechanical Engineering & Aeronautics, University of Patras, 2002 Ph.D., Mechanical Engineering & Aeronautics, University of Patras, 2009 Ph.D., Business Administration, University of Patras, 2016 Research Interests: Development of intelligent control strategies for industrial robots Robotic task scheduling and motion planning in cluttered environments Optimization of production planning using heuristic algorithms Autonomous vehicle systems for industrial and city logistics Publications & Trends: Her work spans fuzzy logic applications, AI-driven predictive models, and multi-robot coordination. Recent studies emphasize optimizing path planning, energy efficiency, and human-robot collaboration in manufacturing. Awards: No scientific awards explicitly mentioned in the text. Grants & Projects: Involved in European and National R&D projects, with contributions to robotics, logistics, and smart infrastructure. Serves as a reviewer for 14 journals including International Journal of Robotics and Automation. Labs & Teams: Engaged in research laboratories focusing on robotics, automation, and intelligent systems, though specific lab names are not detailed in the text.

• Data Science
• Machine Learning
• Machine Vision
• +۸ مورد دیگر

Roger G Nyberg is a Senior Lecturer at Dalarna University's School of Information and Engineering, Department of Information Science. He holds a PhD from Edinburgh Napier University (2016) and teaches courses in artificial intelligence, data science, software engineering, and project management. As head of the Informatics main field of studies, he oversees programs in Systems Science, Graphic Design and Web Development, and Digital Services. His research focuses on Data Science, Machine Learning, Machine Vision, and Monitoring, with applications in transportation, healthcare, and e-commerce. Key areas include automating decision-making processes, analyzing road conditions using acoustic and visual data, and studying hygrothermal transfer in building materials. Recent publications highlight work on gravel road condition evaluation using multimodal deep learning, CO2 emissions in parking systems, and exercise interventions for musculoskeletal pain. Nyberg supervises undergraduate and advanced theses and actively contributes to academic boards and committees at Dalarna University.

Jens Ekengrenمشاهده پروفایل

مدرس ارشد

• Mechanical Engineering
• Materials Engineering
• Additive Manufacturing
• +۳ مورد دیگر

Jens Ekengren is a Senior Lecturer in Mechanical Engineering at Örebro University since 2013, affiliated with the School of Science and Technology and Department of Natural Sciences and Technology. His research focuses on materials engineering, additive manufacturing, and statistical evaluation of defects in steels. He teaches courses in mechanics, materials engineering, and computational methods like FEA/CFD. Education includes a Doctoral Dissertation (2011) on extreme value analysis of steel defects and a Licentiate Thesis (2008) on inclusion content in steels. Key research projects include ATOAM (Additive Manufacturing tooling) and NASCA (agricultural systems). Research interests span statistical defect evaluation (rooted in his PhD work), electrical agricultural vehicles, and additive manufacturing applications in tooling and structural design. Recent publications emphasize 3D printing process optimization, tool cooling design via AM, and material property analysis using computed tomography. No scientific awards explicitly stated. Advising and grants details not provided in text. Active in the Mechanics and Materials research group. Current projects involve data-driven engineering design and agricultural automation.

• Structural Dynamics
• Railway Engineering
• Structural Health Monitoring
• +۷ مورد دیگر

Anders Rønnquist is a Professor and Head of the Department of Structural Engineering at NTNU's Faculty of Engineering. His research focuses on structural dynamics, railway infrastructure, and timber structures, with emphasis on reliability, safety, and innovative monitoring techniques. Collaborations include KTH Stockholm, University of Porto, and industry partners like Elektromotus and Vilnius-based entities. Research Interests Dynamic behavior of railway catenary systems and bridges Structural health monitoring using advanced sensors and machine learning Timber frame dynamics and connection stiffness modeling Wind-structure interaction in long-span bridges Conceptual form-finding in architectural engineering Recent Research Trends Recent work emphasizes data-driven approaches: Kalman filters for crosswind load estimation, deep learning for structural defect detection, and surrogate models for pantograph-catenary systems. Studies also address long-term monitoring of timber buildings and fatigue reliability of railway bridges under evolving traffic conditions. Education & Teaching Coordinates the Teknostart Master's program in Civil & Environmental Engineering. Teaches advanced courses in structural dynamics, steel structures, and railway catenary systems at NTNU. Active in interdisciplinary education bridging structural engineering and architecture. Research Groups Structural Dynamics Group Conceptual Structural Design Group

Andrzej Kordeckiمشاهده پروفایل

استادیار

• Object classification using CNNs
• Autonomous robot navigation
• Image correction methods
• +۳ مورد دیگر

Andrzej Kordecki, Ph.D., is an Assistant Professor at the Warsaw University of Technology's Faculty of Power and Aeronautical Engineering, Department of Theory of Machines and Robots. His research focuses on computer vision applications for robotics, including object classification with convolutional neural networks, autonomous navigation systems using LIDAR and camera data, and advanced image correction techniques. He also specializes in color management systems and calibration of imaging devices. Teaching responsibilities include courses on neural networks, digital image processing, and sensors in robotics. His work has been published in journals like Journal of Intelligent & Robotic Systems and Signal, Image and Video Processing , with conference contributions at venues such as the International Conference on Machine Vision (ICMV). Research highlights include development of the OffRoadSynth dataset for autonomous ground vehicle navigation and pioneering work on vignetting correction in camera systems. His technical expertise spans both theoretical and applied aspects of computer vision and robotics engineering.

• GIS
• Disaster Management
• Geomatics Engineering
• +۳ مورد دیگر

Muhammed Yahya Bıyık is a Researcher in the Department of Geomatics Engineering at Istanbul Technical University. His academic journey includes a Bachelor's (2016-2021), Master's (2021-2024), and ongoing Doctorate (since 2024) in Geomatics Engineering. His research focuses on applying geographic information systems (GIS) in disaster management and leveraging deep learning techniques for geospatial applications. Notable works include studies on landfill site selection post-earthquake and vehicle detection using orthophotos. He is affiliated with the Civil Engineering faculty and actively contributes to advancing geomatics technologies.

Zifan Linمشاهده پروفایل

مدرس

• Image Enhancement
• Power Electronics
• Inverter Technology
• +۳ مورد دیگر

Zifan Lin is a Lecturer and PhD student in the Multi-Discipline Doctor of Philosophy program at the School of Engineering, University of Western Australia. His research focuses on power electronics, underwater imaging, and control systems, with notable contributions to inverter technology, DC microgrid systems, and machine learning applications in vision systems. He actively collaborates on projects spanning Australia and other regions, addressing challenges in renewable energy integration and advanced image processing. His academic background includes multi-disciplinary training in engineering, complementing his teaching duties. Research interests emphasize practical solutions for energy systems (e.g., DC-DC converters, NPC inverters) and underwater image enhancement networks like TANet and ReX-Net. Recent work explores semantic feature refinement for mask detection and robust control schemes for electric motors using reinforcement learning. Publications highlight innovations in space vector modulation strategies, finite-set model predictive control, and agricultural drying technologies. While no specific awards are listed, his prolific output in top journals like IEEE Transactions and LWT-FOOD SCIENCE AND TECHNOLOGY reflects academic recognition. His advising and grant activities remain unspecified in available data.