جست‌وجوی استاد و پژوهشگر

Imran Ahmedمشاهده پروفایل

مدرس ارشد

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +۹ مورد دیگر

Dr. Imran Ahmed serves as a Senior Lecturer in Artificial Intelligence at Anglia Ruskin University's Faculty of Science and Engineering, School of Computing and Information Science. With over 100 research publications exceeding 250 JCR impact factor and an h-index greater than 30, he represents a distinguished academic in computer science and engineering fields. Dr. Ahmed's research spans multiple domains of artificial intelligence, with particular expertise in machine learning, deep learning, computer vision, and data science. His work focuses on medical imaging applications including brain tumor detection, Covid-19 detection, pulmonary nodule classification, and liver lesion detection. He also pioneers research in surveillance systems, IoT-enabled environments, anomaly detection, and AI applications for sustainability in environmental monitoring and precision farming. His recent publications demonstrate a strong trend toward practical AI applications in healthcare, environmental sustainability, and intelligent transportation systems. The research shows increasing emphasis on explainable AI, edge computing implementations, and interdisciplinary approaches that bridge computer science with medical, environmental, and industrial applications. His work consistently addresses real-world challenges with innovative technical solutions. World's top 2% scientists by Stanford University (2021, 2022) Double Gold Medallist Certificate of merit for brain MRI analysis for tumor detection Numerous awards for teaching, research, and administrative excellence Dr. Ahmed supervises research across multiple domains including medical imaging, healthcare informatics, surveillance systems, environmental monitoring, agricultural technology, recommender systems, anomaly detection, cyber security, public health, urban planning, smart cities, augmented reality, and human-computer interaction. His research projects include Human Surveillance and Activity Recognition, Data Analytics during Covid-19, Sustainable Healthcare applications, Deep Learning in Medical Imaging, and Sustainable Environmental Control frameworks. As Principal Investigator, he has led multiple funded projects integrating IoT and AI technologies for practical applications. He is actively involved in organizing technical sessions and workshops for IEEE conferences, particularly focusing on cybersecurity issues of IoT in Ambient Intelligence environments, connected intelligence for IoT applications, and real-time data processing in industrial contexts. His professional memberships include Fellow of the Higher Education Academy, Senior Member of IEEE, Member of ACM Computer Society, and Senior Member of the Institute of Research Engineers and Doctors.

• Empirical Software Engineering
• Requirements Engineering
• Applied Natural Language Processing
• +۷ مورد دیگر

Dr. Chetan Arora is a Senior Lecturer in Software Engineering at Deakin University's School of Information Technology, part of the Faculty of Science Engineering and Built Environment. He holds a PhD from the University of Luxembourg where he received the best PhD thesis award in the ICT domain. His research focuses on applied Artificial Intelligence in Software Engineering, with particular emphasis on Empirical Software Engineering, Requirements Engineering, and Applied Natural Language Processing. PhD in Computer Science from University of Luxembourg Masters in Software Engineering from Technische Universitat Kaiserslautern (Germany) Bachelors in Engineering (CS) from Thapar University (India) Arora's research interests center on the intersection of AI and Software Engineering, particularly how machine learning and natural language processing can enhance software development processes. His work explores requirements engineering, test automation, software trustworthiness, and human-centric software development. He investigates how large language models can be effectively deployed for tasks like test case generation, requirements analysis, and traceability. His recent publications reveal a strong focus on practical applications of AI in software engineering, with numerous studies examining the real-world implementation challenges and benefits. His publication record shows significant activity in top software engineering venues, with a notable emphasis on AI applications in software engineering processes. His recent work demonstrates expertise in retrieval-augmented generation systems, requirements-driven testing, and human-centric software development approaches. The publications collectively highlight his focus on bridging theoretical AI advancements with practical software engineering challenges. Best Ph.D. thesis award in the ICT domain at University of Luxembourg Arora actively supervises doctoral students working on cutting-edge topics including satellite communication systems, extended reality applications, and human-centered AI requirements engineering. His industry collaborations include work with Department of Defence on projects like Contextually Situated Anomaly Detection and Planning and Optimisation of Resources in Defence Satellite Communication Systems. He previously worked at SES Satellites on applied AI for IoT and Satcom, and as an FNR-PPP research fellow at the University of Luxembourg in software quality assurance. His laboratory work focuses on developing practical AI solutions for software engineering challenges, particularly in requirements engineering and test automation. Current projects involve multi-orbit satellite constellation optimization, dynamic radio resource management, and extended reality enabled human-centric requirements engineering.

• Human-Robot Interaction
• Virtual Reality (VR)
• Industry 5.0
• +۵ مورد دیگر

Federica Nenna is an Assistant Professor at the University of Padua, specializing in human-centered technologies within industrial settings. Her research focuses on human-robot collaboration, virtual/augmented reality applications in Industry 5.0, and neurophysiological aspects of human-machine interactions. She investigates how age, cognitive load, and psychological factors influence workers' performance in advanced manufacturing environments. Her work emphasizes ergonomics and safety in digital innovation, particularly through the use of eye-tracking, cardiac monitoring, and entropy analysis to assess user performance and workload. Key themes include trust dynamics in collaborative robotics, teleoperation systems, and the design of inclusive workstations for senior workers. Nenna’s research bridges neurophysiology, engineering, and occupational health to create safer, more efficient industrial environments. Publications highlight trends in VR/XR-based digital twins, human-centric risk management in digital transformation, and the physiological correlates of learning in robotic task environments. She advocates for a human-centered approach to Industry 5.0, addressing both technological and psychological barriers to adoption. Current projects explore cross-age usability of teleoperation interfaces and the integration of biometric feedback for real-time safety monitoring. Notably, she developed the SAFE GYMS IoT system for workplace safety and contributed to the SAFE TALK mobile application for mental health support during isolation. These innovations reflect her commitment to applying cutting-edge technologies to improve both productivity and well-being in rapidly evolving workspaces.

Nicola Riekeمشاهده پروفایل

پژوهشگر

• Medical Imaging
• Computer-Aided Surgery
• Surgical Robotics
• +۳ مورد دیگر

Dr. Nicola Rieke is an affiliated researcher at the Chair for Computer Aided Medical Procedures & Augmented Reality at the Technical University of Munich (TUM). Currently, she works at NVIDIA's Healthcare Team EMEA. Her research focuses on surgical tool tracking, real-time medical imaging, and computer-aided interventions with applications in ophthalmology and retinal microsurgery. Awarded the MICCAI 2015 Young Scientist Award for her work on surgical tool tracking, she has contributed to advancements in intraoperative OCT positioning and instrument localization. Her publications span conferences like MICCAI, IPCAI, and journals such as Medical Image Analysis. Professional service includes organizing roles in MICCAI workshops on domain adaptation, collaborative learning, and global healthcare AI. Her research integrates computer vision techniques with medical robotics to improve surgical precision and workflow. Key projects include real-time tracking algorithms for articulated instruments and robust pose estimation under partial occlusions.

• Digital Signal Processing
• Image Processing
• Multimedia Communications
• +۳ مورد دیگر

Marco Carli is a Full Professor at the Department of Industrial, Electronic, and Mechanical Engineering, Roma Tre University, Italy. He holds a Laurea in Telecommunication Engineering from Università degli Studi di Roma 'La Sapienza' and a Ph.D. from Tampere University of Technology. His research focuses on digital signal and image processing applied to multimedia communications, including digital watermarking, multimedia quality evaluation, and information security. He has led projects such as EHEM (medieval architecture modeling), ISEEYOO (AI-based anomaly detection), and INSECTT (secure IoT-AI systems). Carli serves as an Associate Editor for IEEE Transactions on Image Processing and Area Editor for Signal Processing: Image Communication. He is an IEEE Senior Member. His work spans over 55 journal publications and numerous conferences, addressing topics like immersive VR applications, cybersecurity, and perceptual quality metrics. Education: Laurea in Telecommunication Engineering, Università di Roma 'La Sapienza', 1990s Ph.D. in Telecommunication Engineering, Tampere University of Technology, Finland Projects: EHEM: Digital modeling of medieval architecture and art ISEEYOO: Anomaly detection in Cyber-Physical Systems INSECTT: Secure IoT systems with AI Research Interests: Signal/image processing for multimedia Quality evaluation and watermarking Cybersecurity and IoT applications Awards: None explicitly listed Grants/Advising: Multiple EU-funded projects (e.g., ImmerSAFE, RESISTO, ATENA) and collaborations with industry partners like Thales Alenia Space.

Ingmar Ickerottمشاهده پروفایل

استاد

• Logistics Management
• Digitalization in Supply Chains
• Smart Glasses Applications
• +۳ مورد دیگر

Prof. Dr. Ingmar Ickerott is a faculty member at Osnabrück University of Applied Sciences, affiliated with the School of Management, Kultur und Technik (MKT, Campus Lingen) under the University management department. His academic career spans over two decades, focusing on logistics management, digitalization in supply chains, and smart technology applications like Smart Glasses and Augmented Reality . Academic Background : Diplom-Kaufmann in Business Administration (2001), Ph.D. in Economics (2006). Professional Roles : Senior Project Manager at arvato (2008–2010), Professor since 2010, Dean of MKT since 2019, Vice President for Digitalization since 2019. His research emphasizes logistics innovation , Lean Management , and digital solutions in rural healthcare . Key projects include Land.Digital (2019–2022) and LEAN 4.0 (Erasmus+, 2019–2021). Publications since 2004 cover agent-based simulation , Smart Device economics , and AR in logistics . He actively lectures on topics like Logistics 4.0 and Digital Onboarding . Projects & Grants : Land.Digital : €165,000+ (Erasmus+), 2019–2021. Dorfgemeinschaft 2.0 : €1.46M (BMBF), 2015–2021. Glasshouse : €208,557 (BMBF), 2015–2019.

Al Bovikمشاهده پروفایل

استاد مهمان

• Digital Video
• Visual Neuroscience
• Deep Learning
• +۳ مورد دیگر

Al Bovik is a Visiting Professor at the University of Texas at Austin's Department of Electrical and Computer Engineering, part of the College of Engineering. His research focuses on digital video, visual neuroscience, and deep learning, with an emphasis on developing perceptual theories for high-quality streaming video and virtual/augmented reality systems. He has pioneered advancements in video quality assessment, compression, and AI-generated media evaluation. He has received prestigious awards including the IEEE Edison Medal, Primetime Emmy, and membership in multiple national academies. Bovik co-founded the IEEE Transactions on Image Processing and established the IEEE International Conference on Image Processing in 1994, which he chaired. His influential books include The Essential Guides to Image and Video Processing . Key Research Contributions: HDR/SDR video quality metrics, perceptual artifact detection, and AI-driven quality assessment frameworks. Labs/Teams: Leadership in IEEE initiatives and collaborations in media quality and signal processing. His work bridges theoretical research with practical applications in video streaming, medical diagnostics, and user-generated content analysis.

• Virtual Reality
• Augmented Reality
• Mixed Reality
• +۷ مورد دیگر

Pascal Knierim is a researcher in the Department of Computer Science at Ludwig Maximilian University of Munich, Germany. He completed his PhD at the same institution in 2020 with a dissertation titled "Enhancing interaction in mixed reality: the impact of modalities and interaction techniques on the user experience in augmented and virtual reality." His research focuses on human-computer interaction, particularly in virtual and augmented reality environments, with an ORCID identifier 0000-0001-9578-9953. Knierim's research interests span virtual reality, augmented reality, mixed reality, ubiquitous computing, and extended reality systems. He has made significant contributions to understanding user interaction in immersive environments, privacy considerations in VR/AR, biometric identification using thermal imaging, and universal interaction frameworks. His work often combines technical innovation with user-centered design principles, resulting in numerous publications at top-tier venues including CHI, MUM, UbiComp, and IEEE Pervasive Computing. Recent work has explored content blocking in extended reality, social anxiety in VR proxemics, user awareness of privacy permissions, and framework development for ubiquitous research preservation. Knierim has collaborated extensively with researchers such as Thomas Kosch, Florian Alt, and Albrecht Schmidt, forming a productive research group within LMU Munich's computer science department. He has also contributed to the academic community through editorial roles for major conferences including Mensch und Computer 2023 and the 22nd International Conference on Mobile and Ubiquitous Multimedia (MUM 2023), demonstrating leadership within his research community. His research demonstrates a strong commitment to both theoretical advancement and practical applications of immersive technologies, with particular attention to user experience, privacy, and accessibility considerations.

Francesco Ragusaمشاهده پروفایل

پژوهشگر ارشد

• Computer Vision
• Pattern Recognition
• Machine Learning
• +۵ مورد دیگر

Francesco Ragusa is a Research Fellow at the University of Catania, Italy, holding an Industrial Doctorate in Computer Science (2021). He spent part of his PhD at the University of Hertfordshire, UK. His work focuses on First Person (Egocentric) Vision, including Human-Object Interaction, Industrial Applications, and Augmented Reality. He co-founded NEXT VISION s.r.l., an academic spin-off from the University of Catania since 2021. Key projects include the MECCANO dataset for industrial human-object interactions and the EGO-EXO4D initiative analyzing skilled human activity from multi-perspective views. Research interests span Computer Vision, Pattern Recognition, and Machine Learning. He contributed to seminal datasets like MECCANO and ENIGMA-51, advancing understanding of human behavior in industrial settings. His work emphasizes practical applications, such as wearable assistive systems and visual navigation solutions. Ragusa has delivered tutorials at major conferences (e.g., ICIAP, VISIGRAPP) on First Person Vision’s history, challenges, and trends. He actively promotes industrial collaborations and has secured grants including PNRR MUR (Code E63C22001940006) and EU funding under Next Generation EU. His teaching and professional activities include organizing workshops on egocentric vision for AI-driven assistants and industrial safety systems. Current research directions involve multimodal synthetic data utilization, gaze-based interaction analysis, and cross-modal fusion for human-robot collaboration.

Massimo Orazio Spataمشاهده پروفایل

پژوهشگر ارشد

• Deep Learning
• Biomedical Engineering
• Computer Science
• +۳ مورد دیگر

Massimo Orazio Spata is a Research Fellow in Computer Science at the University of Catania's Department of Mathematics and Computer Sciences, specializing in deep learning applications for biomedical, audio, and biometric systems. He has held roles at STMicroelectronics since 1999, focusing on system integration, image processing, and biomedical device R&D. He teaches courses such as Mobile Programming and Computer Architecture at secondary schools and has advised numerous students on grid computing and middleware projects. Education: PhD in Computer Science (University of Catania, 2008), MSc in Computer Science (University of Catania, 2013), and a teaching certification in Computer Science (University of Catania, 1998). Research interests include deep learning algorithms, biomedical device development, grid scheduling, and cybersecurity. He has authored patents on lab-on-chip systems, bio-computer analysis, and scheduling methods, and his work has been recognized with STMicroelectronics Innovation Awards (2016–2014) and a Cisco CCNA certification. Key collaborations include projects with Google (Mediapipe Objectron for robotics), Huawei (video deblurring), and involvement in the PNRR Horizon HiCONNECTS project (2024–present). He serves on conference committees (e.g., ICAETA 2023) and has developed e-learning systems and CAD tools for STMicroelectronics.

• Computer Graphics
• Virtual and Augmented Reality
• Facial Expression Analysis
• +۴ مورد دیگر

Joe Geigel is a Professor in the Department of Computer Science at Rochester Institute of Technology's Golisano College of Computing and Information Sciences. He holds a DSc in Computer Science from George Washington University, an MS in Computer Science from Stevens Institute of Technology, and a BS in Mathematics from Manhattan College. His career includes industry positions at Eastman Kodak, Bell Laboratories, and RCA Solid State before transitioning to academia. Geigel's research explores the intersection of computer graphics and performing arts, with expertise in: Virtual and augmented reality systems Facial expression analysis and motion capture Interactive theatre and dance technologies Human-computer interaction for creative applications Interdisciplinary education methods His publications demonstrate consistent innovation in virtual performance technologies, with recent work focusing on mixed reality theatre, museum interpretation systems, and educational applications of immersive technologies. He has directed over 15 technology-enhanced productions including Singring and the Glass Guitar and Farewell to Dawn . As co-director of the CS Graphics and Applied Perception Lab, Geigel leads the XRLive team developing extended reality solutions for live performances. He teaches graduate courses in computer graphics, animation algorithms, and virtual reality applications.

Jennifer C. Brittonمشاهده پروفایل

دانشیار

• Anxiety Disorders
• Neuroimaging
• Developmental Neuroscience
• +۳ مورد دیگر

Jennifer C. Britton is an Associate Professor in the Department of Psychology at the University of Miami's College of Arts and Sciences. She leads the Bridging Research on Anxiety, Innovations, and Neuroscience (BRAIN) Group, dedicated to understanding anxiety disorders through interdisciplinary approaches combining behavioral science, psychophysiology, and neuroimaging. Her research focuses on the neural mechanisms underlying anxiety across the lifespan, particularly studying threat learning, attention biases, and interoception. She employs advanced methods like fMRI, eye-tracking, and computational modeling to explore how fear conditioning and extinction processes contribute to clinical disorders. Key themes include developmental trajectories of anxiety, treatment development (e.g., attention bias modification), and translational neuroscience applications. Expertise: Anxiety Disorders | Neuroimaging | Developmental Neuroscience Methodologies: fMRI | EEG | Augmented Reality Interventions Current work examines social reward-threat conflict processing, cardiac interoceptive awareness in HIV populations, and validating novel assessment tools like the Attention Bias Questionnaire (ABQ). Her lab also investigates neural correlates of therapy outcomes in pediatric anxiety. Notable contributions include demonstrating amygdala-cortical connectivity changes during attention bias modification and pioneering child-friendly fear conditioning paradigms. She advocates integrating neurocognitive training into clinical interventions for anxiety and obsessive-compulsive disorders. Grants and collaborations focus on translational research bridging basic science and clinical care. Ongoing projects explore neurobiological markers of treatment response and developing personalized interventions using gene-environment interaction insights.

• Image Processing
• Artificial Intelligence
• Machine Learning
• +۷ مورد دیگر

Dr. Taha Hussein Rassem is a Senior Lecturer in Computing at the School of Computer Science and Informatics, De Montfort University, UK, within the Faculty of Computing, Engineering and Media. He holds a Ph.D. in Computer Engineering (Imaging) from Universiti Sains Malaysia, an M.Tech in Computer Science from the University of Hyderabad, India, and a B.Sc. in Computer Engineering from the University of Technology, Baghdad, Iraq. He previously served as a Senior Lecturer at Universiti Malaysia Pahang (UMP) and as a Research Fellow at Bournemouth University, where he continues as a Visiting Fellow until May 2026. Ph.D. in Computer Engineering (Imaging), Universiti Sains Malaysia, 2014 M.Tech in Computer Science, University of Hyderabad, India, 2007 B.Sc. in Computer Engineering, University of Technology, Baghdad, Iraq, 2001 Dr. Rassem’s research focuses on Image Processing, Artificial Intelligence, Machine Learning, Deep Learning, Texture Classification, and Digital Watermarking , with applications in medical diagnostics such as early detection of Alzheimer’s disease. His teaching expertise includes Programming, Multimedia, Virtual and Augmented Reality, Web and Mobile Application Development, and Human-Computer Interaction. He is affiliated with the Institute of Digital Research, Communications and Responsible Innovation and the Institute of Artificial Intelligence at DMU. His research projects include Early detection and diagnosis of Alzheimer’s diseases using hybrid deep and machine learning , Modern Fuzzy Min-Max Neural Network for Pattern Classification , and New Secure Hybrid SVD-Based Image Watermarking Scheme . He has led externally funded grants, including an international grant from the University of Hail, Saudi Arabia, and a Ministry of Education grant in Malaysia. Dr. Rassem has received numerous awards for research, grants, and supervision, including multiple ANUGERAH CENDEKIA BITARA awards, Top 10 Outstanding Grant and Publication Awards at UMP in 2020, and recognition as one of the top supervisors for final-year projects. He is also a recipient of the SANGGAR SANJUNG HALL OF FAME AWARD from Universiti Sains Malaysia. Senior Member, IEEE Senior Member, International Association of Engineers Professional Member, Institution of Engineering and Technology (IET) Professional Member, British Computer Society (BCS) Professional Technologist, Malaysian Board of Technology (MBOT) until 2023 He has successfully supervised Ph.D. students, with several receiving publication awards under his guidance. His research has been supported by competitive grants, and he continues to contribute significantly to AI and image processing research. He is actively involved in research groups focusing on AI and responsible innovation.

Brett Stevensمشاهده پروفایل

مدرس ارشد

• Virtual Reality
• Augmented Reality
• Computer Games Technology
• +۱۱ مورد دیگر

Brett Stevens is a Principal Lecturer and Research and Innovation Lead at the School of Film, Media and Creative Technologies, Faculty of Creative & Cultural Industries, University of Portsmouth. He also serves as Director of Postgraduate Taught Programmes and coordinates postgraduate research (PhD/MPhil) in Digital and Creative Technologies. He is actively involved in research, innovation, and leadership in XR and digital heritage. Research Interests: His work centers on Virtual Reality, Augmented Reality, Computer Games, User Interface and Experience Design, and immersive technologies for heritage institutions. He explores how physical and digital interactions enhance engagement in museums and libraries. Recent Research Trends: His latest publications focus on locomotion classification in VR, saliency detection using GANs, digital preservation of archaeological data, and the role of avatar fidelity in human-computer interaction. These reflect a strong interdisciplinary approach combining computer science, design, and cultural applications. Scientific Awards: IEEE Outstanding Leadership Award (2023) Advising and Grants: He has successfully supervised 20 PhD students in areas including VR, AR, Game Design, and Computer Vision. He leads multiple research projects such as Supporting Elephant and Rhino Conservation and Ecology , CT Research Sprint Projects , and Photorealistic Asset Creation , often in collaboration with institutions like the University of Nottingham and University of York. He is actively involved in funding-driven innovation in XR and heritage. Labs and Teams: He is affiliated with the Centre of Excellence for Heritage Innovation and the Centre for Creative and Immersive XR at the University of Portsmouth, contributing to strategic innovation in immersive content creation and digital preservation.

Matthew Rodgerمشاهده پروفایل

مدرس ارشد

• Perceptual-Motor Coordination
• Auditory-Motor Coordination
• Motor Skill Acquisition
• +۳ مورد دیگر

Matthew Rodger is a Senior Lecturer at the School of Psychology Intelligent Autonomous Manufacturing Systems, Queen's University Belfast. His research focuses on perceptual-motor coordination, auditory-motor synchronization, and applications of movement sonification in motor skill learning, particularly for individuals with visual impairments and Parkinson's disease. He has supervised nine PhD students, including current advisees Bonnie Smith and Michal Toth, and former students like James Stafford and Alannah Savage. Rodger is actively involved in interdisciplinary projects such as 'Improvising Futures' and 'Dance for Parkinson’s,' and contributes to UN Sustainable Development Goals related to health and well-being. His work has been recognized with the QUB Research Culture Seed Fund (2021). Research Interests: Auditory-motor coordination, movement sonification, Parkinson's disease rehabilitation, music performance skill acquisition, and embodied cognition. Recent projects include investigating sound-based interventions for gait improvement in Parkinson's patients and exploring aesthetic dimensions in musical interaction. Key Awards: QUB Research Culture Seed Fund (2021). Collaborations: Active in Northern Ireland's Parkinson's@NI network and collaborates with experts in psychology, neurology, and music technology.