جست‌وجوی استاد و پژوهشگر

• Neuromorphic Engineering
• Spiking Neural Networks
• CMOS Circuit Design
• +۳ مورد دیگر

Hugh Greatorex serves as a Researcher at the University of Groningen within the Faculty of Science and Engineering, affiliated with the Bio-inspired Circuits & Systems research group. His work centers on neuromorphic hardware design, specializing in spiking neural networks and event-based processing systems that prioritize energy efficiency and real-world applicability in robotics and embedded AI. His research spans critical areas in neuromorphic engineering: Neuromorphic Engineering Spiking Neural Networks CMOS Circuit Design Memristive Computing Event-based Vision and Audio Processing Symbolic Computation in Neural Hardware Greatorex integrates circuit design with neural algorithms to solve power efficiency challenges, frequently exploring beyond-CMOS technologies like memristors and multi-timescale neural dynamics for practical implementations. Analysis of his 14 recent publications (2022-2025) reveals a cohesive trajectory toward hybrid neuromorphic processors combining CMOS with emerging devices. Key contributions include the TEXEL and Fused-MemBrain architectures for beyond-CMOS integration, alongside advancements in event-based sensory processing and symbolic operations within spiking hardware. This work consistently bridges neural computation with symbolic AI paradigms while emphasizing scalability and robustness. No scientific awards were documented in available sources. Information regarding student advisement and research grants was not provided in the source materials. As a core member of Groningen's Bio-inspired Circuits & Systems group, Greatorex contributes to internationally collaborative projects focused on biologically inspired electronic systems for intelligent processing, with applications spanning edge AI and neural computation modeling.

Peter Kuchmentمشاهده پروفایل

استاد

• Partial Differential Equations
• Mathematical Physics
• Medical Imaging
• +۴ مورد دیگر

Peter Kuchment is a University Distinguished Professor in the Mathematics Department at Texas A&M University. His research focuses on Partial Differential Equations, Mathematical Physics, Medical Imaging, and Geometric Analysis. He holds prestigious fellowships from the AAAS, AMS, APS, and SIAM. Kuchment has advised numerous PhD and master's students, many of whom have gone on to academic and industry roles globally. His work spans theoretical advancements in inverse problems, quantum graphs, and tomographic imaging techniques. Education: Science Doctor (1983), PhD (1973), and MS (1971) in Mathematics from institutions in Ukraine and Russia. Professional Memberships: Extensive involvement in mathematical societies including AMS, SIAM, and IEEE. Key research interests include spectral theory of periodic operators, medical imaging modalities like thermoacoustic tomography, and applied mathematics in novel materials science. Kuchment has organized major international conferences and workshops on topics such as quantum graphs and hybrid imaging methods. Scientific Awards: Multiple recognitions for student advisement and research contributions. Active in academic service, he directs outreach programs like the Summer Mathematics Research Training (SMaRT) camp and contributes to departmental initiatives in mathematics education and outreach.

• Multi-target Tracking
• Bayesian Filtering
• Sensor Fusion
• +۳ مورد دیگر

Professor Daniel Clark is a member of the University of Southampton's academic staff, specializing in multi-target tracking, Bayesian methods, and sensor fusion. His research focuses on advancing algorithms for aerospace systems, robotics, and statistical inference. He supervises PhD students in electronic engineering and is affiliated with the Vision, Learning and Control Centre for Robotics. His work bridges theoretical foundations with practical applications in tracking systems and cybersecurity. Recent contributions include advancements in covariance intersection, adversarial risk formulations, and sensor data fusion techniques. Research Interests: His expertise spans multi-object tracking, stochastic guidance systems, and information-theoretic bounds. He explores applications in maritime surveillance, robotics navigation, and secure algorithm design. Advising & Grants: Currently supervising Chuanhang Qiu (PhD in Electronics). His research has been published in top-tier journals like IEEE Transactions on Aerospace and Electronic Systems. Labs & Teams: Active member of the Vision, Learning and Control Centre for Robotics, contributing to interdisciplinary projects in autonomous systems and data fusion.

Giovanna Masseiمشاهده پروفایل

استاد

• Non-lethal wildlife management
• Fertility control
• Wildlife ecology and behavior
• +۳ مورد دیگر

Giovanna Massei is a Professor and Europe Director of the Botstiber Institute for Wildlife Fertility Control, affiliated with the University of York's Department of Environment & Geography. Her research focuses on non-lethal wildlife management, particularly fertility control for invasive species, free-roaming dogs, and livestock. She has led over 30 grants totaling millions in funding, including projects on tick-borne disease control, grey squirrel fertility control, and wild boar population management. Education: PhD in Zoology (Aberdeen University, 1995), Specialisation in Wildlife Management (National Institute of Wildlife Management, 1988), MSc in Natural Sciences (University of Florence, 1985). Research Interests: Human-wildlife coexistence, non-lethal wildlife control methods, fertility control technologies, wildlife ecology, and invasive species management. Grants/Projects: One-Health approach to tick-borne disease control (UKRI-DEFRA, £1.25M, 2023-2026) Red Squirrel Recovery Network (National Heritage Lottery Fund, £158k, 2023-2030) Oral contraceptive trials for wild boar (Italian Ministry of Health, £250k, 2022-2025) Labs/Teams: Leads the Botstiber Institute for Wildlife Fertility Control and collaborates with global institutions on wildlife management initiatives.

• Biodiversity Monitoring
• Conservation Biology
• Ecology
• +۸ مورد دیگر

Dr. PJ Stephenson is a Research Fellow at the University of Lausanne , affiliated with the Department of Ecology and Evolution within the Faculty of Biology and Medicine . He serves as Chair of the IUCN Species Survival Commission Species Monitoring Specialist Group and collaborates with the Fumagalli Group to advance biodiversity monitoring science. Education: BSc in Zoology (University of London), PhD in Tenrec Ecology (University of Aberdeen) Current Roles: Senior Research Fellow (ETH Zürich), IUCN advisor His research focuses on understanding biodiversity monitoring challenges , addressing taxonomic and geographic data biases , developing conservation indicators , testing remote sensing and eDNA technologies , and analyzing conservation programme success factors . Recent projects include: Nature-Positive Biodiversity Credits (2024-2025): Methodological development for credit systems Data Flow Analysis (2021-2023): Cross-sector biodiversity data accessibility study Global Monitoring Tools (2023-2025): Guideline development for diverse stakeholders Scientific awards and honors: No specific awards mentioned in text He has supervised multiple UNIL Masters students on topics including protected area effectiveness , species monitoring methods , and data gaps in East African conservation . His work spans technological monitoring innovations , policy frameworks , and field research in Africa/Madagascar .

Ciaran Eisingمشاهده پروفایل

دانشیار

• Computer Vision
• Artificial Intelligence
• Machine Learning
• +۷ مورد دیگر

Ciaran Eising is an Associate Professor in the Department of Electronics & Computer Engineering at the University of Limerick. His research focuses on computer vision, machine learning, and their applications in intelligent transportation systems, particularly autonomous driving and driver assistance systems. He is a member of the Centre for Sustainable Digital (Re)Manufacturing, Data-Driven Computer Engineering Research Centre, and Lero – the SFI Research Centre for Software. Education: PhD from the National University of Ireland Galway (2010), BE (2003). External roles include Senior Expert at Valeo Vision Systems (2009–2020) and Adjunct Lecturer at NUI Galway (2016–present). His expertise spans automotive vision systems, embedded systems, and sensor fusion. Research Interests: Driver Assistance Systems, Autonomous Driving, Object Detection, Motion Segmentation, and Sensor Fusion. Over 94 publications since 2007, with recent work on BEV perception, multimodal fusion, and DDoS mitigation in healthcare IoT. Grants/Advising: Accepting PhD students; collaborations include industry partnerships and cross-disciplinary research. Labs/Teams: Active in Lero and other university research centers, contributing to UN SDGs via sustainable transportation innovations.

Erica Sotoمشاهده پروفایل

استادیار

• Broadcast Journalism
• Media Studies
• Social Journalism
• +۴ مورد دیگر

Erica Soto is an Assistant Professor of Journalism at St. Thomas Aquinas College (STAC), bringing over 15 years of experience as a bilingual multimedia journalist and producer. She specializes in fostering experiential learning, emphasizing cutting-edge technology and traditional tools to prepare students for broadcast media careers. Soto teaches courses such as Broadcast Journalism, Media Law & Ethics, and Video Production, ensuring students gain skills in scriptwriting, camera operation, and full production workflows. Education: B.A. in Broadcast Journalism from the University of Colorado Boulder; M.A. in Social Journalism from CUNY’s Graduate School of Journalism (inaugural class). Professional Experience: Freelance producer for StoryCorps (NPR), with credits including audio stories for Morning Edition. Previously worked on the Creative Arts Emmys (E!), Kids’ Choice Awards (Nickelodeon), and Model Latina (NuvoTV). Research & Commitment: Advocates for diversity in media and education, aligning with STAC’s focus on community and inclusion. Teaches the importance of covering multicultural perspectives, empowering students to shape the future of journalism. Awards: Imagen Award for the docuseries Puerto Rican Voices . Memberships: Freelancers Union, National Association of Hispanic Journalists. Teaching Philosophy: Prioritizes hands-on learning to bridge classroom theory with industry practices, ensuring students are prepared to innovate in evolving media landscapes. Finds fulfillment in mentoring students to become storytellers and media experts.

Andrea Albarelliمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۳ مورد دیگر

Andrea Albarelli is an Associate Professor at Ca' Foscari University of Venice, affiliated with the Department of Environmental Sciences, Informatics and Statistics. His research focuses on Artificial Intelligence, Machine Learning, and Computer Vision, with a particular emphasis on Explainable AI, Pattern Recognition, and Data Analytics applications. He has contributed to numerous peer-reviewed publications, including studies on hierarchical text classification, fruit ripeness analysis, and embedded vision systems. His teaching activities include courses on Data Analytics for Business and Society, emphasizing practical applications of AI and informatics. Albarelli's work spans theoretical frameworks and applied research, addressing challenges in both academic and industrial contexts. Research Interests: Machine Learning algorithms, computer vision techniques, and their applications in agriculture, edge computing, and multi-camera systems. Recent Contributions: Over 90 publications, including high-impact journals like Electronics and Expert Systems with Applications . His academic contributions reflect a balance between foundational research and real-world problem-solving, with notable projects on model explainability, quantization-aware neural networks, and calibration techniques for vision systems. Albarelli serves as a faculty member in both undergraduate and graduate programs, integrating cutting-edge research into curriculum design.

• Biomechanics
• Motor Control
• Mild Traumatic Brain Injury (mTBI)
• +۴ مورد دیگر

Gustavo Heidner is an Assistant Professor of Kinesiology at Montclair State University within the College for Community Health . His research focuses on biomechanics and motor control, particularly the diagnosis/treatment of mild traumatic brain injury (mTBI) and its effects on balance, motor control, and decision-making. He also explores virtual reality applications for motor learning paradigms and high-stress encounters like law enforcement responses. His teaching responsibilities include courses such as PEMJ 321 (Kinesiology) and PEMJ 324 (Basic Motor Learning). Educational Background: BSc in Exercise Science and Physical Education (Pontifical Catholic University of RS) MA in Exercise Science: Biomechanics (Indiana State University) PhD in Bioenergetics and Exercise Science: Biomechanics and Motor Control (East Carolina University) Research Interests: Combines biomechanical analysis with neurobehavioral studies to address real-world challenges such as mTBI rehabilitation and decision-making under stress (e.g., law enforcement scenarios). Recent work includes studies on visual-motor control during deadly force encounters and the neural correlates of fatigue vs. concussion. Key Contributions: Over 20 peer-reviewed publications in areas like gait adaptations, police officer motor response variability, and virtual reality-assisted motor training. Research emphasizes translational applications for public safety and clinical practice.

• Digital Technology for Learning
• AI in Sports Performance
• 360-Degree Vision Analysis
• +۳ مورد دیگر

Dr. Katherine (Kath) O'Brien is a Senior Lecturer at QUT's School of Exercise & Nutrition Sciences, specializing in sport pedagogy, technology-enhanced learning, and officiating development. She holds a PhD from the University of Queensland and has served as a National Coach, State Coaching Panel Chair, and High School Teacher. Affiliations: International Journal of Sport Coaching Editorial Board, QUT Leadership Team Research Focus: AI in sports officiating, female athlete learning, social-neuroscientific influences Her work bridges practical coaching with cutting-edge technology, including AI-driven video feedback and 360-degree camera systems. Recent awards include the QUT Researcher Symposium Oral Presentation Competition (2023) and AAUT Teaching Excellence Award (2022). She founded the Australian Sport Officiating Summit (ASOS) and QUT Women in Sport Leadership Conference. Currently supervising research on bone stress in athletes, referee conversational patterns, and primary school physical education perceptions.

Mehrdad Dianatiمشاهده پروفایل

استاد

• Connected and Autonomous Systems
• Autonomous Vehicles
• Artificial Intelligence
• +۴ مورد دیگر

Professor Mehrdad Dianati is a faculty member at Queen's University of Belfast in the School of Electronics, Electrical Engineering and Computer Science. His research focuses on Connected and Autonomous Systems, Autonomous Vehicles, Artificial Intelligence, Future Networks (5G/6G), and Future Transport Systems. He actively supervises PhD students in these areas and has collaborated with institutions like the University of Surrey and University of Waterloo. His work emphasizes cybersecurity in autonomous systems, cooperative perception for driving applications, and advanced communication protocols for vehicular networks. Key contributions include publications on anomaly detection in autonomous vehicles, motion planning using fluid dynamics, and simulation techniques for sensor data. Research Interests: Autonomous Vehicle Cybersecurity 3D Object Detection in Driving Scenarios Cooperative Perception and V2X Communication Deep Learning for Trajectory Prediction Recent Articles: Focus on cybersecurity, motion planning algorithms, and sensor simulation for autonomous systems Exploration of future networks (6G) and metaverse integration

Peyman Kabiriمشاهده پروفایل

مدرس ارشد

• Network Security
• Cybersecurity
• Intrusion Detection and Response
• +۶ مورد دیگر

Peyman Kabiri is a Senior Lecturer in Cyber Security at the De Montfort University School of Computer Science and Informatics , Faculty of Computing, Engineering and Media. His research spans interdisciplinary domains including Network and Cybersecurity (Intrusion Detection/Response) Remote Sensing and Acoustic Emission Analysis Many-Valued Logic and Robotics Sound Analysis and Music Information Retrieval Peyman's academic contributions focus on adaptive error compensation in mechanical systems and security frameworks for cyber-physical environments. His recent publications highlight innovations in Monocular SLAM algorithms for indoor navigation Wavelet packet transform for image processing Signal strength-based wireless intrusion detection Trust modeling in virtualized systems As an educator, he teaches Practical Host & Network Security (PG) Secure Coding (UG) Endpoint Security (UG) with extensive experience in microprocessor design, robotics, and network security modules. Professional memberships include BCS (2024) IEEE (1997-2002, 2012) ACM (2010-2013) SPIE (2005) ISMVIP (2010-2019) ISAV (2017)

Willi Menapaceمشاهده پروفایل

پژوهشگر

• Computer Vision
• Deep Learning
• 3D Reconstruction
• +۳ مورد دیگر

Willi Menapace is a Researcher at the University of Trento , affiliated with the Multimedia and Human Understanding Group (MHUG). His work focuses on the intersection of Computer Vision , Deep Learning , and 3D Reconstruction , with applications in Medical Imaging and Interactive Video Generation .

• Intelligent Transport Systems
• Transportation Engineering
• Urban Traffic Management
• +۳ مورد دیگر

Rajesh Krishnan is an Honorary Research Fellow at the Department of Civil and Environmental Engineering, Imperial College London. His work focuses on Intelligent Transport Systems (ITS), traffic data analysis, and urban traffic management. He holds a PhD from Imperial College London and a B.Tech from Indian Institute of Technology Madras. His research spans over 50 publications in areas like traffic sensor technology, real-time data analysis, and public transport optimization. Education: PhD in Civil Engineering, Imperial College London (2003-2008) B.Tech in Civil Engineering, Indian Institute of Technology Madras (1991-1995) Research Interests : Optimization of traffic signal systems for buses and autonomous vehicles Machine learning applications in traffic prediction and anomaly detection Public-private collaboration models for traffic information systems Data fusion techniques using GPS, Bluetooth, and camera sensors Recent work highlights include developing real-time congestion detection algorithms and frameworks for integrating autonomous vehicles into mixed traffic flows. His publications emphasize practical ITS solutions for urban mobility challenges. No student advisees or grants are explicitly listed in the provided materials.

Yu-Lin Weiمشاهده پروفایل

عضو هیئت علمی

• Audio Signal Processing
• Wireless Communication
• Indoor Positioning Systems
• +۴ مورد دیگر

Yu-Lin Wei is a Teaching Assistant Professor in the Department of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign (UIUC). He holds a Ph.D. from UIUC (2024), and M.S. and B.S. degrees in Computer Science and Information Engineering from National Taiwan University (2016 and 2014, respectively). His research focuses on audio signal processing, IoT systems, wireless/visible light communication, and indoor positioning. He has been honored with the ECE Rambus Fellowship (2020-2021) and was a Young Researcher at the Heidelberg Laureate Forum (2019). He teaches CS/ECE 438: Communication Networks and CS/ECE 434: Real-World Algorithms for IoT and Data Science . His work spans innovations in acoustic augmented reality (Ear-AR), teeth activity sensing via earphones (EarSense), and positioning systems using polarized light (CELLI). His research group, SiNRG, explores signal processing and IoT applications under the advisement of Romit Roy Choudhury. Key contributions include MobiSys Best Demo Runner-up (2017) for CELLI and advancements in sample-constrained optimization for audio personalization. He has contributed to IEEE standards (e.g., 802.15.7r1) and served as a tutorial speaker at MobiCom and conference co-chair roles.