جست‌وجوی استاد و پژوهشگر

Xingchen Zhangمشاهده پروفایل

مدرس

• Human Intention Prediction
• Human Pose Estimation
• Image Fusion
• +۳ مورد دیگر

Dr. Xingchen Zhang is a Marie Skłodowska-Curie Individual Fellow at the Personal Robotics Laboratory (PRL), Imperial College London, and holds a Lecturer position in the Department of Electrical and Electronic Engineering. Previously, he served as a Teaching Fellow and Research Associate at Imperial College. He teaches Deep Learning courses and is actively involved in academic reviews for prestigious programs like UKRI Future Leaders Fellowships and top conferences/journals such as CVPR, ECCV, and IEEE TNNLS. Xingchen earned his BSc from Huazhong University of Science and Technology (2012) and PhD from Queen Mary University of London (2018). His research focuses on human motion prediction, pose estimation, image fusion techniques (visible-infrared, multi-focus), visual object tracking, and deep learning applications in computer vision. His work has led to a notable book on image fusion, awarded the National Science and Technology Academic Publications Fund in China (2019). His recent publications emphasize real-world applications such as traffic flow prediction, pedestrian privacy protection, and fusion-based object tracking. He contributes to advancing graph neural networks for mobility analysis and spatio-temporal modeling, while maintaining a strong focus on interdisciplinary robotics and AI solutions. Awards: Marie Curie Fellowship, National Science & Technology Academic Publications Fund (2019) Key Roles: Reviewer for UKRI FLF, CVPR, ECCV, IJCV Labs: Personal Robotics Lab (PRL), Imperial College London

Beat Signerمشاهده پروفایل

استاد

• Cross-Media Information Spaces and Architectures (CISA)
• Interactive Paper
• Dynamic Data Physicalisation
• +۷ مورد دیگر

Beat Signer is Professor of Computer Science at Vrije Universiteit Brussel (VUB) and Director of the Web & Information System Engineering (WISE) laboratory. His research focuses on cross-media information spaces and architectures (CISA) spanning interactive paper, dynamic data physicalisation, and tangible holograms. His educational background includes a Computer Science degree from ETH Zurich, where he completed his PhD thesis on fundamental concepts for interactive paper and cross-media information spaces in 2005. Key research areas include: Cross-media document formats and resource-selector-link (RSL) hypermedia metamodel Context-sensitive adaptation and cross-media transclusion Multimodal interfaces (Mudra, iGesture) and tangible computing Internet of Things interoperability and semantic middleware Recent publications (2023-2025) reveal strong trends in dynamic data physicalisation hardware, FAIR positioning systems (OpenHPS), end-user IoT development (eSPACE), and next-generation human-information interaction paradigms. His work increasingly integrates Solid protocols for decentralized data and explores thermal dimensions in tangible holograms. As Principal Investigator, he leads multiple EU-funded projects including OpenHPS, TangHo, and eSPACE. His team has developed influential frameworks like MindXpres for cross-media presentations and CMT for context modeling. He supervises 13 doctoral researchers including Dr. Maxim Van de Wynckel and Dr. Audrey Sanctorum, focusing on cross-media applications in education, IoT, and data visualization. His WISE laboratory develops innovative solutions bridging digital and physical information spaces through projects like ArtVis for collaborative data exploration and TangHo for physically augmented virtual objects.

Reginald Souleyretteمشاهده پروفایل

استاد

• Transportation Engineering
• Traffic Safety
• Transportation Data Analytics
• +۵ مورد دیگر

Dr. Reginald R. (Reg) Souleyrette is the Chair of the Department of Civil Engineering and Commonwealth Professor of Transportation Engineering at the University of Kentucky. He also serves as Program Manager for Planning and Education at the Kentucky Transportation Center. With over 25 years of experience, he teaches courses in highway safety, GIS, and airport design. His research focuses on transportation data analytics, traffic safety, railroad engineering, and sustainable infrastructure, with over $10M in sponsored projects. Education: PhD in Civil Engineering (Transportation) from UC Berkeley (1989), M.S. and B.S. in Civil Engineering from University of Texas (1986, 1984). Licensed as a Professional Engineer in KY and IA. Research interests include transportation policy, data-driven decision support, and multimodal safety systems. He is a Fellow of the Association of Traffic Safety Information Systems Professionals and active in TRB committees, serving as Communications Coordinator for its Data and Information Systems Section. Key contributions include railroad crossing safety tools (e.g., FARSA system), automated safety assessment frameworks, and innovations in traffic incident management. His work spans international case studies, policy analysis, and advanced modeling techniques.

Ravishankar Ramanathanمشاهده پروفایل

استادیار

• Quantum Cryptography
• Quantum Information Theory
• Device-Independent Quantum Information Processing
• +۳ مورد دیگر

Ravishankar Ramanathan is an Assistant Professor at the University of Hong Kong's School of Computing and Data Science, Department of Computer Science. His research spans Quantum Cryptography, Quantum Information Theory, and Human-Robot Interaction. He holds a PhD from the National University of Singapore (2013), with prior postdoctoral roles at The National Quantum Information Centre (Poland), Université Libre de Bruxelles, and the University of Oxford. His work includes foundational studies in quantum mechanics and advanced robotics applications, with over 30 refereed publications in top journals like Nature Communications and Physical Review Letters. Research interests focus on quantum device-independent protocols, randomness amplification, and human-centric robotics systems. His lab (QIFT Group: https://qift.weebly.com/) explores both theoretical quantum mechanics and practical robotics solutions for mobility assistance and social interaction. Recent publications highlight contributions to quantum cryptography (e.g., noise-tolerant protocols) and autonomous systems (e.g., robotic wheelchair navigation and social robot design). He collaborates internationally, bridging quantum theory with real-world robotics applications.

• Machine Learning
• Deep Learning
• Neural Networks
• +۵ مورد دیگر

Sam Leroux is a Tenure Track Assistant Professor and IMEC Postdoctoral Researcher at Ghent University's Faculty of Engineering and Architecture, Department of Information Technology. His research spans multiple interdisciplinary domains where artificial intelligence meets real-world applications, with particular emphasis on machine learning, deep neural networks, and distributed systems. He maintains active collaborations with IMEC and contributes to several EU and national research initiatives focused on practical AI deployment. Dr. Leroux's research interests center on developing efficient and privacy-aware machine learning systems that can operate effectively on resource-constrained devices. His work bridges theoretical advances in neural network architectures with practical applications in agriculture, healthcare monitoring, industrial IoT, and sustainable computing. He has pioneered approaches in adaptive neural networks that dynamically adjust computation based on available resources, enabling AI deployment at the network edge without compromising privacy. His publication record reveals a clear trajectory from foundational work in neural network architectures toward increasingly applied research. Recent publications demonstrate strong focus on privacy-preserving AI techniques, hardware-efficient machine learning, and computer vision applications in agriculture and industrial settings. His work consistently addresses the tension between model performance and resource constraints, with growing emphasis on ethical considerations in AI deployment. As an academic supervisor, Leroux currently guides numerous doctoral researchers across diverse projects including broiler welfare monitoring, hardware-efficient continuous learning, UAV-based agricultural sensing, and privacy-aware ergonomic analysis. He serves as Promotor for the 'Hardware-efficient continuous learning' project funded by the Special Research Fund, demonstrating his leadership in securing competitive research funding. His work environment features strong connections between Ghent University's academic research and IMEC's technological expertise, creating a fertile ground for translating theoretical advances into practical solutions. This positioning enables his research group to tackle challenges spanning from algorithm development to hardware implementation, with particular focus on real-world validation of proposed techniques.

• Robotics
• Machine Learning
• Computer Vision
• +۳ مورد دیگر

Prof. Abhinav Valada is a Full Professor (W3) at the University of Freiburg, leading the Robot Learning Lab and serving as Chair of the IEEE RAS Technical Committee on Robot Learning. He holds affiliations with the Department of Computer Science , BrainLinks-BrainTools , and the ELLIS unit Freiburg . His research focuses on enabling robots to learn continuously through perception and interaction in complex environments, emphasizing scalable lifelong learning systems. Education: PhD (summa cum laude), University of Freiburg (2019) MS in Robotics, Carnegie Mellon University (2013) BTech in Electronics & Instrumentation, VIT University (2010) Research Interests: Robotics, machine learning, computer vision, with specializations in robot perception, state estimation, and planning. Current work emphasizes open-vocabulary scene understanding , uncertainty-aware perception , and embodied AI . Projects include multi-modal SLAM systems, neural radiance fields for robotics, and generalizable manipulation policies. Awards: IEEE RAS Early Career Award (2023) NVIDIA Research Award (2022) AutoSens Most Novel Research Award (2022) DFG Emmy Noether AI Fellowship (2021) Grants & Labs: Director of the Robot Learning Lab , co-founder of Platypus LLC (2013–2015), and collaborator on projects like SORTIE (disaster response robotics). Active in funding initiatives focusing on autonomous systems and AI ethics.

• Image Processing
• Signal Processing
• 3D Environments
• +۴ مورد دیگر

Stuart Perry is a Professor at the University of Technology Sydney (UTS), serving as Head of Discipline for Signal Processing and Analytics in the School of Electrical and Data Engineering. He holds affiliations with UTS' Faculty of Engineering and Information Technology, the Global Big Data Technologies Centre, and the Visualization Institute. With over 20 years of experience, his career spans roles at DSTO and Canon Information Systems Research Australia (CiSRA), focusing on image processing, signal processing, and perceptual quality measurement. Perry co-directs the Perceptual Imaging Laboratory (PILab), researching 3D environments, light field technologies, and human perception in immersive realities. He actively contributes to international standards committees like ISO/TC42 and ISO/SC29/WG7, leading JPEG's point cloud coding efforts. His research emphasizes adaptive image processing, machine learning-driven object detection, and medical imaging applications. Perry has authored 60+ publications, two books, and 20 patents. Current projects include VR empathy case studies, point cloud compression, and disaster management digital transformation. Education: PhD in Engineering, University of Sydney (1999) Research Interests: His work bridges computational imaging and human perception, addressing challenges in augmented/virtual reality (AR/VR), 3D scanning, and immersive media. Key areas include light field and point cloud coding, psychophysics of visual perception, and medical diagnostics via machine learning. He explores how perceptual principles can optimize interactive technologies for education, healthcare, and entertainment. Recent Research Trends: Recent articles focus on 3D Gaussian splatting, glaucoma detection via deep learning, and JPEG Pleno standards for plenoptic imaging. His work balances technical innovation (e.g., efficient point cloud compression) with human-centric design (e.g., reducing VR motion sickness through display lag analysis). Awards & Recognition: Member of IEEE and founding SPINet participant. Over 60 refereed publications and 20 patents highlight his industry-academic impact. Grants & Leadership: Leads SmartSat CRC projects on yield estimation and Aus4innovation-funded disaster response tech. Manages grants totaling millions AUD. Editorial roles include Associate Editor of SPIE/IS&T Journal of Electronic Imaging. Labs & Collaborations: PILab collaborates internationally on perceptual imaging standards. Active in ISO committees shaping future media technologies.

• Computer Vision
• Computer Graphics
• Machine Learning
• +۶ مورد دیگر

Dimitrios Tzionas is an Assistant Professor for 3D Computer Vision at the University of Amsterdam (UvA), leading research at the intersection of Computer Vision, Computer Graphics, and Machine Learning. His work focuses on reconstructing and modeling 3D human-body interactions with objects and scenes, supporting applications in Robotics, Mixed Reality, and the Metaverse. Academic Affiliation: University of Amsterdam (since 2022), Max Planck Institute for Intelligent Systems (2016-2022) Education: PhD in Computer Science (University of Bonn, 2017), MSc in Electrical & Computer Engineering (Aristotle University, Thessaloniki) His research emphasizes whole-body 3D interaction , including pose estimation, grasp synthesis, and contact-aware modeling. He develops methods like InteractVLM for semantic contact estimation and PICO for dense 3D contact datasets, leveraging vision-language models and optimization frameworks. Recent publications at CVPR, ICCV, and SIGGRAPH Asia highlight advancements in 3D reconstruction, avatar synthesis (PuzzleAvatar), and interactive dynamics (InterDyn). His work is supported by an ERC Starting Grant (2024-2030) and industry partnerships (Google, NVIDIA). Scientific Awards ERC Starting Grant (2024) ELLIS Scholar (2025) Outstanding Reviewer at CVPR, ICCV, ECCV He advises multiple PhD students, including Alvaro Budria and Lixin Xue , and collaborates with institutions like ETH Zurich and MPI-IS. His team's tools (e.g., ICON, GRAB) are widely adopted in academic and industrial research.

• Astrophysics
• Radio Astronomy
• Space Surveillance
• +۳ مورد دیگر

Dr. Steve Prabu is a Visiting/Adjunct Professor at Curtin University's Curtin Research Institute and Curtin Institute of Radio Astronomy (CIRA), affiliated with the School of Elec Eng, Comp and Math Sci (EECMS) under the Faculty of Science and Engineering. His work focuses on astrophysical phenomena such as black hole jets, X-ray binaries, and radio astronomy techniques. He is actively involved in space surveillance using low-frequency radio arrays like the SKA-Low and Murchison Widefield Array (MWA), contributing to satellite tracking and space domain awareness research. His research interests include studying jet dynamics in black hole systems, HI spectroscopic distance measurements, and improving observational techniques for space objects. Dr. Prabu has published extensively on topics ranging from radio galaxy structures to mitigating satellite interference in astronomical observations. He collaborates closely with institutions like CIRA and utilizes advanced instrumentation to advance both astrophysical understanding and practical applications in space surveillance. Awards & Recognition: No specific awards mentioned. Advising & Grants: No explicit details provided on student advising or grant funding. However, his involvement in major projects like SKA-Low suggests significant institutional support. Labs/Teams: Associated with Curtin Institute of Radio Astronomy (CIRA) and collaborates on MWA and SKA initiatives.

• Responsible AI
• Computer Vision
• Computer Graphics
• +۵ مورد دیگر

Prof. Hubert P. H. Shum is a Professor of Visual Computing and Director of Research in the Department of Computer Science at Durham University. He specializes in Responsible AI, Computer Vision, and AI in Healthcare. As a Co-Founder of the Durham University Space Research Centre and Fellow of the Wolfson Research Institute for Health and Wellbeing, he leads interdisciplinary research in healthcare, space technology, and autonomous systems. His work includes over 200 publications in top venues like CVPR, ICCV, and MICCAI, focusing on spatio-temporal data modeling. He has secured £10M+ in grants from EPSRC, MoD, and Innovate UK, supervising over 30 PhD students. Key projects include NortHFutures (digital health hub) and counter-drone research. Research interests span AI ethics, medical imaging, autonomous vehicles, and space applications. His lab develops technologies for surgical workflow anticipation, LiDAR segmentation, and human-AI interaction. Notable awards include Best Paper Awards in CVPR and exceptional teaching/supervision accolades from Durham University. Key Grants : EPSRC Impact Acceleration (£2.76M), EPSRC Digital Health Hub (£4.17M), Royal Society (£143k). Professional Activities : Conference chairs for Pacific Graphics, BMVC; editorial roles in Computer Graphics Forum and IJCV. Labs/Initiatives : Durham University Space Research Centre, Centre for Visual Arts and Culture.

Lineker Goulart Coelhoمشاهده پروفایل

استادیار

• Urban Water Management
• Green Infrastructure
• Life Cycle Assessment
• +۷ مورد دیگر

Lineker Goulart Coelho serves as an Assistant Professor in the Department of Engineering Technology and Didactics at the Technical University of Denmark (DTU), specializing in Building Technology and Processes. Based at the Ballerup campus, he actively leads research in sustainable urban water systems and green infrastructure while accepting PhD students. His research focuses on urban water management innovation through nature-based solutions, with particular expertise in green roof hydraulics, computational fluid dynamics for drainage systems, and life cycle assessment of sustainable materials. Current work integrates IoT sensor networks for real-time wetland monitoring and develops frameworks for biobased construction material production. Analysis of his 2025 publications reveals strong emphasis on practical urban climate adaptation , with 80% of works addressing hydraulic performance metrics under extreme conditions and 60% incorporating geospatial analysis for implementation planning. Key cross-cutting themes include circular economy integration and digital twin applications for environmental systems. Scientific Awards: Aase og Egnar Danielsens Fond (2022 & 2023) for Green Roof research Direktør Dr. Techn. A.N. Neergaards og Hustrus Fond (2022) for Water Quality studies As Principal Investigator for six active research projects including Print2build (3D concrete printing sustainability) and AUS: Autopoietic Urban Systems, he secures funding from major Danish foundations. His advising focuses on experimental hydrology and digital monitoring systems, with recent activities spanning 12 international conferences including NORDIWA 2024 and the 7th International Congress on Water Management.

John R. Wagnerمشاهده پروفایل

استاد

• Mechatronics
• Nonlinear Control
• Intelligent Control
• +۷ مورد دیگر

Dr. John R. Wagner is a Professor in the Department of Automotive Engineering at Clemson University's College of Engineering, Computing and Applied Sciences. He joined the department in August 1998 after industry roles at Delco Electronics, Hughes Electronics, and Delphi Automotive Systems, where he developed automotive control systems using hardware-in-the-loop and in-vehicle testing. Wagner established the Driving Simulator Laboratory and Rockwell Automation Mechatronics Educational Laboratory, and serves as faculty advisor for the Clemson SAE student chapter. His educational background includes: Ph.D. in Mechanical Engineering from Purdue University (1989) M.S. in Mechanical Engineering from SUNY at Buffalo (1985) B.S. in Mechanical Engineering from SUNY at Buffalo (1983) Wagner's research centers on Mechatronics , Nonlinear Control , and Intelligent Control systems with applications in automotive, energy, and manufacturing. He pioneers diagnostic/prognostic strategies and dynamic system modeling for turbine systems and vehicle safety, recently advancing digital twin technology for predictive maintenance and collaborative design. His work integrates AI-driven methodologies for autonomous vehicle safety and thermal management. Recent publications (2023-2025) reveal a dominant shift toward digital twin applications in ground vehicle maintenance, design validation, and tradespace exploration. Key trends include adversarial learning for highway safety, driver behavior analysis for traffic improvement, and PLM tool integration in engineering education, reflecting convergence of AI, systems engineering, and practical automotive solutions. His primary recognition includes: ASME Fellow Wagner actively mentors students through SAE chapter leadership and laboratory research, guiding capstone projects in mechatronics and vehicle dynamics. His educational initiatives include developing the Rockwell Mechatronics Laboratory and integrating PLM concepts into curriculum. Industry collaborations (e.g., Rockwell Automation) and editorial roles (IEEE/ASME Transactions on Mechatronics) underscore his impact on automotive engineering practice and pedagogy. He directs the Driving Simulator Laboratory and Rockwell Automation Mechatronics Educational Laboratory, enabling interdisciplinary research in vehicle control systems, energy harvesting, and human-vehicle interaction for next-generation automotive solutions.

Rudolf Widmer-Schnidrigمشاهده پروفایل

پژوهشگر

• Low-Frequency Seismology
• Planetary Interior Structure
• Mars Geophysics
• +۳ مورد دیگر

Rudolf Widmer-Schnidrig is a Researcher at the Institute of Geodesy within Faculty 06 at the University of Stuttgart. He is affiliated with the Black Forest Observatory (BFO) , where he specializes in low-frequency seismology to study Earth's mantle and core structure through elasto-gravitational free oscillations. His work extends to analyzing data from the InSight mission on Mars, contributing to understanding planetary interiors and Martian atmospheric processes. Recently, he has explored signatures of compact dark matter objects using terrestrial gravimeter data. Research focuses include seismic sensor calibration (e.g., DAS systems), atmospheric-seismic interactions, and long-period Earth oscillations. He has been instrumental in testing seismometers for Mars missions and interpreting InSight's seismic/meteorological data. His collaborative efforts span global seismology networks and interplanetary geophysical comparisons. Publications highlight innovations in sensor technology, Mars regolith characterization, and detection of rare seismic phenomena like 9-day Greenland fjord tsunamis. While no formal awards are listed, his contributions to planetary science and gravitational wave research are notable.

• Radar Systems
• Wireless Communications
• Signal Processing
• +۴ مورد دیگر

Dr. Robin AMAR is a Postdoctoral researcher at the University of Luxembourg's Interdisciplinary Centre for Security, Reliability and Trust (SnT), within the SPARC department. His research focuses on advanced waveform design for radar and communication systems, particularly in mmwave and automotive radar applications. He specializes in interference mitigation, Doppler-tolerant systems, and coexistence of radar-communication networks. His work integrates theoretical optimization with practical hardware implementations using platforms like USRP. Key research areas include polynomial phase waveforms, FMCW waveform optimization, and sensor network design. His studies address challenges in urban environments, spectrum sharing, and real-time signal processing. Dr. AMAR has contributed to both theoretical frameworks and experimental validations through measurement-based analyses. His expertise bridges electrical engineering, signal processing, and interdisciplinary security applications. Notable projects include designing interference-immune radar systems for automotive safety and developing dual-function waveforms for simultaneous sensing and communication. Despite no listed awards, his work demonstrates impactful contributions to radar technology innovation. He collaborates within SPARC's research teams but no specific labs or grants are detailed in the provided information.

Frankie Jacksonمشاهده پروفایل

مدرس

• Digital Twinning
• Aerodynamics
• Computational Fluid Dynamics
• +۶ مورد دیگر

Dr. Frankie Jackson is a Lecturer in Mechanical Engineering at the University of Huddersfield's School of Computing and Engineering. He leads teaching in aerodynamics, computational fluid dynamics (CFD), finite element analysis, and thermodynamics. His research focuses on digital twinning, meso-scale CFD, multiphase flow, and renewable energy systems. He holds a PhD from the University of Leeds (2021) and a bachelor's degree in Energy Engineering from the University of Huddersfield. As technical co-lead of the school's High Performance Computing facility, he specializes in parallel computing for complex simulations. His expertise includes gas pipeline dynamics, oil and gas systems, and pantograph-catenary interactions in rail engineering. He collaborates with industries via Knowledge Transfer Partnerships and contributes to UN Sustainable Development Goals related to clean energy and infrastructure innovation. Recent work involves optimizing wind turbines using ML-driven CFD and developing digital twins for control valves in oil/gas pipelines. Dr. Jackson is a member of the Institute of Mechanical Engineers and serves as vice-secretary of the Yorkshire Automobile Division Committee. His research spans from atomic-scale material polishing simulations to large-scale aerodynamic modeling, with 15 publications (2018–2025) and 75+ citations.