جست‌وجوی استاد و پژوهشگر

Zeinab Shirvaniمشاهده پروفایل

پژوهشگر ارشد

• Remote Sensing
• Artificial Intelligence
• Environmental Science
• +۳ مورد دیگر

Zeinab Shirvani is a Digital Futures Postdoctoral Fellow at KTH Royal Institute of Technology, affiliated with the Division of Geoinformatics in the Department of Urban Planning and Environment. Her research focuses on leveraging remote sensing and AI techniques to study forest disturbances, particularly in Miombo woodlands of southern Africa. She earned a PhD in Remote Sensing/Cartography from TU Dresden (Germany, 2020) and previously conducted postdoctoral research at the Swedish University of Agricultural Sciences (SLU). Her current project, 3Dfire (2023-2025), employs Sentinel satellite data and deep learning algorithms (e.g., RAUNet5) to enhance forest fire detection and analysis. This work aims to inform climate-smart forest management strategies, addressing challenges like fire severity, anthropogenic impacts, and climate change effects in vulnerable ecosystems. Key research themes include wildfire dynamics, AI-driven spatial-temporal analysis, and sustainable forest governance. Collaborating with Professors Yifang Ban and Ulla Mörtberg, her interdisciplinary approach bridges geoinformatics, environmental science, and climate policy. Outputs include high-impact publications on fire regimes, vegetation recovery, and landscape degradation. Zeinab’s broader contributions span deforestation modeling, landslide susceptibility mapping, and drought impacts on ecosystems. Her work integrates object-based image analysis, GIS, and machine learning to solve complex environmental challenges, with applications in both academic and policy contexts.

• Digital Humanities
• Literary Studies
• 19th-21st Century Literature
• +۵ مورد دیگر

Marine Riguet is a Lecturer in French Literature (19th-21st centuries) and Digital Humanities at the University of Reims Champagne-Ardenne, affiliated with the Interdisciplinary Research Center on Aesthetic and Literary Models (CRIMEL). She holds a PhD from Sorbonne University and completed a postdoctoral fellowship at OBVIL (Observatoire de la vie littéraire). Her work bridges literary studies with digital humanities, focusing on intermedial practices, text mining, and contemporary poetic forms. Riguet explores how digital tools transform literary analysis, particularly in studying 19th-century critique and modern multimedia writing. Education: PhD in Literature (Sorbonne University, 2018), postdoctoral research at OBVIL (Sorbonne-CNRS), and academic exchanges at the University of Chicago. She also spent three years in publishing before pursuing academia. Research interests include digital textualities, video poetry (LittéraTube), and the intersection of literature with science and technology. Her projects involve network analysis, semantic shifts, and creative writing in digital environments. Riguet collaborates with institutions like Compiègne University's COSTECH and Sorbonne's CELLF. Key achievements: 2021-2022 Discoverers’ Prize, publications in Po&sie and Humanités numériques , and contributions to interdisciplinary conferences. She teaches multimedia writing at MMI-IUT Troyes and leads workshops on video poetry and digital creation.

• Robotics
• Biomedical Engineering
• Control Systems
• +۳ مورد دیگر

Jason Gu is a Professor in the Department of Electrical and Computer Engineering at Dalhousie University, cross-appointed to the School of Biomedical Engineering. His research integrates robotics, control systems, and biomedical engineering to develop innovative solutions for mobile robotics, surgical systems, and rehabilitation technologies. His primary research domains include: Robotics : Mobile robotics, surgical robots, rehabilitation assistive devices, wireless control systems, and multi-sensor data fusion. Biomedical Engineering : Artificial eye implant control, medical robotic devices, and rehabilitation technology design. Control Systems : Real-time intelligent control, nonlinear systems theory, and embedded control applications. Alternative Energy : Development of novel energy technologies and systems. Analysis of his recent publications (2023-2025) reveals a strong convergence of AI with robotics, particularly in vision-language models for human-robot interaction, semantic SLAM for dynamic environments, and medical image processing. His work shows increasing emphasis on lightweight algorithms for UAVs, neural interfaces, and energy-efficient control systems for aerospace applications. His distinguished honors include: IEEE Canada President (2020-2021) and President-elect (2018-2019) Fellow of the Engineering Institute of Canada (FEIC) Fellow of the Canadian Academy of Engineering (FCAE) Professional Engineer (PEng) designation Professor Gu leads a dynamic research laboratory developing advanced robotic platforms including the PA10 Portable General-Purpose Intelligent Arm and B21r Mobile Robotic System. His team actively pursues real-world applications in surgical robotics, terrain perception for legged robots, and alternative energy systems through industry-academic partnerships and competitive research grants.

Timothy Wileyمشاهده پروفایل

مدرس

• Autonomous Robotics
• Artificial Intelligence
• Online Learning
• +۶ مورد دیگر

Dr. Timothy Wiley is a Lecturer in Computer Science at RMIT University's School of Computing Technologies within the STEM College. He specializes in Artificial Intelligence and Robotics, focusing on autonomous systems, online learning, and human-robot interaction. His roles include leading the RedbackBots RoboCup team and designing core courses in AI and robotics. He holds a PhD from UNSW Sydney and has extensive industry and academic collaborations, including with Rheinmetall Defence Australia and Nova Systems. Affiliations: RMIT AI Innovation Lab, CIAIRI, RUASRT Education: PhD (Computer Science, UNSW), BSc (Computer Science, UNSW) Research: Autonomous robotics, Explainable AI, UAV systems, fatigue crack modeling Research interests center on data-efficient machine learning for robotics, explainable AI, and applications in agriculture, aviation, and defense. Recent projects include UAV delivery systems and AR visualization for RoboCup. He teaches courses like Programming Autonomous Robots and leads the first-year Programming Studios. Notable achievements include the 2025 Best Paper Award at HRI and finalist status in RMIT's 2023 Research Leadership Awards. His work bridges academic research with industry applications, such as food waste reduction in macadamia harvesting and urban wind environment modeling for AAM.

J. Michael Mooreمشاهده پروفایل

عضو هیئت علمی

• Human-Computer Interaction
• Software Design
• Information Retrieval
• +۶ مورد دیگر

J. Michael Moore is an Instructional Associate Professor in the Department of Computer Science & Engineering at Texas A&M University, part of the College of Engineering. He holds a PhD in Computer Science from Texas A&M (2007) and has extensive teaching experience in courses like Human-Computer Interaction and Accessible Computing. His research focuses on HCI, software design, accessibility, and digital libraries, with notable work on design exploration and document triage systems. Education includes a B.S. in Biochemistry from Texas A&M (1991) and an M.S. in Computer Science from Texas State University (1997). He has authored over 20 peer-reviewed publications and has been recognized with awards such as the 2014 Mentoring Award and the Guseman Award (2002). Moore also contributes to professional service roles, including advising student organizations like DeAF and OSTEM. Teaching: Over 20 years of instruction in programming, HCI, and accessible computing. Research: Specializes in HCI, accessibility, and collaborative design tools. Service: Serves on committees for diversity initiatives and professional networks. His work integrates technical innovation with user-centered design principles, emphasizing accessibility and inclusive computing practices.

• Computer Science Education
• Virtualization
• Embedded Runtime Systems
• +۳ مورد دیگر

Rebecca Schreib serves as an Assistant Teaching Professor and Director of Undergraduate Studies in Rice University's Department of Computer Science. She holds a Ph.D., M.S., and B.S. in Computer Science from Rice University (2019, 2015, 2014 respectively). Her research focuses on computer science education, virtualization, and embedded runtime systems. Her educational background includes a doctoral emphasis on designing personalized interactive learning tools for large introductory courses. Key research contributions include MemStep (2024), collaborative computational thinking courses (2020), and automated assessment systems (2016–2017). Her work spans both educational technology and embedded systems, with a focus on bridging theory-practice gaps in programming education while advancing runtime system reliability for constrained environments. She has developed tools that enhance student engagement and automated systems for testing and memory management. While no scientific awards are listed, her publications reflect sustained innovation in educational technology and embedded computing since 2012. Her advising and grant activities are not explicitly documented here. She contributes to Rice's undergraduate program infrastructure through her directorship role.

• Computational Neuroscience
• Mathematical Modeling
• Neuroinformatics
• +۱ مورد دیگر

Sharon Crook is a Professor in the School of Mathematical and Statistical Sciences at Arizona State University, where she serves as Associate Director for Graduate Programs. Her research focuses on computational neuroscience, developing standardized modeling approaches like NeuroML for multi-scale simulations of neural systems. Her work bridges computational neuroscience, cognitive science, and machine learning, creating integrative frameworks for model development. Research interests include neural oscillations, computational neuroanatomy, model interoperability, and data-driven approaches to understanding neural dynamics. Her recent publications demonstrate a strong focus on developing standardized modeling frameworks and computational tools. She explores applications in medical imaging analysis, neural simulation platforms, and collaborative neuroscience resources.

Sourav Gargمشاهده پروفایل

پژوهشگر ارشد

• Computer Vision
• Robotics
• Deep Learning
• +۴ مورد دیگر

Dr. Sourav Garg is a Research Fellow at QUT's School of Electrical Engineering and Robotics, affiliated with the QUT Centre for Robotics and the Australian Centre for Robotic Vision (ACRV). He holds a PhD from QUT (2019) and specializes in robotic vision, with a focus on visual place recognition, scene understanding, and robot navigation. His research emphasizes practical applications, such as localization using visual semantics and addressing viewpoint and scene appearance challenges. Dr. Garg's work has been recognized with awards including the Executive Dean's Commendation for his thesis and the SAGE QUT Publication Prize. He has published extensively in top-tier venues like the International Journal of Robotics Research (IJRR), IEEE ICRA, and ECCV. His research has been featured in media outlets such as Brisbane Times and Engineers Australia. Education: PhD in Robotics from QUT (2019) Affiliations: QUT Centre for Robotics, ACRV Research Affiliate Research Highlights: Pioneered semantic-geometric approaches for place recognition, developed open-source tools like OpenSeqSLAM2.0, and explored multi-resolution and multi-scale fusion techniques for visual localization. His contributions span collaborations with government organizations and industry, focusing on applications in autonomous systems, drones, and indoor robots.

• Neuroscience of Creativity
• Educational Neuroscience
• Cognitive Neuroscience
• +۵ مورد دیگر

Adam E Green is a Professor in the Department of Psychology at Georgetown University's College. He specializes in the neuroscience of creativity, particularly how neural processes underpin creative thinking and learning. His work integrates cognitive neuroscience with educational contexts, exploring endogenous neural mechanisms and neurostimulation techniques to enhance creativity. He is the founder and former President (2019-2021) of The Society for the Neuroscience of Creativity. Dr. Green holds a Ph.D. in Cognitive Neuroscience from Dartmouth College and a B.A. from Johns Hopkins University. His research focuses on creativity's neural foundations, including the cognitive and emotional dynamics of creative problem-solving, math anxiety's impact on STEM performance, and spatial cognition development. He has pioneered tools like the Scientific Creative Thinking Test (SCTT) and conducts translational research to bridge neuroscience and educational practice. His recent work examines creativity differences in natural environments, the role of semantic integration in idea generation, and computational approaches to predicting academic success through creativity metrics. Key contributions include linking creativity to brain network dynamics, demonstrating creativity-specific anxiety, and advancing interdisciplinary frameworks for creativity measurement. His grants focus on enhancing creative cognition through neuroscientific insights and improving STEM education via spatial learning interventions. Active in both basic and applied neuroscience, Green's work has implications for mental health, education policy, and cognitive enhancement technologies.

Julie Wallمشاهده پروفایل

استاد

• Artificial Intelligence
• Advanced Computing
• Deep Learning
• +۱۲ مورد دیگر

Professor Julie Wall is a faculty member at the University of West London, serving as Professor of AI and Advanced Computing in the School of Computing and Engineering. She is actively engaged in research, teaching, and professional service, including her role as an expert at the British Standards Institution (BSI) in the domain of artificial intelligence. Research Interests: Julie Wall's research is centered on the design and application of intelligent systems for processing and modeling temporal data, particularly in speech and language. She leverages neural network architectures—ranging from biologically inspired models to computationally efficient deep learning systems—to analyze diverse data types such as audio, video, images, tabular data, and 3D features. Her work extends to developing production-grade deep learning and natural language understanding systems for immersive environments like virtual and augmented reality. Publications and Research Trends: Her body of work, comprising over 50 high-quality papers and multiple patents, reflects a strong trajectory in AI systems that integrate multimodal data with temporal dynamics. The research spans core areas of machine learning, natural language processing, and applied AI, with increasing focus on real-world deployment, efficiency, and intelligent interaction in extended reality platforms. Scientific Awards: US Patent UK Patent Advising and Grants: Julie Wall supervises research students across disciplines including forensic science and artificial intelligence. She contributes extensively to academic programs, teaching courses such as BSc and MSc in Computer Science, Artificial Intelligence, Data Science, and specialized AI programs in cybercrime and criminal justice. While specific grant details are not listed, her patent holdings and publication volume suggest sustained research funding and project leadership. Labs and Teams: As a leading researcher in AI and advanced computing, she is likely involved in or leads research groups focused on intelligent systems, deep learning, and multimodal AI at the University of West London, though specific lab names are not mentioned in the text.

Dujuan Yangمشاهده پروفایل

استادیار

• Urban Planning
• Smart Cities
• Energy Systems
• +۵ مورد دیگر

Dujuan Yang is an Assistant Professor in the Department of the Built Environment at Eindhoven University of Technology (TU/e). Her research focuses on Travel Behavior and Energy Effects, Urban Infrastructure Management, Energy Neutral City Development, and Decision Support Systems in Smart Cities. She leads the TU/e Smart Cities program's Urban Data & Data Platform initiative and has expertise in quantitative methods for urban sustainability. Dr. Yang holds a Ph.D. from TU/e (2013 Prestige Grant recipient), MSc from Harbin Institute of Technology, and BSc from Southeast University. She has co-authored over 50 peer-reviewed articles in journals like Transportation Research Part C and Applied Energy , and led projects like Triangulum and DESENT. She serves as Guest Editor for Urban Planning and reviewer for 15+ journals. Her research bridges urban data analytics with policy impact, emphasizing digital twins for energy efficiency, evacuation safety, and occupant comfort. Notable contributions include frameworks for sustainable urban energy systems and methodologies for analyzing household energy adaptation strategies under policy changes. Key Projects: Triangulum (Smart Cities Implementation), DESENT (Decision Support Systems) Awards: WCTR Prestige Grant (2013) Grants: €2.5M+ secured through EU Horizon 2020 and Dutch funding Dr. Yang's work integrates smart technologies with human-centric design, addressing challenges like climate resilience and equitable urban development through data-driven solutions.

Mark Sandlerمشاهده پروفایل

استاد

• Digital Signal Processing
• Machine Learning
• Deep Learning
• +۶ مورد دیگر

Mark Sandler is a Professor of Signal Processing and Director of the Centre for Digital Music at Queen Mary University of London. He leads the School of Electronic Engineering and Computer Science and contributes to the Centre for Multimodal AI. His work spans Digital Signal Processing, Machine Learning, and their applications in Audio and Music Technology, including source separation, neural audio synthesis, and physics-informed models. He has pioneered research in music informatics, sound synthesis, and AI-driven creativity. Awards include Fellowships from the Royal Academy of Engineering (FREng), IEEE (FIEEE), IET (FIET), and Audio Engineering Society (FAES). Research interests include audio segmentation, harmonic analysis, and interdisciplinary projects with computer vision. He has authored numerous publications on topics like neural synthesizers, knowledge distillation, and spatial audio systems. His contributions extend to semantic web technologies for music production and interactive audio applications. Current projects focus on low-latency synthesis, machine learning for music tagging, and adaptive audio systems. Awards and grants highlight leadership in digital music innovation. His academic roles include supervising research groups and directing interdisciplinary initiatives. The labs under his leadership include the Centre for Digital Music and collaborations with industry partners on audio engineering and immersive technologies.

• Machine Learning
• Computer Vision
• Robotics
• +۵ مورد دیگر

Roberto Javier López Sastre is an Associate Professor of Signal Theory and Communications at the University of Alcalá. He holds a Ph.D. from the same institution (2010), focusing on 'Visual vocabularies for category-level object recognition' under Dr. Saturnino Maldonado Bascón's supervision. His research spans machine learning, computer vision, robotics, and astrophysics. Key areas include Bayesian neural networks for stellar dating, semantic navigation in robotics, and AI-driven medical assistive technologies. Affiliation: Department of Signal Theory and Communications, University of Alcalá Research Group: GRAM (Multisensorial Recognition and Analysis Group) His work interfaces computational methods with real-world applications, such as assistive robotics for neurodevelopmental disorder patients and deep learning models for astrophysical parameter estimation. Recent contributions include semantic segmentation-driven navigation systems and Bayesian approaches to black hole solutions. Publications emphasize interdisciplinary applications of AI, including live video processing, continual learning frameworks, and physics-informed neural networks. Ongoing research explores the intersection of robotics, healthcare, and astrophysics through collaborative projects. López Sastre's GRAM group focuses on multisensory data analysis for recognition and navigation challenges. His technical expertise spans signal processing, probabilistic modeling, and embedded AI systems.

Boris Jutziمشاهده پروفایل

استاد

• Active Optical Sensors
• Computer Vision
• Laser Scanning
• +۷ مورد دیگر

Prof. Dr. Boris Jutzi is a leading academic in photogrammetry and remote sensing, currently serving as Professor at Karlsruhe Institute of Technology (KIT) and acting head of the Chair of Photogrammetry and Remote Sensing at Technical University of Munich (TUM). His research focuses on active optical sensors, computer vision, laser scanning, and 3D reconstruction techniques. He holds a diploma in electrical engineering from University of Kaiserslautern, a PhD from TUM, and venia legendi from KIT. Affiliations: KIT Institute of Photogrammetry and Remote Sensing, TUM Chair of Photogrammetry and Remote Sensing Education: Diploma in Electrical Engineering (University of Kaiserslautern) Doctorate (TUM) Venia Legendi (KIT) His research interests include: Neural Radiance Fields (NeRF) for 3D reconstruction LiDAR technology and applications UAV-based remote sensing Geospatial data fusion Computer vision in environmental monitoring Awards: Faculty Teaching Award (2020) Best Paper Awards (2019, 2016, 2014, 2006) His work emphasizes novel sensor integration and automated scene analysis , with contributions to urban and environmental 3D modeling. Current projects include underwater scene reconstruction via NeRFs and large-scale digital twin datasets (e.g., TUM2TWIN).

Leonardo Magela Cunhaمشاهده پروفایل

مدرس

• Artificial Intelligence
• Multi-agent Systems
• Agent-based Modeling
• +۴ مورد دیگر

Leonardo Magela Cunha is a Lecturer in Computer Science at King's College London's Department of Informatics, part of the Faculty of Natural, Mathematical & Engineering Sciences. He holds a PhD from the Pontifícia Universidade Católica do Rio de Janeiro (PUC-Rio) and previously worked as a Software Engineer at Petrobras. His research focuses on Artificial Intelligence, Multi-agent Systems, Agent-based Modeling, Semantic Web technologies, and Responsible AI Education. He is affiliated with King's Computing Education Research Centre (CERC) and contributes to the Sustainability Hub, exploring Distributed Artificial Intelligence in socio-economic contexts. Key research interests include the intersection of AI ethics with education, semantic frameworks for collaborative environments, and agent-based approaches to group formation in e-learning platforms. He co-authored the influential 2023 working paper on Responsible AI Education frameworks, blending technical and pedagogical insights. Earlier work centered on semantic web applications, model-driven architecture (MDA), and collaborative learning platforms like AulaNet, leveraging agent-based approaches for group management and task allocation. His academic contributions span over 15 publications since 2001, emphasizing both foundational technical research and applied educational technology. He leads the Computing Education Research Centre's initiatives in curriculum design and pedagogical innovation, particularly in computer science education. Current projects aim to integrate sustainability metrics into distributed AI systems and address ethical challenges in AI curricula. Labs/Teams: Sustainability Hub, Computing Education Research Centre (CERC) Key Collaborations: Multi-institutional AI ethics frameworks, Agent-based learning systems Future Work: Expanding Responsible AI education programs, semantic web interoperability standards