جستجوی استاد راهنمای دانشگاهی

Miles Hansardمشاهده پروفایل

مدرس ارشد

• Computer Vision
• 3D Scene Reconstruction
• Robotics
• +۶ مورد دیگر

Dr. Miles Hansard is a Senior Lecturer at Queen Mary University of London's School of Electronic Engineering and Computer Science. His research focuses on 3D scene reconstruction, multi-view imaging, depth cameras, radar localization, and human vision. He specializes in geometric aspects of vision, image processing, and robotics applications. His teaching includes modules on Computer Graphics (for both postgraduate and undergraduate students) and Introduction to Multimedia Systems. These courses cover topics like 3D graphics algorithms, human perception of color, and multimedia system fundamentals. Dr. Hansard's work integrates sensor technologies such as time-of-flight cameras and millimeter-wave radar to improve 3D reconstruction and robotic systems. He contributes to projects like the GRIP software framework for robotic grasping and has published extensively in journals like IEEE Transactions on Image Processing and the International Journal of Neural Systems. He is affiliated with the Centre for Multimodal AI, where he collaborates on research involving sensor fusion, autonomous systems, and visual perception. His expertise bridges computer vision, robotics, and multimedia engineering.

Alberto Quattrini Liمشاهده پروفایل

دانشیار

• Robotic Exploration
• Multi-Agent Systems
• Underwater Robotics
• +۱ مورد دیگر

Alberto Quattrini Li is Associate Professor of Computer Science at Dartmouth College, directing the Reality and Robotics Laboratory. His research develops autonomous systems for aquatic environments with applications in environmental monitoring and underwater archaeology. Current NSF-supported projects focus on multi-robot aquatic exploration and archaeological inspection systems. Research thrusts include surface vehicle obstacle avoidance in waterways, low-cost underwater sensing solutions, autonomous underwater construction, and laser-based air-underwater communication. Recent innovations include buoyancy-enabled manipulation systems and multi-sensor SLAM techniques for underwater operations. Quattrini Li advises six PhD students and collaborates with archaeologists through NSF grants. His laboratory prototypes systems using custom surface and underwater robotic platforms. No scientific awards are documented in the source materials.

Mohammad Naser Sabet Jahromiمشاهده پروفایل

استادیار

• Explainable Artificial Intelligence
• Biometrics
• Machine Learning
• +۴ مورد دیگر

Mohammad Naser Sabet Jahromi is an Assistant Professor at the Department of Architecture, Design and Media Technology, Aalborg University, Denmark. He is affiliated with the Visual Analysis and Perception Centre for AI Ethics, Law and Policy. His research focuses on explainable AI (XAI), biometrics, machine learning, and ethical AI applications in legal and medical domains. He actively participates in interdisciplinary projects like REPAI: Responsible AI for Value Creation (2023-2027), which explores AI ethics, computational discourse analysis, and value-driven AI systems. His educational background is not explicitly detailed in the provided text, but his research trajectory indicates strong expertise in computer science and AI systems. Key research interests include interpretable machine learning models, privacy-preserving biometric systems, and AI applications in asylum adjudication and educational assessment. Recent work emphasizes developing XAI frameworks like SIDU-TXT for NLP, verifying machine unlearning mechanisms, and automating large-classroom assessments. His projects bridge technical AI advancements with societal implications through collaborations with legal and ethical scholars. Notable contributions include datasets evaluating XAI methods in medicine and methodologies for transparent AI decision-making. He has participated in conferences such as ICPR 2024 and JURISIN 2023, showcasing interdisciplinary research impact.

Robin Bloomfieldمشاهده پروفایل

استاد

• Software and System Dependability
• Safety and Assurance Cases
• Security-Informed Safety
• +۷ مورد دیگر

Robin Bloomfield is Professor of Software and System Dependability at City, University of London, affiliated with the College of Engineering, Design and Physical Sciences. He is also a founding member of Adelard LLP, a leading consultancy in software safety and dependability, where he continues to contribute significantly. MA in Natural Sciences, University of Cambridge, 1978 His research focuses on the dependability of computer-based systems, particularly in safety, security, and reliability . Key areas include assurance cases , security-informed safety , trustworthiness evaluation , critical infrastructure interdependencies , and policy development . He has pioneered frameworks for evaluating complex systems, especially in nuclear and transportation domains. His recent publications highlight a growing emphasis on assuring machine learning and autonomous systems , integrating security into safety arguments , and developing methodologies for interdependency analysis in critical infrastructures. These works reflect a trend toward holistic, evidence-based assurance models for emerging technologies. Fellow of the Royal Academy of Engineering (FREng), 2014 Bloomfield has held influential roles in national and international advisory bodies, including the UK Nuclear Safety Advisory Group (NUSAC), the Cabinet Office Information Assurance group, and NATO research initiatives. He has chaired major conferences such as EWICS and served on the Safecomp programme committee for many years. He is also Associate Editor-in-Chief of IEEE Security & Privacy magazine and has advised the UK Parliament on systemic risks in computer-based trading. He leads research efforts that bridge academic rigor and real-world application, particularly through his work with Adelard. His projects often involve collaboration with government agencies, industry stakeholders, and international research bodies to address challenges in critical infrastructure resilience and safety assurance.

Francois Chaumetteمشاهده پروفایل

استاد پژوهش

• Robotics
• Computer Vision
• Visual Servoing
• +۱۷ مورد دیگر

François Chaumette is a Senior Research Scientist (Directeur de recherche) at Inria, affiliated with IRISA and the Centre Inria de l'Université de Rennes. He has been a key researcher in robotics and computer vision since 1990 and led the Lagadic research team from 2004 to 2017. His research interests are centered on robot vision, particularly visual servoing and active perception . He has made foundational contributions to image-based and position-based visual servoing, and his work integrates control theory, computer vision, and robotics. His research spans applications in mobile robotics, aerial systems, medical robotics, space robotics, and soft object manipulation. The recent publications highlight a consistent focus on visual servoing under complex constraints—such as motion blur, occlusions, and deformations—applied to drones, cable-driven robots, and space systems. There is a strong emphasis on robustness , stability analysis , and hybrid sensing (e.g., vision + proximity, vision + force). His work with the RemoveDebris mission demonstrates real-world impact in space robotics. AFCET/CNRS Prize for best Ph.D. in Automatic Control Best paper awards at RFIA 1996 & 2004 Best paper in IEEE T-RA (2002) Best paper in IEEE RA-L (2019) Best paper in IEEE RAM (2020) IEEE Fellow (2013) He has advised over 30 Ph.D. students, many of whom have become active researchers in robotics. He has served in editorial roles for top journals including IEEE Transactions on Robotics , IEEE Robotics and Automation Letters , and the International Journal of Robotics Research . He was elected to the IEEE RAS Administrative Committee (2016–2018) and served on ERC grant panels for robotics. Chaumette is the main developer of ViSP (Visual Servoing Platform), a widely used C++ library for visual tracking and servoing. His leadership in both theoretical advances and software tools has significantly shaped the visual servoing community.

Stewart Eskewمشاهده پروفایل

دانشگاهی

• Ethical Theory
• Medical Ethics
• Ethics of Artificial Intelligence
• +۷ مورد دیگر

Stewart Eskew is an Assistant Teaching Professor in the Department of Philosophy at the University of Wisconsin-La Crosse, part of the College of Arts, Social Sciences and Humanities. He teaches a wide range of courses including logic, ethics, epistemology, philosophy of science, and political philosophy, and is actively involved in the university’s AI Ethics Certificate program. Education: Ph.D. in Philosophy, University of Wisconsin–Madison M.A. in Philosophy, University of Wisconsin–Madison B.A. in Philosophy, California State University, Bakersfield His research centers on ethical theory, medical ethics, AI ethics, moral perception, and philosophy of science . He explores how moral knowledge is acquired through perception and how ethical principles apply to emerging technologies. His recent work emphasizes the integration of AI tools in humanities education and the ethical implications of artificial intelligence. His recent publications and presentations show a strong trend in moral epistemology and applied ethics , particularly focusing on perceptual models of moral knowledge, AI ethics, and careers in medical ethics. The interdisciplinary nature of his work bridges philosophy with healthcare, education, and technology. Professional Affiliations: American Philosophical Association Wisconsin Philosophical Association UWL Faculty Senate UWL Senate Executive Committee Emplify Health IRB Stewart has advised on curriculum development, particularly in ethics and AI, and has taught at multiple institutions including Marquette University, Coe College, and UW–Madison. He is engaged in pedagogical innovation and serves on university committees related to ethics and governance. He is also involved in outreach programs such as the Badger Precollege Program. He leads initiatives in AI ethics education and continues to develop research on moral expertise and perception. His work supports interdisciplinary collaboration between philosophy, healthcare, and technology sectors.

• Robotic Vision
• Autonomous Vehicles
• Computer Vision
• +۷ مورد دیگر

Dr. Annette Stahl is a Professor at the Department of Engineering Cybernetics, Norwegian University of Science and Technology (NTNU). She is an Onsager Fellow and leads the Robot Vision Group, overseeing the AILARON project funded by the Research Council of Norway. Her roles include affiliation with NTNU AMOS and the SFI AutoShip Centre for Research-based Innovation. Stahl holds a PhD in Applied Mathematics (Computer Vision) from Heidelberg University. Affiliations: NTNU AMOS, SFI AutoShip, and AILARON project leadership Research Focus: Robotic vision, autonomous systems, underwater exploration, and aquaculture monitoring Education: PhD in Applied Mathematics (Computer Vision) – Heidelberg University Research Interests: Her work spans robotic and computer vision, control theory, autonomous vehicles, mathematical image analysis, and machine learning applications in aquaculture and maritime systems. Key focus areas include underwater SLAM, sensor fusion for autonomous ships, and plankton detection using AI. Articles: Recent publications emphasize underwater robotic systems, sensor fusion for autonomous navigation, and AI-driven aquaculture monitoring. Key themes include 3D reconstruction, visual SLAM, and maritime tracking algorithms. Grants & Projects: AILARON (FRINATEK/IKTPLUSS) AUTOSIGHT (IKTPLUSS) AROS (IKTPLUSS) SFI AutoShip (SFI) Advising: Main supervisor for 10+ PhD candidates (e.g., Trym Nygård, Mauhing Yip) Co-advisor for projects like INDISAL (fish identification) Labs/Teams: Robot Vision Group at NTNU Collaborations with SINTEF Ocean and Zebop AS

Dmitri Williamsمشاهده پروفایل

استاد

• Technology and Society
• Online Gaming
• Social Capital
• +۵ مورد دیگر

Dmitri Williams is a Professor of Communication at the University of Southern California (USC) Annenberg School for Communication and Journalism. His research focuses on technology and society, particularly the social and economic impacts of new media, online gaming, and digital communities. He holds academic affiliations with multiple programs, including Communication (BA, PhD), Communication Data Science (MS), Communication Management (MCG), and Digital Social Media (MS). Williams earned his PhD from the University of Michigan in 2004. His work employs diverse methodologies, such as experiments, machine learning, surveys, and ethnography to study topics like social value measurement, player behavior in online games, and digital influence. He has collaborated with tech companies, startups, and policymakers, including testimony before the U.S. Senate on video games and serving as an expert witness in federal court cases. His research interests emphasize understanding how online environments shape social interactions, including topics like social capital, toxicity, mentorship dynamics, and gender representation. Notable projects include longitudinal studies on gaming communities, the Virtual Census series analyzing diversity in video games, and computational models of influence in digital systems. Williams’ publications span top journals like Journal of Communication , Computers in Human Behavior , and New Media & Society . He has been featured in major media outlets such as NPR , The New York Times , and Wired , and directs the Annenberg Game Lab. His consulting work helps firms optimize consumer engagement and player experience in gaming, retail, and donation platforms.

• Networking
• Operating Systems
• Distributed Systems
• +۶ مورد دیگر

Kang Shin is a Professor in the Department of Electrical Engineering and Computer Science at the University of Michigan's College of Engineering. His research spans multiple domains in computer science and engineering, focusing particularly on automotive security, wireless communications, and distributed systems.

• Human-Robot Interaction
• Explainable Robotics
• Assistive Robotics
• +۵ مورد دیگر

Dr. Maryam Banitalebi Dehkordi is a Senior Lecturer in Robotics and AI at the University of Hertfordshire, UK. She holds a PhD in Perceptual Robotics from Scuola Superiore Sant'Anna (Italy) and a master's in Mechatronics from University Technology Malaysia. Her career spans academia and industry, with roles at institutions like Technical University of Munich and NavVis GmbH, as well as industry projects such as the Innovate UK-funded AgriRobot. Her research focuses on Human-Robot Interaction (HRI) , Explainable Robotics , Assistive Robotics , and autonomous systems . Key projects include DOC (navigation aid for visually impaired individuals) and AgriRobot (precision agricultural robotics). She has expertise in activity recognition via smartphone sensors, navigation systems, and social robotics interfaces. Publications (2012–2025) emphasize explainable AI in robotics, feature selection for activity recognition, and social behavior interpretation. Her work bridges theoretical robotics with real-world applications in healthcare, agriculture, and accessibility. No awards are explicitly listed, but her extensive collaboration network (Italy, Germany, UK) reflects interdisciplinary impact. She advises on robotics projects and has contributed to both academic journals and industry collaborations.

Haizhong Wangمشاهده پروفایل

استاد

• Transportation Engineering
• Disaster Resilience and Emergency Management
• Intelligent Transportation Systems (ITS)
• +۳ مورد دیگر

Haizhong Wang is a Professor in the Department of Civil and Construction Engineering at Oregon State University, affiliated with the College of Engineering. He holds a Ph.D. in Civil Engineering from the University of Massachusetts Amherst (2010), an M.S. in Applied Mathematics from the same institution (2010), and earlier degrees from Beijing University of Technology and Hebei University of Technology in China. His research focuses on transportation systems, disaster resilience, and intelligent infrastructure solutions. Education: Ph.D., Civil Engineering, UMass Amherst, 2010 M.S., Applied Mathematics, UMass Amherst, 2010 M.S., Civil Engineering, Beijing University of Technology, 2006 B.S., Civil Engineering, Hebei University of Technology, 2003 Dr. Wang's research integrates traffic flow modeling, agent-based systems, and interdisciplinary approaches to address challenges in emergency evacuation logistics, autonomous vehicle impacts, and climate-resilient infrastructure. He explores topics such as tsunami preparedness, wildfire evacuation behavior, and optimization of electric vehicle networks. His work emphasizes data-driven methodologies for enhancing transportation safety, efficiency, and disaster response capabilities. Recent studies highlight his contributions to understanding evacuation decision-making under time-critical scenarios, optimizing multi-modal transportation networks, and assessing infrastructure vulnerability to cascading disasters. Collaborative projects include developing frameworks for cooperative logistics systems and interdisciplinary models linking natural, built, and social systems for community resilience. His grants and collaborations focus on disaster preparedness, smart work zones, and connected vehicle technologies. He advises on transportation safety and serves on research initiatives addressing climate adaptation and emergency management. Current efforts include refining agent-based models for vertical evacuation strategies and evaluating the societal impacts of automated vehicles on urban mobility.

Arturo Dezaمشاهده پروفایل

استادیار

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

Arturo Deza is an Assistant Professor of Computer Science at Universidad de Ingeniería y Tecnología (UTEC) in Lima, Peru, and CEO of Artificio, a research-driven company advancing autonomous driving technology. His academic work bridges neuroscience, machine learning, and computer vision, focusing on adversarial robustness, foveated systems, and human-machine perception. He holds a PhD in Dynamical Neuroscience from UCSB and a B.S. in Mechatronics Engineering from Universidad Nacional de Ingenieria. His research has been recognized with awards like the EB-1A Green Card for Extraordinary Ability and the Harvard Brain Initiative Travel Award. Deza's interdisciplinary approach includes contributions to image virality analysis, peripheral representation modeling, and bio-inspired AI. His recent talks and publications address topics ranging from autonomous driving challenges to neuro-symbolic AI integration. Education : PhD in Dynamical Neuroscience, UCSB (Vision and Image Understanding Lab) B.S. in Mechatronics Engineering, Universidad Nacional de Ingenieria Research Interests : Adversarial Robustness in Deep Learning Foveated Vision Systems Human-Machine Perception Autonomous Driving Technology Bio-inspired AI Models Awards : EB-1A Green Card for Extraordinary Ability in the Sciences Harvard Brain Initiative Young Scientist Travel Award NVIDIA Best Poster Award (2015) Professional Roles : Assistant Professor, UTEC (since Aug 2023) CEO & Co-Founder, Artificio (Lima-based autonomous driving tech) His recent work emphasizes practical AI applications, including the Robusto-1 dataset for autonomous driving evaluation and studies on adversarial robustness in perception systems. Deza also actively contributes to academic reviewing (ICLR, NeurIPS, CVPR) and organizes workshops like the Shared Visual Representations in Human and Machine Intelligence (SVRHM) at NeurIPS.

William Clarkمشاهده پروفایل

استادیار

• Geometric Mechanics
• Nonholonomic Systems
• Hybrid Systems
• +۷ مورد دیگر

William Clark is an Assistant Professor in the Department of Mathematics at Ohio University, affiliated with the College of Arts and Sciences. He is based at Morton Hall 527 on the Athens Campus and specializes in geometric mechanics, hybrid systems, and robotic perception. Education: B.S. in Mechanical Engineering, Ohio University, 2015 Ph.D. in Applied & Interdisciplinary Mathematics, University of Michigan, 2020 His research lies at the intersection of applied mathematics and robotics, focusing on geometric mechanics , particularly Lagrangian and Hamiltonian systems, nonholonomic constraints, and stability analysis. He also investigates hybrid systems , including Zeno phenomena and invariant structures in impact systems, with applications to locomotion and control. A third pillar of his work is robotic perception , where he develops geometric and gradient-based methods for sensor registration and pose estimation, often leveraging machine learning techniques. His publications reveal a strong trend in using geometric and topological methods to analyze complex dynamical systems, especially those involving discontinuities and constraints. His work bridges pure mathematical theory with practical applications in robotics and autonomous systems. Scientific Awards: No awards listed in the provided text. Advising and Grants: No students or advisees are listed. No grants or funding sources are mentioned. Labs and Research Teams: No specific lab or research team is mentioned in the provided information.

Timothy McMahanمشاهده پروفایل

استادیار

• Adaptive Virtual Environments
• Neurogaming
• Virtual Reality
• +۷ مورد دیگر

Dr. Timothy McMahan is an Assistant Professor in the Department of Computer Science at the University of North Texas. His research focuses on adaptive virtual environments, neurogaming, and applying VR/AR technologies to neuropsychological assessment and training. He holds a Ph.D. in Computer Science (2016) and multiple advanced degrees from UNT. Education: Ph.D. Computer Science, University of North Texas (2014–2016) M.S. Computer Science, University of North Texas (2007–2013) B.S. Computer Science, University of North Texas (2003–2007) Postdoctorate in Computational Neuropsychology, University of North Texas (2016–2017) Research Interests: Adaptive VR environments for personalized user experiences Neurogaming applications in healthcare and education Machine learning for cognitive assessment and environmental adaptation EEG-based analysis of user engagement and cognitive workload VR tools for neuropsychological disorder diagnosis and treatment Recent work emphasizes VR applications in memory research, adaptive systems leveraging real-time ML predictions, and EEG-driven analyses of subjective experiences. Articles focus on bridging virtual and real-world interactions through computational neuroscience methods. No scientific awards or grants are explicitly listed in the provided materials. No advisees or lab affiliations are documented here.

Gregoire Larueمشاهده پروفایل

دانشیار

• Road Safety
• Rail Safety
• Driver Behavior
• +۷ مورد دیگر

Associate Professor Gregoire Larue is a Principal Research Fellow at the University of the Sunshine Coast (UniSC), Australia, affiliated with the School of Law and Society and the Road Safety Research Collaboration. With expertise at the intersection of engineering, mathematics, and human factors, his research focuses on improving road and rail safety through understanding driver behavior in various conditions. His educational background includes a MEng from ECL in France, an MSc from the University of Queensland, and a PhD from Queensland University of Technology. Dr. Larue has worked in road and rail safety research since 2007, leading numerous projects for transport government agencies and the rail industry. Dr. Larue's research interests center on driver behavior in impaired and distracted driving scenarios. His current work focuses on developing AI technology to automatically detect impairment, with specific projects examining alcohol and medicinal cannabis effects on driving performance. He also investigates railway level crossing safety, monotonous driving effects on alertness, and driver behavior across diverse road environments. His publications demonstrate strong methodological rigor, combining driving simulators with physiological monitoring and advanced data analysis techniques. His recent publications (2024) span hazard perception of distracted drivers, cooperative lane-changing for autonomous vehicles, drowsiness detection systems, and railway level crossing safety, reflecting his diverse yet cohesive research program focused on practical road safety applications. Best paper – Transportation Research Board Annual Meeting, 2019 Standards Australia Young Leaders Program for 2018/19 Award Australasian Centre for Rail Innovation Fellowship Award Best paper (co-author) – International Journal of Advanced Computer Science and Applications, 2013 Outstanding Thesis Award, QUT, 2010 Nomination for the Peter Vulcan Award, 2009 Dr. Larue serves on the Australasian Road Safety Conference Scientific Committee and Interactive Workshop Sub-Committee, and is a member of the Railway Level Crossing Committee of the Transportation Research Board. His research has practical applications for road design, traffic management, and in-vehicle safety systems, with the ultimate goal of reducing road trauma through evidence-based interventions.