Find Academic Supervisors

• Robotic Vision
• Autonomous Vehicles
• Computer Vision
• +7 more

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

• Cognitive Robotics
• Human-Robot Interaction
• Developmental Robotics
• +14 more

Alessandro Di Nuovo is a Professor in the Department of Computing and Mathematics at Sheffield Hallam University, within the College of Business, Technology and Engineering. He is a leading researcher in cognitive and developmental robotics, with a focus on human-robot interaction, assistive technologies, and neuromorphic computing. His work bridges AI, robotics, and healthcare, particularly in applications for autism therapy and active ageing. His research spans cognitive robotics , neuromorphic computing , assistive robotics , and human-robot interaction , with a strong emphasis on embodied cognition, numerical cognition in robots, and privacy-aware systems. He has pioneered the use of spiking neural networks and event-based vision for real-time robotic perception and learning. His work often integrates cloud computing and multimodal interfaces to enhance robotic services for elderly care and children with developmental disorders. The recent publications highlight a consistent trend in personalized, interactive learning systems , where robots learn from human feedback using reinforcement learning, natural language, and sleep-inspired consolidation. There is also a growing focus on privacy and cybersecurity in social robotics, reflecting ethical considerations in assistive technologies. Applications are strongly oriented toward healthcare , including stroke rehabilitation, ASD screening, and in-home monitoring for older adults. He has been involved in numerous collaborative projects, often as a principal investigator or senior researcher, working with institutions across Europe. His contributions to major conferences and journals underscore his leadership in the field of cognitive and developmental systems. Di Nuovo has supervised and collaborated with a wide range of students and researchers, including Simone Varrasi, Roberto Vagnetti, Muhammad Aitsam, and Daniela Conti. His work has been supported by grants from EPSRC and other UK research councils, particularly in the domain of robotics for healthcare and social good. He is actively involved in research groups focusing on assistive robotics , cognitive systems , and cybersecurity in healthcare robotics , contributing to both theoretical models and real-world implementations of socially intelligent robots.

Fernando E. CasadoView profile

Researcher

• Machine Learning
• Robotics
• Human-Robot Interaction
• +5 more

Dr. Fernando E. Casado is a Researcher at the Personal Robotics Lab (PRL) within the Department of Electrical and Electronic Engineering at Imperial College London since March 2023. He holds a BSc in Computer Science (2017, University of Santiago de Compostela) with awards for academic excellence, an MSc in Artificial Intelligence Research (2018, Menéndez Pelayo International University), and a PhD in Computer Science (2022, USC) with Cum Laude distinction for his work on continual federated learning strategies. His research focuses on multi-robot and multi-user machine learning to enhance trustworthy human-robot interaction, addressing challenges such as concept drift, non-stationary data, and personalized robotic behavior. Key contributions include federated learning frameworks for assistive robotics, adaptive algorithms for heterogeneous data, and eye-gaze tracking for trust assessment in HRI. Publications span topics like federated learning, continual learning, and human-robot trust, with applications in assistive devices and smart environments. Awards include the Best Academic Record and Thesis Award (BSc) and the highest honors in his PhD. Casado’s work bridges theoretical machine learning with practical robotics, emphasizing privacy-aware systems and user-centered design. He collaborates internationally, including visits to PRL in 2021, and contributes to advancing adaptive algorithms for real-world robotic applications.

• Human-Robot Interaction
• Explainable Robotics
• Assistive Robotics
• +5 more

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.

Arturo DezaView profile

Assistant Professor

• Computer Vision
• Machine Learning
• Deep Learning
• +5 more

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 ClarkView profile

Assistant Professor

• Geometric Mechanics
• Nonholonomic Systems
• Hybrid Systems
• +7 more

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.

Vlachos KostasView profile

Assistant Professor

• Robotics
• Control of Robotic Mechanisms
• Microrobotics
• +7 more

Kostas Vlachos is an Assistant Professor in the Department of Computer Science and Engineering at the University of Ioannina, Greece. He has been in this position since 2014, following prior teaching roles at the University of Thessaly (2007–2013). He is a member of the Information Processing and Analysis (I.P.AN.) research group and actively supervises PhD, MSc, and diploma students in robotics and control systems. PhD, School of Mechanical Engineering, National Technical University of Athens, 2004 MSc, Interdepartmental Postgraduate Program in Automation Systems, National Technical University of Athens, 2000 Diploma in Electrical Engineering, Technical University of Dresden, Germany, 1993 His research focuses on robotics and control, with emphasis on microrobotics , haptic mechanisms , medical simulators , and autonomous navigation . He has made significant contributions to over-actuated marine platforms, reinforcement learning for navigation, and tactile robotic systems. His work bridges mechanical engineering and computer science, particularly in intelligent robotic control. The 15 most recent publications highlight a strong trend in autonomous marine robotics , multi-agent reinforcement learning , and intelligent control systems . Key themes include energy-efficient control, obstacle avoidance, sensor fusion, and learning-based navigation. The research spans from theoretical control design to real-world implementation in unmanned surface vehicles and microrobots. Best Student Paper Award, 9th Hellenic Conference on AI (SETN 2016) Vlachos has supervised over 30 students at various levels and has participated in multiple national and European research projects in robotics and automatic control. His teaching includes courses such as Computational Mathematics, Robotics, and Robotic Systems. He collaborates extensively with researchers like E. Papadopoulos and K. Blekas. He leads research within the Information Processing and Analysis (I.P.AN.) group, focusing on intelligent perception and control of robotic systems. His lab works on mobile manipulators, haptic devices, mini-robots, and marine platforms, integrating simulation (ROS/Gazebo) with real-world experimentation.

Mohsen KhademView profile

Professor

• Robotics
• Computer Vision
• Machine Learning
• +5 more

Mohsen Khadem serves as a Reader in Robotics at the School of Informatics, University of Edinburgh, where he directs the Surgical and Interventional Robotics Group. He holds dual affiliations with the Institute for Perception, Action and Behaviour and the Center for Inflammation Research and the Institute of Regeneration and Repair. As a UKRI Future Leaders Fellow, his work bridges engineering and clinical medicine through the development of advanced robotic systems for surgical interventions. His research focuses on continuum robotics with primary applications in surgical and interventional robotics. Key areas include surgical robotics and image-guided therapies, computer vision and medical image processing, mechanics-based modeling and simulation, and applications of control theory in robotics. Khadem's approach emphasizes solving clinical problems first, working closely with surgeons to develop appropriate robotic solutions, whether new hardware designs or novel algorithms. His recent publications demonstrate a strong trajectory toward medical robotics applications, particularly in bronchoscopy navigation and surgical skill assessment. The work combines computer vision techniques with robotic control systems to address clinical challenges in minimally invasive procedures, showing increasing sophistication in both image processing and robotic manipulation capabilities. UKRI Future Leaders Fellow Khadem actively supervises multiple PhD students including Balint Thamo (focusing on concentric tube robots), Emile Makute (specializing in machine learning for continuum robots), Alex Adams (working on spectroscopy for cancer diagnosis), and Zhaoxing Deng (researching surgical skill assessment). His major projects include leading the Cyber-Physical System for Unified Diagnosis and Treatment of Lung Diseases and participating in the EPSRC-funded MicroTex research hub. Based at the Bayes Centre and IRR South facilities, Khadem's Surgical and Interventional Robotics Group operates as a cross-institutional research team with strong connections to clinical partners. The lab focuses on developing therapeutic and diagnostic robotic instruments through close collaboration with surgeons and clinicians to identify optimal solutions for specific medical challenges.

• Artificial Intelligence
• Data Science
• Computer Vision
• +6 more

Niklas Beuter is a Professor of Artificial Intelligence and Data Science at TH Lübeck, Germany, within the Department of Electrical Engineering and Computer Science. He has been in this position since 2023, contributing to both research and education in AI and computer vision. His educational background includes a Diplom in Computer Science with a focus on robotics from Universität Bielefeld, completed with distinction, followed by a Ph.D. from the same institution in 2011. His doctoral research centered on 3D human detection and tracking for mobile robotic platforms, supporting situation awareness in dynamic environments. Beuter's research is deeply rooted in artificial intelligence, computer vision, and robotics , with a focus on dynamic 3D scene analysis, human-robot interaction, and autonomous systems . His work bridges theoretical models with real-world applications, particularly in autonomous driving and intelligent robotic perception. He has led research teams in industry, demonstrating strong leadership in applied AI. The trend in his publications reflects a consistent focus on perception systems for robots and vehicles , evolving from foundational work in 3D reconstruction and gesture-based interaction to advanced topics like pedestrian intent forecasting using deep learning. His contributions span top conferences such as IEEE ICRA, CVPR, and Intelligent Vehicles, indicating sustained engagement with the core AI and robotics communities. While no formal scientific awards are listed in the provided text, his leadership roles and publication record reflect significant professional recognition. He actively supervises student theses and invites students to register for thesis topics via email, indicating an ongoing commitment to mentoring. Although no specific grants are mentioned, his industrial and academic research leadership suggests involvement in funded projects. He is a member of research groups including CoSA and serves as Deputy Head of ISy, showing active participation in institutional research organization. His research has been conducted in collaboration with teams at Universität Bielefeld, Daimler Research Center, and Robert Bosch GmbH, reflecting a strong interdisciplinary and industry-academia network. His work continues to influence both academic research and industrial applications in AI and autonomous systems.

• Computer Vision
• Artificial Intelligence
• Robotics
• +7 more

Christopher McCarthy is an Associate Professor in the Department of Computing Technologies within the School of Science, Computing and Emerging Technologies at Swinburne University of Technology. His research focuses on computer vision algorithms applied to robotics, intelligent transport systems, and assistive technologies, particularly for people with low vision. He serves as Stream Leader in Swinburne’s Innovative Planet Research Institute, leading the Intelligent Transport stream, and is a Chief Investigator in the Australian Cobotics Centre funded by the ARC. He has held research roles at CSIRO Data61, the Bionics Institute, and the University of Melbourne, contributing to bionic eye technology under the Bionic Vision Australia consortium. His research interests include: Computer Vision and AI for real-time systems Robot perception and navigation Assistive technologies for low-vision and blind users Intelligent transport systems and video analytics Human-machine interaction and cyber-human teams His recent publications reflect strong trends in deep learning, continual learning, and real-world deployment of vision systems in transport and healthcare. He has led numerous field trials and evaluations to assess system performance in real-world contexts. His work is highly interdisciplinary, combining computer science with engineering, medicine, and urban planning. Christopher McCarthy has received multiple awards, including: FSET Research Collaboration Award Excellence in Industry Engagement Special Commendation – VC Research Impact Finalist – National Disability Award in Technology Best Paper Award (IEEE) Excellence in Teaching (University of Melbourne) He has supervised over 20 HDR students in areas including robotics, AI, assistive tech, and transport analytics. He has led major research grants from ARC, Defence, SmartCrete CRC, iMOVE, and city councils. He also served as Academic Director for Work-Integrated Learning (2016–2023) and coordinated professional placements. His teaching includes core computer science units such as Computer Systems and Object-Oriented Programming. He maintains ongoing affiliations with: Bionics Institute (Honorary Member) Bionic Vision Australia (Affiliate) Data61 (Honorary Member) Royal Children's Hospital, Melbourne International Task Force for Vision Restoration Outcomes (Chair)

• Artificial Intelligence
• Machine Learning
• Artificial Neural Networks
• +19 more

Professor Stephan Chalup is a leading academic in Artificial Intelligence and Machine Learning at the University of Newcastle , affiliated with the School of Information and Physical Sciences and the Data Science and Statistics department. He leads the Interdisciplinary Machine Learning Research Group (IMLRG) and the Newcastle Robotics Lab , where his team has achieved global recognition, including two RoboCup world championships. PhD in Computing Science , Queensland University of Technology (2002) Diplom in Mathematics with Neuroscience , University of Heidelberg His research focuses on artificial neural networks , deep learning , and high-dimensional data analysis , with applications in robotics, computer vision, medical imaging, and architectural analysis. He investigates how biological neural systems inspire robust AI models, particularly in topological data analysis and 4D vision . The recent publications highlight a strong trend in topological and geometric machine learning , with a focus on 4D data analysis , multi-agent reinforcement learning , and robot perception . His work bridges theoretical AI with practical industry solutions in transport, healthcare, and robotics. RoboCup World Champion (2008, 2006) Leadership Excellence, CESE (2024) Supervision Research Excellence Award (2015) Multiple Best Student Paper Awards (2019, 2018, 2011) Chalup has supervised numerous students and led significant research projects, including the ARC Discovery Project on estimating topology of low-dimensional data. His lab fosters interdisciplinary collaboration and innovation, with alumni working in top global tech roles. He is an active keynote speaker and program committee member in major AI conferences. His labs, including the Newcastle Robotics Lab , are equipped with state-of-the-art robots and computing systems, supporting cutting-edge research in humanoid robotics, autonomous navigation, and AI-driven data analysis.

William SmithView profile

Professor

• Computer Vision
• Computer Graphics
• Machine Learning
• +15 more

William Smith is a Professor in the Department of Computer Science at the University of York, where he leads the Vision, Graphics and Learning (VGL) research group. He holds a BSc and PhD in Computer Science from the University of York, completed in 2002 and 2007 respectively. He has served in key roles including Director of Admissions, PGT AI Programme Lead, and Research Group Lead. He is an Associate Editor for the journal Pattern Recognition and was a Royal Academy of Engineering/The Leverhulme Trust Senior Research Fellow from 2019 to 2020. Education: BSc in Computer Science, University of York, 2002 PhD in Computer Vision, University of York, 2007 His research lies at the intersection of computer vision, computer graphics, and machine learning. He focuses on physics-based and 3D vision, shape and appearance modeling, and the application of statistical and machine learning methods. Key application areas include face and body analysis, surveying and mapping, object capture, and inverse rendering. His work leverages advanced mathematical tools such as convex and nonlinear optimization, manifold learning, computational geometry, and low-level vision techniques. His recent publications, spanning top venues like ECCV, NeurIPS, WACV, and IEEE T-PAMI, reflect a strong trend in neural scene representation, inverse rendering, and illumination modeling. Themes include relighting outdoor scenes, self-supervised pose estimation, spherical neural fields, and orientation-aware deep learning for omnidirectional inputs. These works demonstrate a consistent focus on integrating physical models with deep learning for robust and interpretable vision systems. Scientific Awards: Royal Academy of Engineering/The Leverhulme Trust Senior Research Fellow (2019–2020) William Smith supervises a team of nine PhD students and has advised several alumni who have gone on to research and industry roles. He has served in significant service roles including Area Chair for ICCV, CVPR, and 3DV, Programme Chair for BMVC 2020, General Chair for CVMP 2019, and reviewer for major conferences since 2008. He is actively involved in the academic community and continues to contribute to cutting-edge research through his leadership in the VGL group at York. The Vision, Graphics and Learning (VGL) group, which he leads, conducts research in computer vision, graphics, and machine learning, with projects such as Branching Out (historic tree mapping), Senior Research Fellowship (model-based vision meets deep learning), Google Daydream (VR/AR head modeling), and LEAPP (polar archival photography). The group fosters a collaborative environment with both current and former members contributing to impactful research.

Hubert JobView profile

Professor

• Protected Area Management
• Spatial Planning
• Regional Development
• +7 more

Univ.-Prof. Dr. Hubert Job is a Senior Professor of Geography and Regional Research at the Institute of Geography and Geology, Faculty of Philosophy, University of Würzburg. His work bridges spatial planning, regional development, and environmental economics with regional focus on Central Europe, the Alps, and Africa. Research Interests : Protected area management, ecological connectivity, sustainable tourism economics, socio-economic impact analysis, cultural landscape preservation, and transnational spatial governance. Projects : Leads PlanToConnect (€301,000 sub-budget) for ecological corridor integration in Alpine spatial systems, contributes to multi-regional input-output analyses (DBU-funded), and evaluates nature tourism impacts in Lüneburger Heide, Wadden Sea, and Bavarian Forest National Parks. Awards : Recipient of the Austrian Geographical Society's Hans Bobek-Preis (2000) for exceptional contributions to geographical research. Collaborations : Chairs ARL European Working Group AlpPlan, collaborates with institutions across Sweden, Mexico, Tanzania, and Italy, and integrates UNESCO MAB frameworks into Alpine conservation.

Tracy L. Kijewski-CorreaView profile

Professor

• Civil Infrastructure Engineering
• Natural Hazard Assessment
• Disaster Mitigation
• +5 more

Tracy L. Kijewski-Correa is the William J. Pulte Director of the Pulte Institute for Global Development and Academic Director of the Integration Lab (i-Lab) at the University of Notre Dame's Keough School of Global Affairs. She holds a joint appointment as Professor of Civil Engineering and Global Affairs in the Department of Civil and Environmental Engineering & Earth Sciences. Her research focuses on civil infrastructure challenges in both developed and developing contexts, with particular emphasis on natural hazard assessment and mitigation. A co-founder of Engineering2Empower (E2E), she has developed comprehensive strategies for sustainable housing in Haiti, integrating community-led innovation and market-based solutions. Her work spans multiple regions including Haiti, United States, Latin America, Middle East, South Asia, and South Pacific/Oceania. Kijewski-Correa's recent publications demonstrate a clear trend toward leveraging open data and computational approaches for high-fidelity regional loss estimations, particularly for hurricane risk assessment. Her work increasingly integrates computer vision, Bayesian data integration, and component-level fragility modeling to advance the precision of disaster impact predictions while maintaining computational tractability across large building portfolios. Kellogg Institute Faculty Fellow (since 2011) Her research has been supported by multiple grants including projects focused on climate adaptation in Bangladesh and Haiti, community-driven development in Haiti, post-disaster sheltering programs, and technology incubators for sustainable development. As director of the Pulte Institute and Academic Director of the i-Lab, she leads interdisciplinary teams working at the intersection of engineering, global development, and disaster resilience.

• Computer Vision
• Mobile Devices
• Assistive Technology
• +3 more

Dr. Juan Manuel Sáez Martínez is a full professor in the Department of Computer Science and Artificial Intelligence at the University of Alicante's Higher Polytechnic School II. With a PhD in Computer Engineering and over two decades of academic experience since 2000, he specializes in Computer Vision and Mobile Device Applications for accessibility, particularly for the blind and visually impaired. His groundbreaking NaviLens project—a digital signage system patented internationally by the University of Alicante and licensed to Neosistec SL—represents a significant contribution to assistive technology. Teaching experience across 15+ years in programming fundamentals, computer systems, and internships for telecommunications and multimedia engineering Supervised one PhD thesis on structural similarity in object recognition Active in public research projects including airport navigation systems and airborne obstacle detection for the visually impaired His research interests focus on computer vision algorithms , stereo-based wearable devices , and ultra-efficient artificial vision systems for mobile platforms . Recent work includes biomedical informatics applications like 3D obstacle detection and accessibility-oriented UI design. He has participated in 10+ competitive public research projects (2016-2021) while contributing to technology transfer initiatives. Teaching contributions include 4 quinquennials (five-year terms) and 14+ years of instruction in Programming Fundamentals I for Telecommunication Sound and Image Engineering. Notable collaborations include co-authorship with Dr. F. Escolano on entropy-based SLAM algorithms and Gaussian mixture models for image processing. Current research emphasizes practical applications through the Mobile Vision Research Laboratory (MVRLab) .