جستجوی استاد راهنمای دانشگاهی

Pierre Klinteforsمشاهده پروفایل

پژوهشگر

• Cognitive Science
• Computational Neuroscience
• Robotics
• +۴ مورد دیگر

Pierre Klintefors is a Researcher at the Department of Philosophy, Lund University, affiliated with the Joint Faculties of Humanities and Theology. His work bridges theoretical neuroscience, cognitive science, and robotics. Room: LUX:B476 Visiting Address: Helgonavägen 3, Lund Email: pierre.klintefors@lucs.lu.se Research Focus: Pierre investigates computational aspects of the body schema —an agent’s internal representation of its body. He employs frameworks like predictive processing and active inference , which hypothesize that the brain minimizes sensory prediction errors via hierarchical Bayesian inference. His models are implemented on humanoid platforms to explore embodied robotics and theoretical neuroscience . Publications: His work spans robotics , Bayesian statistics in psychology, and pattern processing in social cognition. Current projects include his dissertation on Action-Oriented Body Perception (2023–2027), and participation in public robotics events like Robotveckan 2024 . Contact: Mobile: +46 70 942 84 58 | Postal Address: Box 192, 221 00 Lund | Internal Post Code: 30

• Cognitive Science
• Human-Computer Interaction
• Robotics
• +۴ مورد دیگر

Paul Hemeren is an Associate Professor of Informatics at the University of Skövde , specializing in biological motion perception and human-robot interaction. His research spans cognitive science, artificial intelligence, and transportation safety, with emphasis on understanding how humans perceive actions and intentions in dynamic environments. Academic Background : Ph.D. in Cognitive Science (Lund University, 2008), B.A. from Hope College (USA) Current Research : Focuses on action representation, driver-cyclist interaction modeling, and multimodal perception systems Applied Projects : Developing intelligent driver support systems (I2Connect) and predictive collision detection models Methodologies : Combines experimental psychology with machine learning and computational modeling Recent publications examine kinematic primitives in action similarity judgments, attentional synchrony in films, and data-driven collision prediction models. His work bridges theoretical cognitive science with practical implementations for traffic safety and robotic systems, particularly through collaborations with Swedish research foundations and European robotics initiatives. Professional affiliations include membership in the Cognitive Science Society and European Network for Artificial Cognitive Systems. Research has been funded by Swedish insurance research funds and EU Horizon programs.

• Production Engineering
• Industrial Automation
• Digital Twins
• +۳ مورد دیگر

Dr. Anna Syberfeldt is a Professor in Production Engineering at the Department of Engineering Science, University of Skövde. She leads the Virtual Production Development research group and serves as research director at the ASSAR Industrial Innovation Arena. With a background in computer science from De Montfort University and habilitation in automation engineering, her work bridges AI, robotics, and immersive technologies with industrial production systems. Professor in Production Technology Research Director at ASSAR Industrial Innovation Arena University of Skövde Affiliation Her research focuses on developing innovative industrial solutions through: Artificial Intelligence and Machine Learning Collaborative Robotics and Human-Robot Interaction Digital Twins and Simulation-Based Optimization Augmented/Virtual/Mixed Reality Applications Smart Manufacturing and Industry 4.0 Worker Well-Being and Productivity Optimization Recent publications demonstrate her leadership in simulation-based optimization, collaborative robotics, and mixed reality applications in manufacturing. Her work emphasizes creating ultra-flexible production systems through cyber-physical approaches while prioritizing environmental sustainability and human-centric design. Key trends in her research include: Unified frameworks for virtual commissioning Knowledge graph applications in production systems Multi-objective optimization balancing productivity and ergonomics Smart glasses evaluation for industrial operators Evolutionary algorithms for complex manufacturing problems Her projects demonstrate practical implementations of: MAXLabs distributed cyber-physical testbed ERAIVA posture identification software Virtual environments for human-robot collaboration testing Digital support functions for factory layout planning

• Robotics
• Precision Agriculture
• Computer Vision
• +۵ مورد دیگر

Stefan Ericson is a Senior Lecturer and Division Head at the School of Engineering Science, University of Skövde. His research focuses on robotics, computer vision, and precision agriculture, particularly in autonomous navigation systems for agricultural robots and industrial applications. Education: Doctoral thesis on Vision-Based Perception for Localization of Autonomous Agricultural Robots (2017). Research Interests: Visual odometry, digital twins, deep learning for manufacturing, and AI in precision agriculture. Projects: Currently involved in Port Microgrid (optimizing port energy systems), Helios Energy Hub (smart energy management), and Next Generation Laboratory Environment (electric drivetrain production). His recent articles emphasize deep learning for welding analysis, digital twins in production lines, and visual odometry for uneven terrain and agricultural environments. He teaches courses at both bachelor's and master's levels, including topics in robotics and engineering.

Magnus Johnssonمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Cognitive Science
• +۷ مورد دیگر

Magnus Johnsson is a Professor of Computer Science at the Department of Computer Science, Kristianstad University, within the Faculty of Natural Science. He also holds positions as Leader of the Research Environment of Computer Science (RECS) and Deputy Dean (2024–2025). Previously, he served as Associate Professor at Malmö University (2018–2024) and held roles at Lund University, Moscow Engineering Physics Institute, and others. Education includes a PhD in Cognitive Science (2009), MSc and BSc in Computer Science (2004/2003), and MA in Cognitive Science (2004), all from Lund University. He has pedagogical qualifications in PhD supervision and university teaching. Research focuses on artificial intelligence, cognitive robotics, computational neuroscience, and philosophy of mind. Key areas include self-organizing neural networks (e.g., Associative SOM), action recognition, and AI applications in medicine/robotics. He pioneered tactile perception models for robots and developed systems like the LUCS Haptic Hand series. Awards include multiple BICA Society accolades (2018–2019) and active roles in editorial boards and professional societies like Swedish AI Society (SAIS). His work bridges cognitive science, engineering, and philosophy, with over 50 publications and grants in AI, robotics, and medical diagnostics. Leadership includes directing research environments and serving on academic boards. Collaborations span international institutions, and his entrepreneurial ventures include Magnus Johnsson AI Research AB (2017–).

• Neurophysiology
• Motor Control
• Sensory Neuroscience
• +۳ مورد دیگر

Benoni Edin is a Professor at the Department of Diagnostics and Intervention and the Faculty Office of Medicine at Umeå universitet. His research focuses on understanding the neuronal control mechanisms underlying human manual manipulation, including sensory integration, motor planning, and tactile feedback. He leads a research group exploring sensorimotor control across multiple levels from peripheral sensory receptors to brain mechanisms. Key themes include the role of tactile feedback in prosthetics, biomechanics of grasping, and neural adaptation in manipulation tasks. His work bridges basic neuroscience with clinical and technological applications in robotics and rehabilitation. Recent studies involve high-resolution imaging of skin deformation, force estimation from fingernail images, and vibrotactile feedback systems for amputees. Edin holds a Docent title and has contributed to over 70 peer-reviewed publications since 1987. Research activities emphasize interdisciplinary approaches combining microneurography, EEG, brain imaging, and robotic systems. His group investigates how sensory information (tactile, visual, auditory) is integrated for action planning, with implications for developing intelligent prosthetics and improving medical assessment protocols. The lab collaborates on projects like sensory feedback for hand prostheses and predictive models of biting behavior. Edin’s work has been applied to enhance prosthetic control algorithms and refine national medical licensing tests for international graduates. Current projects include context-dependent adaptations in biting behaviors and sensory information processing in motor control. His research has been supported by grants focusing on neurorehabilitation technologies and human-machine interfaces. The lab actively engages in translating fundamental neuroscience discoveries into clinical tools and assistive devices.

• Artificial Intelligence
• Robotics
• Human-Computer Interaction
• +۳ مورد دیگر

William Ahlberg is a Doctoral student and Researcher at Kungliga Tekniska Högskolan (KTH), affiliated with the Division of Robotics, Perception and Learning. His research focuses on integrating human feedback into autonomous agent development, particularly in creating believable non-player characters (NPCs) for video games through advanced machine learning techniques. He explores algorithms that align human feedback with computational models using active and preference learning extensions, alongside novel interaction modalities for feedback collection. Education details: Doctoral student at KTH's Division of Robotics, Perception and Learning. Research interests emphasize multi-modal adversarial imitation learning, playstyle generation, and human-in-the-loop systems. His recent articles (2023-2025) highlight trends in game AI, NPC behavior modeling, and generative adversarial networks applied to interactive agent training. No scientific awards are listed. He has no recorded advisees or grants in the provided data. His work is primarily conducted within the Robotics, Perception and Learning division at KTH.

• Human-Robot Interaction
• Social Robotics
• Autonomous Systems
• +۳ مورد دیگر

Iolanda Leite is an Associate Professor at the Division of Robotics, Perception and Learning at KTH Royal Institute of Technology. She holds a PhD from the Technical University of Lisbon and has held postdoctoral positions at Yale Social Robotics Lab and Disney Research. Her research focuses on developing robots capable of understanding and responding to human social dynamics, emphasizing trust, interaction efficiency, and ethical considerations in human-robot collaboration. She has led or co-led numerous research projects funded by institutions such as the Wallenberg AI, Autonomous Systems and Software Program (WASP), NordForsk, and the Swedish Foundation for Strategic Research. Her work spans socially acceptable autonomy, interactive learning, and human-robot teaming, with a particular interest in ethical implications and inclusive design. Leite has been recognized with multiple awards, including the Best Paper Award at ACM/IEEE HRI 2023 and the Jacobs Foundation Early Career Fellowship 2018. She actively contributes to the academic community as Co-Editor-in-Chief of the ACM Transactions on Human-Robot Interaction and has organized major conferences like HRI 2023 and IROS 2023. In teaching, she oversees degree projects in computer science, electrical engineering, and robotics at both undergraduate and graduate levels, emphasizing practical and theoretical foundations in AI and robotics.

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

Atsuto Maki is a Professor of Computer Science at KTH Royal Institute of Technology, affiliated with the School of Electrical Engineering and Computer Science and the Division of Robotics, Perception and Learning. He holds a PhD from KTH and an MEng from the University of Tokyo. Previously, he served as an associate professor at Kyoto University and worked in industry for over a decade at Toshiba Research Cambridge Lab and Toshiba Corporate R&D, focusing on computer vision systems like radar image analysis. His research spans machine learning, deep learning, and computer vision, including motion/object recognition, clustering, subspace analysis, and representation learning. He teaches Machine Learning (DD2421) and co-chairs the Master’s Programme in Machine Learning. Maki has over 30 patents in image analysis and is a board member of the Swedish Society for Automated Image Analysis. Recent projects include grants like 'SeDECI' (semi-supervised learning with imbalanced data) and collaborations with NII, RIKEN AIP, and the University of Tokyo. He actively organizes conferences (e.g., ECCV 2026) and workshops, and holds leadership roles in academic partnerships. Key awards include the Niwa-Takayanagi Best Paper Prize (2018). His work emphasizes practical applications in manufacturing, medical imaging, and autonomous systems, reflected in papers on synthetic data for quality inspection, sonar beamforming, and deep learning regularization techniques.

• Topology Optimization
• Computational Mechanics
• Acoustics
• +۳ مورد دیگر

Eddie Wadbro is a Visiting Professor at the Department of Computing Science , Umeå University. His research spans computational mechanics, acoustics, and machine learning, focusing on topology optimization and its applications in industrial design, forestry, and electromagnetics. He actively collaborates across disciplines to solve complex engineering challenges. Key Research Areas: Topology optimization, acoustic wave control, machine learning for industrial systems, fluid dynamics Recent Trends: Alzheimer's disease classification via morphological analysis, deep reinforcement learning for autonomous machinery, multiscale material design Collaborations: Works with experts in forestry engineering, electromagnetics, and biomedical imaging.

Ola Ringdahlمشاهده پروفایل

دانشیار

• Robotics
• Artificial Intelligence
• Machine Learning
• +۶ مورد دیگر

Ola Ringdahl is an Associate Professor at the Department of Computer Science, Umeå University, specializing in robotics for agriculture and forestry. He serves as the Director of the MSc program in AI and teaches multiple courses. Research Group: Intelligent Robotics Affiliation: Umeå University, Department of Computer Science His research focuses on developing novel artificial intelligence and machine learning algorithms for autonomous and semi-autonomous robotic navigation, industrial manipulator path planning using 3D localization, and perception algorithms for semantic data extraction from sensors. Projects include EU initiatives Sweeper and CROPS for fruit harvesting robots. Publications highlight applications in precision agriculture/forestry and sensor fusion. Recent publications analyze advancements in agricultural robotics using machine learning, human-robot interaction via multi-camera systems, and grape vine detection with RGB-D data. The majority of his work addresses outdoor environments and sensor-driven decision-making in autonomous systems. Key Collaborators: Polina Kurtser, Thomas Hellström, Yael Edan Ola leads the Intelligent Robotics group and has participated in long-term projects like PRECISION (2018-2021), SOCRATES (2016-2020), Sweeper (2015-2018), and CROPS (2010-2014). His work combines academic research with practical implementation in real-world agricultural and forestry settings.

Michael Sandborgمشاهده پروفایل

استاد مدعو

• Medical Imaging Science
• Radiation Physics
• Optimization of Imaging Techniques
• +۳ مورد دیگر

Michael Sandborg is a radiation physicist at Linköping University Hospital and an Adjunct Professor at the Faculty of Medicine , Linköping University . He leads research on optimizing medical imaging techniques through the Center for Medical Imaging and Visualization (CMIV) and the Radiological Sciences Unit within the Department of Diagnostics and Specialist Medicine . His research focuses on: Medical imaging dose optimization Photon-counting detector CT evaluation Radiation therapy quantitative CT Quality assurance protocols Brachytherapy planning algorithms Recent publications analyze dual-energy CT accuracy, radiation safety in interventional procedures, and automated imaging systems. He supervises doctoral students and clinical staff while teaching radiation physics to medical and engineering students. Key collaborations include: CMIV interdisciplinary center EFOMP radiation standards development Östergötland Region healthcare partnerships

• Robot Learning
• Computer Vision
• Autonomous Systems
• +۲ مورد دیگر

Dr. Renaud Detry is Associate Professor of Robot Learning at KU Leuven with dual appointments in Electrical and Mechanical Engineering. His research develops learning algorithms for robotic perception and manipulation in challenging environments including construction, healthcare, and space operations. Current projects address uncertainty-aware learning systems, robotic sand grading, multi-task policy training, and trajectory prediction for shared control. Applications range from terrestrial construction automation to NASA's Mars Sample Return mission, where he served as machine-vision lead. As associate editor for IEEE Transactions on Robotics and conference organizer for ICRA/IROS, he advances robotic learning methodologies. Received best presentation award at ECCV 2022 for spacecraft pose estimation research.

Gabriel Skantzeمشاهده پروفایل

استاد

• Speech Communication
• Conversational Systems
• Human-Robot Interaction
• +۵ مورد دیگر

Professor Gabriel Skantze is a faculty member at KTH Royal Institute of Technology in Stockholm, Sweden, affiliated with the Department of Speech Music and Hearing within the School of Computer Science and Communication. His research focuses on conversational systems, human-robot interaction (HRI), and multimodal dialogue technologies. He co-founded Furhat Robotics in 2014 and currently holds a part-time role as Chief Scientist there, while maintaining his full-time academic position. Skantze earned his MSc in Cognitive Science from Linköping University and his PhD in Speech Communication from KTH in 2007. His work integrates interdisciplinary approaches from linguistics, phonetics, and artificial intelligence to develop socially intelligent robots capable of natural face-to-face interaction with humans. Research interests include turn-taking prediction, feedback modeling in HRI, and visual grounding in dialogue. He has supervised numerous PhD students, including ongoing advisees such as Nikita Torgashov and Bram Willemsen, and past students like Carol Figueroa and Chinmaya Mishra. His awards include Best Paper recognitions at HRI 2025 and SIGDIAL 2022. Skantze serves as President Emeritus of SIGdial (ACL) and on editorial boards for journals like Transactions on Human-Robot Interaction . Key projects explore robots as hosts on autonomous buses, virtual patients for medical training, and language learning companions. Funded by grants, his work bridges theoretical research with practical applications in healthcare, education, and robotics. Collaborations with Furhat Robotics and academic institutions worldwide highlight his commitment to advancing socially aware AI systems.

• Autonomy of robots and vehicles
• Motion planning
• Optimal motion control
• +۶ مورد دیگر

Björn Olofsson is an Associate Professor and Senior Lecturer in the Department of Automatic Control at Lund University's Faculty of Engineering. He also serves as the Director of First and Second Cycle Studies and is a Project Manager. He is affiliated with major research initiatives including ELLIIT (the Linköping-Lund initiative on IT and mobile communication) and WASP (Wallenberg AI, Autonomous Systems and Software Program). His academic affiliations span Lund University and Linköping University, where he was appointed Docent in 2020. He holds an M.Sc. in Engineering Physics and a Ph.D. in Automatic Control, both from Lund University. His academic journey reflects a strong foundation in engineering and control systems. His research focuses on the autonomy of robots and vehicles, with emphasis on motion planning and optimal motion control. He explores applications in ground vehicles, unmanned aerial and surface vehicles, and industrial robotics. His work intersects with key global challenges, including sustainable transport and digitalization, aligning with UN Sustainable Development Goals related to technology and health. The 15 most recent publications analyzed show a consistent trend in autonomous systems, predictive control, and robotics. Topics include uncertainty-aware motion planning, human-robot collaboration, maritime autonomy, and learning-based control. The research integrates AI, machine learning, and advanced control theory, applied across aerial, marine, and terrestrial domains. Björn actively supervises multiple PhD students and has led numerous research projects, such as ELLIIT B14 and the Center for Construction Robotics. He is involved in organizing academic events like Robotics Week for Schools and manages the RobotLab LTH infrastructure. He has taught a range of courses including Applied Robotics, Autonomous Vehicles, and graduate-level courses on motion planning and optimal control. He also supervises Master’s theses in Automatic Control and Vehicular Systems.