جستجوی استاد راهنمای دانشگاهی

Tønnes Nygaard is an Associate Professor at the Department of Technology Systems, University of Oslo, affiliated with the Faculty of Mathematics and Natural Sciences. His research focuses on evolutionary robotics, morphological adaptation, and embodied artificial intelligence. He leads projects like COCOMO (Co-evolution of Control and Morphologies) and works extensively with the DyRET (Dynamic Robot for Embodied Testing) platform. Key research interests include robot control systems, adaptive morphology design, and real-world implementation of evolutionary algorithms. His work bridges theoretical computer science with practical robotics applications, emphasizing hardware-software co-evolution and embodied cognition principles. Publications span topics like morphological adaptation in quadruped robots, semi-supervised learning for terrain classification, and overcoming convergence issues in multi-objective evolutionary algorithms. Nygaard collaborates internationally and contributes to both academic journals and conferences in robotics and AI. No scientific awards are explicitly listed, though his impactful contributions to real-world evolutionary robotics suggest potential recognition pending explicit mentions. Advising and grant activities are central to his role, though specific student names or grant amounts are not detailed in the provided texts. Labs/Teams: Core contributor to the DyRET project and affiliated with the Section for Autonomous Systems and Sensor Technologies at UiO.

• Robotics
• Evolutionary Algorithms
• Morphological Adaptation
• +۳ مورد دیگر

Stefano Nichele is a Professor at the Department of Computer Science and Communication, Østfold University College, Norway. He holds additional roles as Professor II at OsloMet and has served in leading academic positions since 2014. His research focuses on Artificial Life (ALife), Neuro-Inspired AI, and Machine Learning, with a particular emphasis on cellular automata, reservoir computing, and neuro-inspired substrates. Nichele co-directs the Østfold AI (ØAI) hub and is an active member of IEEE, ELLIS, and the Norwegian AI Research Consortium (NORA). He earned his PhD in Computer Science from NTNU (2015) and completed his MSc at the University of Insubria, Italy. His work bridges computational systems and biological substrates, exploring criticality in neural networks and quantum-evolutionary algorithm interactions. He has received prestigious awards, including the Young Research Talent grant (2019) and the Distinguished Early-Career Investigator award (2024). Nichele’s research spans theoretical and applied domains, with over 50 publications on cellular automata dynamics, neuro-inspired robotics, and AI ethics. His recent projects include studying in vitro neural networks for computational capacity assessment and developing frameworks for body-brain co-evolution in soft robotics. Education: PhD in Computer Science, NTNU (2015) MSc in Computer Science, University of Insubria (2009) Awards: Young Research Talent grant (2019) Distinguished Early-Career Investigator (2024) Grants & Roles: Co-director of the Østfold AI hub Board member of NORA (Norwegian AI Research Consortium) Labs & Collaborations: Focus on neuro-inspired AI systems and unconventional computing Partnerships with institutions like Simula Metropolitan and the International Society for Artificial Life (ISAL)

• Artificial Life
• Neuro-Inspired Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر

Kristian Muri Knausgård is a Lecturer at the Department of Engineering Sciences , University of Agder , Norway. He teaches courses in embedded systems, software development, and robotics. Current courses: MAS245 (Embedded Computer Systems), MAS417 (Software Development), MAS418 (Robotics Programming) Previous courses: MAS218 (Electrical Circuits), MAS234 (Embedded Systems) His research focuses on embedded systems , real-time systems , and technical cybernetics , with applications in artificial intelligence , computer vision , and systems engineering . He contributes to the university's research groups on Robotics and Automation and Systems Engineering and Modeling . Recent publications show a strong emphasis on: Autonomous systems (robotics, docking algorithms) Deep learning applications in marine ecology 3D reconstruction and computer vision techniques Fish detection/classification using neural networks Industrial automation for aquaponic systems His work bridges theoretical research with practical implementations in mechatronic systems and environmental monitoring.

• Embedded computer systems
• Real-time systems
• Technical cybernetics
• +۵ مورد دیگر

Sidney Pontes-Filho is a Postdoctoral Fellow at Simula Research Laboratory in Oslo, Norway, with a strong academic affiliation to the Norwegian University of Science and Technology (NTNU) where he completed his PhD in Computer Science. His primary departmental affiliation is with the Department of Computer Science at Oslo Metropolitan University (OsloMet). His research spans multiple institutions including Simula Research Laboratory where he works in the Numerical Analysis and Scientific Computing department. His educational background includes a B.Sc. in Computer Science from Federal University of Paraíba, Brazil (2013), an M.Sc. in Computer Science from Technical University of Kaiserslautern, Germany (2018), and a Ph.D. in Computer Science from NTNU. His research focuses on the intersection of complex systems, unconventional computing, computational neuroscience, and artificial general intelligence, with particular emphasis on neural cellular automata and criticality phenomena. Pontes-Filho's publication record reveals a consistent trajectory in exploring how critical systems can serve as substrates for intelligent behavior. His work demonstrates how neural cellular automata operating near critical points exhibit emergent properties relevant to artificial intelligence, including attention mechanisms, scalability, and robust control systems. His research spans theoretical frameworks like EvoDynamic, practical applications in soft robotics control, and medical imaging tools for brain extraction from fMRI data. His scientific contributions show an interdisciplinary approach merging concepts from statistical physics, neuroscience, and computer science to develop novel computational paradigms. The evolution of his work demonstrates increasing sophistication in connecting theoretical criticality concepts with practical AI applications, particularly in embodied systems and neuromorphic computing.

• Complex Systems
• Unconventional Computing
• Computational Neuroscience
• +۳ مورد دیگر

Vasileios Gkioulos is a Professor at the Department of Information Security and Communication Technology, Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology (NTNU). His research focuses on cybersecurity for critical infrastructures, particularly in maritime and energy systems, with significant contributions to digital twins, threat modeling, and security policy frameworks. His work includes developing cybersecurity training programs, analyzing maritime navigation system vulnerabilities, and integrating safety-security co-engineering methodologies. He leads the Critical Infrastructure Security and Resilience group and has published extensively on topics like cyber-physical ranges, secure autonomous ship architectures, and wireless security testbeds. Recent articles explore digital twin applications for threat modeling, DevSecOps in critical infrastructure risk management, and modular maritime cybersecurity training. His research also addresses social robots in public spaces, emphasizing business-system-security interdependencies and privacy protection. Professor Gkioulos collaborates with institutions globally, co-authoring publications with researchers like Sokratis Katsikas, Habtamu Abie, and Sandeep Pirbhulal. His work spans journals such as International Journal of Information Security , Journal of Marine Science and Engineering , and Computers & Security , alongside conference proceedings and technical reports.

• Cybersecurity
• Critical Infrastructure Security
• Cyber-Physical Systems Security
• +۴ مورد دیگر

Mats Erling Høvin is an Associate Professor at the University of Oslo's Department of Informatics, affiliated with the Robotics and Intelligent Systems (ROBIN) research group. His academic work focuses on generative design, CAD/CAM systems, rapid prototyping, and evolutionary robotics. Previously, he conducted significant research in Delta-Sigma noise shaping for analog-to-digital converters. Research Interests: Generative design methodologies for manufacturing Computer-Aided Design (CAD) and Computer-Aided Manufacturing (CAM) systems Rapid prototyping and additive manufacturing techniques Evolutionary algorithms applied to robotics and optimization problems Delta-Sigma modulation for analog/digital signal conversion Robotic locomotion and control systems His publications demonstrate a consistent focus on optimization techniques applied to robotics, signal processing, and manufacturing systems. Recent work explores physics-based simulations for medical robotics and generative design for structural optimization. Earlier contributions established foundations in evolutionary robotics, motion capture filtering, and analog circuit design. Høvin teaches courses including IN5590 and IN1080, and leads research in the ROBIN group focusing on intelligent systems development. His work bridges theoretical computer science with practical engineering applications in robotics and manufacturing.

• Generative Design
• CAD
• CAM
• +۶ مورد دیگر

Jon Petter Omtvedt is a Professor at the Department of Chemistry, University of Oslo, specializing in nuclear chemistry and hydrometallurgy. He leads the Nuclear Chemistry Research Group and is engaged in teaching courses such as KJM 3900 Radioactivity and KJM 5912 Radiochemistry. His research focuses on chemical studies of super-heavy elements (SHEs), hydrometallurgical innovations, and detector technology development. He collaborates internationally with institutions like RIKEN (Japan), GSI (Germany), and SINTEF (Norway). Education: PhD in Nuclear Chemistry from the University of Oslo (1995). Active in advancing remote laboratory education through projects like RoboLab. Research Interests: Super-heavy element synthesis and chemical characterization, hydrometallurgical recovery of metals from waste, nuclear detector systems, and innovation in teaching methodologies. Specializes in liquid-liquid extraction techniques (e.g., SISAK system) for studying SHEs like flerovium (Fl) and hassium (Hs). Grants & Advising: Leads major projects on SHE chemical investigations and hydrometallurgy. Advises industry partners including Boliden and Glencore on metal recovery technologies. No explicit grant details provided in texts. Labs & Teams: Head of the Nuclear Chemistry Teaching Section at UiO. Key contributor to the ModulAr Robotic Gas-jet target (MARGE) system and Vacuum to Liquid Transfer Chamber (VLTC) for SHE research.

• Super-heavy Element Chemistry
• Hydrometallurgy
• Nuclear Chemistry
• +۳ مورد دیگر

Pedro Pablo Lucas Bravo is a Doctoral Research Fellow at the University of Oslo's Department of Informatics (IFI), affiliated with the RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion within the Faculty of Mathematics and Natural Sciences. His research focuses on developing interactive music systems using autonomous agents and swarm intelligence, with applications in Extended Reality (XR), Spatial Audio, and robotics. His Ph.D. project explores automatic tempo synchronization in human-machine systems through swarms of autonomous agents, aiming to create emergent musical behaviors in virtual, physical-virtual, and physical platforms. Key technologies include XR, spatial audio synthesis, motion capture, and robotic platforms. Bravo has contributed to projects like the XR Human-Swarm Interactive Music System and the MusicLab Copenhagen Dataset. His work bridges computer science, music technology, and artificial intelligence, with publications in venues such as IEEE ACSOS, NIME, and SMC. He holds a focus on interdisciplinary collaboration, leveraging swarmalator systems for self-organizing compositions and exploring cross-disciplinary applications of embodied oscillators in music performance.

• Music Technology
• Robotics
• Artificial Intelligence
• +۵ مورد دیگر

Kyrre Harald Glette is a Professor in the Department for Informatics at the University of Oslo , affiliated with the Robotics and Intelligent Systems Research Group and the RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion . His research focuses on the co-design of robot morphology and control using evolutionary and bio-inspired artificial intelligence methods. Research Interests: Robotics and Intelligent Systems Evolutionary Robotics and Co-Design of Morphology and Control Artificial Intelligence and Machine Learning Evolvable Hardware and Embodied Computation Computational Creativity and Music-AI Interaction Human-Robot Interaction and Swarm Robotics His recent publications (2023–2025) reflect a strong interdisciplinary trend, combining robotics, evolutionary computation, and music technology. Key themes include evolutionary design of modular robots , real-time adaptation in bio-inspired systems , interactive sonification , and AI-driven music generation . His work often involves the DyRET robotic platform, emphasizing real-world evolution and embodied learning. Scientific Contributions: Extensive publications in top venues like Frontiers in Robotics and AI , IEEE ICRA , GECCO , and Nature Machine Intelligence . Development of open-source robotic platforms and frameworks for evolutionary robotics. Interdisciplinary work bridging AI, neuroscience, and music. Advising and Projects: He supervises MSc students in evolutionary robotics, robot locomotion, and musical robot swarms. He is involved in several research projects including Predictive and Intuitive Robot Companion (PIRC) , Modeling and Robots , Multimodal Elderly Care Systems (MECS) , Musical Human-Machine Interaction , and Neurophysiological Mechanisms of Human Auditory Predictions (AudioPred) . Labs and Research Groups: He is a key member of the Robotics and Intelligent Systems (ROBIN) group, the RITMO Centre of Excellence , and the Creative Computing Hub Oslo (C2HO) . These groups support interdisciplinary research in AI, robotics, music, and human interaction.

• Robotics
• Artificial Intelligence
• Evolutionary Computing
• +۱۲ مورد دیگر

Prof. Konstantinos Alexis is a Professor in the Department of Engineering Cybernetics at the Norwegian University of Science and Technology (NTNU). His research focuses on resilient robotic autonomy, emphasizing robot control, path planning, and Simultaneous Localization and Mapping (SLAM). He leads major international grants from agencies like DARPA, NSF, and the Norwegian Research Council, advancing autonomous systems for extreme environments such as subterranean exploration and search-and-rescue operations. His work integrates advanced control strategies with field robotics, demonstrated through projects like the DARPA Subterranean Challenge. Key contributions include robust model predictive control for UAVs, contact-based inspection planning, and graph-based exploration path planning. Alexis has organized workshops on aerial robotics at top conferences like ICRA and ICUAS, and his team develops open-source tools for robotics autonomy. Award-winning publications include the IET 2014 Premium Award and multiple best-paper recognitions. His research extends to solar-powered UAVs, thermal-inertial localization, and multi-modal sensor fusion for degraded environments. The Autonomous Robots Lab at NTNU is central to his research activities.

• Robotics
• Resilient Robotic Autonomy
• Robot Control
• +۵ مورد دیگر

Houxiang Zhang is a Professor and Deputy Head of Department (Research) at the Department of Ocean Operations and Civil Engineering , Faculty of Engineering , Norwegian University of Science and Technology (NTNU) in Ålesund, Norway. He joined NTNU in 2011 and holds an industry-supported gift professorship (2011-2016). His research focuses on biological robots/modular robotics and virtual prototyping/marine mechatronics , with over 300 publications and 8 patents. Ph.D. in Mechanical and Electronic Engineering (2003) Habilitation in Informatics (2011) Research Interests include: Bio-inspired robotics and system design Marine automation and ship intelligence Digital twin technology and co-simulation Hybrid modeling approaches Artificial intelligence applications in maritime systems Scientific Awards and recognitions: Multiple IEEE best paper awards (2008, 2014, 2015, 2023, 2024) Finalist in IEEE Robotics and Automation conferences Dimitris N. Chorafas Award for outstanding PhD work Academy memberships: IEEE Senior (2012), NTVA (2019), DKNVS (2024) Advising and Research Leadership : Supervised 21 PhD/Master's students WP Leader for EU Horizon project RoboSAPIENS (2024-2026, 7.5M Euros) Key member in Norwegian Digital Ocean Space-Møre Ocean Lab (2023-2030, 30.7M NOK) Coordinated major SFI projects (2015-2022, 190M NOK each)

• Biological robots
• Modular robotics
• Marine automation
• +۵ مورد دیگر

Professor in the Department of Computing, Mathematics, and Physics at Western Norway University of Applied Sciences. Research bridges academia and industry through empirical studies on software modeling, requirements engineering, and software architecture. Current collaborations include Volvo, Ericsson, Saab, and Grundfos. Publications focus on marine data systems, sustainability in computing education, and industrial software engineering challenges. Research spans empirical software engineering with emphasis on industrial modeling applications, requirement engineering, and architecture design. Recent work explores marine data observability, sustainability education, and anomaly detection systems. Publications demonstrate consistent focus on practical software engineering solutions, with recent expansion into sustainable computing education and marine data systems. Trend shows increasing emphasis on environmental applications of computing technologies.

• Empirical Software Engineering
• Model-Driven Development
• Software Architecture
• +۲ مورد دیگر

Daniel Hagen is an Associate Professor at the Department of Engineering Sciences, University of Agder (UiA), Norway. He holds a Ph.D. in Engineering Sciences (2020), M.Sc. and B.Sc. in Mechatronics (2014 and 2012), and a Trade Certificate as Automation Mechanic (2009). His academic career is complemented by extensive industrial experience in roles such as Chief Scientist at Twilligent and Senior Technical Advisor at MotionTech, focusing on control systems, robotics, and energy-efficient mechatronics. Dr. Hagen's research interests include robotics, actuation systems, fluid power, and control systems. He leads projects in digital twins, autonomous robotics (e.g., UiAbot), and energy-efficient electro-hydraulic systems. His work emphasizes practical applications in offshore engineering and industrial automation. He teaches courses like Robotics and Instrumentation, Programming for Intelligent Robotics, and Mechatronic System Design. He is affiliated with research groups such as CAIR (Artificial Intelligence Research) and the Intelligent Mechatronics (iTron) group. Recent publications focus on real-time control systems, payload motion prediction, and digital twin frameworks for mechatronics. His research bridges academic innovation with industrial challenges, particularly in energy efficiency and autonomous systems.

• Robotics
• Modeling and Simulation
• Actuation Systems
• +۴ مورد دیگر

Karen Parish is an Associate Professor at the University of Inland Norway, affiliated with the Faculty of Teacher Education and Pedagogy and the Department of Pedagogy at the Teacher Education Department. Her research focuses on cybersecurity education, robotics integration in schools, teacher professional development with digital tools, sustainable education, and global-local educational policies. She leads projects like KidCY (cybersecurity education for children) and SustainALL (sustainability in all-day schools), collaborating internationally with institutions in countries such as Austria, Portugal, and Liechtenstein. Her work emphasizes innovative technologies like AR/VR, humanoid robots, and AI to enhance educational practices. Key projects include developing interactive materials for child cybersecurity awareness and creating curricula for climate stability through whole-school approaches. She is part of the Profession, Education, Learning, and Society (PULS) research group and has published extensively on comparative education, teacher training, and human rights education. Recent activities include advancing KidCY’s modular course for teachers and presenting SustainALL’s online sustainability course. Her publications span journals like Technology, Knowledge and Learning and Frontiers in Education , addressing topics from robotics in classrooms to institutional logics in global education policies.

• Cybersecurity Education
• Robotics in Education
• Teacher Professional Development
• +۶ مورد دیگر

Kyrre Glette is a Professor at the University of Oslo's Department for Informatics, affiliated with the RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion and the Robotics and Intelligent Systems (ROBIN) research group. His work focuses on co-designing robot bodies and behaviors using AI methods, particularly through the open-source robotic platform DyRET. Research interests include evolutionary robotics, bio-inspired computing, and embodied AI. Research Groups: Robotics and Intelligent Systems (ROBIN) RITMO Centre of Excellence fourMs Lab Projects: COCOMO: Co-evolution of Control and Morphologies Multimodal Elderly Care Systems (MECS) Predictive and Intuitive Robot Companion (PIRC) His publications explore topics like evolutionary algorithms for morphological adaptation, embodied music interfaces, and neural mechanisms of auditory prediction. Advising focuses on MSc projects in evolutionary robotics and modular robot control.

• Artificial Intelligence
• Robotics
• Evolutionary Computing
• +۴ مورد دیگر