Norwegian University of Science and TechnologyNorway
Professor Ingrid Bouwer Utne is a faculty member at the Department of Marine Engineering, Norwegian University of Science and Technology (NTNU). Her primary research focuses on risk analyses of ships, marine systems, and autonomy, with emphasis on operational safety, maintenance management, and risk control in autonomous maritime technologies. Key Projects: Leader of the Risk Group at NTNU, involved in the SFI Autoship initiative and ERC AdG BREACH project addressing risk-based rationality in autonomous systems. Research Interests: Autonomous systems design, probabilistic risk assessment, safety engineering, and risk-informed decision-making for marine operations. Grants & Funding: Secured funding from the Research Council of Norway, MAROFF, and industry partners for projects like ORCAS (Online Risk Management for Autonomous Ships) and UNLOCK (Supervisory Risk Control). She supervises numerous PhD students and postdocs, focusing on topics such as autonomous vessel navigation, risk modeling for underwater robotics, and decarbonization of maritime systems. Her work bridges theoretical risk analysis with practical applications in marine autonomy and safety systems.
Norwegian University of Science And TechnologyNorway
Børge Rokseth is an Associate Professor at the Department of Engineering Cybernetics, Norwegian University of Science and Technology (NTNU). His work focuses on maritime systems, autonomous vessel control, and safety verification. He actively supervises Master's students and contributes to research on risk-informed control systems, hybrid power systems, and systems-theoretic process analysis (STPA). Research Interests: Rokseth's research spans autonomous ship systems, dynamic risk assessment, and safety verification. He explores risk-based decision-making for maritime autonomy, hazard identification in hybrid propulsion systems, and control function allocation in dynamic positioning. His work integrates systems theory, machine learning, and regulatory compliance (e.g., COLREGS) to enhance safety and environmental performance in marine operations. Publications: His recent work includes probabilistic trajectory prediction frameworks for autonomous ships, STPA-based safety analyses, and studies on decarbonization barriers in the maritime industry. These publications emphasize risk modeling, systems-theoretic approaches, and simulation-based verification. Teaching: Rokseth teaches courses such as TTK4130 - Modelling and Simulation, contributing to the education of future engineers and researchers in cybernetics and maritime systems.
Trym Vegard Haavardsholm is a 20% part-time Lecturer at the University of Oslo (UiO) within the Section for Autonomous Systems and Sensor Technologies. He also serves as Principal Scientist at the Norwegian Defence Research Establishment (FFI) and is a PhD candidate at the Department of Engineering Cybernetics, NTNU. His research focuses on computer vision, machine learning, robotics, and image analysis, with a particular emphasis on multispectral imaging systems and unmanned aerial vehicles (UAVs). Haavardsholm has contributed to advancements in sensor technologies for tactical reconnaissance, autonomous navigation, and real-time data processing. His work spans applications in defense, environmental monitoring, and emergency response systems. Research Interests Haavardsholm’s research integrates interdisciplinary approaches to develop innovative sensor systems and algorithms. Key areas include compact multispectral imaging for small UAVs, in-operation camera calibration, and anomaly detection in hyperspectral data. His contributions emphasize practical applications such as urban feature classification, collaborative indoor navigation, and bioaerosol detection. His work bridges theoretical computer science with applied engineering, addressing challenges in autonomous systems and sensor fusion. Publications His publications highlight trends in multispectral sensor design, UAV imaging, and real-time georeferencing. Recent work includes compact sensor systems for tactical use and advancements in pushbroom image rectification. Earlier research explored band selection algorithms for target detection and GPU-accelerated anomaly detection. Professional Roles As a lecturer, Haavardsholm contributes to academic supervision and teaching in autonomous systems. His dual role at FFI and UiO reflects his commitment to translating academic research into practical defense and civilian applications. His PhD candidacy at NTNU underscores his ongoing academic engagement in engineering cybernetics.
Lokukaluge Prasad Perera is a Professor in Maritime Technology at UiT The Arctic University of Norway and a Senior Research Scientist in Smart Data at SINTEF Digital . He holds a BSc in Mechanical Engineering from Oklahoma State University (1999), MSc in Systems & Controls from the same institution (2001), and a PhD in Naval Architecture and Marine Engineering from Technical University of Lisbon (2012). His research focuses on Maritime and Offshore Systems , Advanced Data Analytics , Autonomous Navigation , Energy Efficiency , and Digital Twin Applications . He has published over 100 peer-reviewed papers and was recognized in the World's Top 2% Scientists (2021-2022) by Stanford University. Key professional experiences include roles at SINTEF Ocean (2014–2017), Center for Marine Technology and Engineering in Portugal (2008–2012), and Wärtsilä Finland (2012–2014). He has also held academic positions at Naval & Maritime Academy and Ocean University of Sri Lanka . His work addresses challenges in emission reduction , renewable energy integration , and safety-critical systems for maritime operations. Current projects emphasize trustworthiness of autonomous ships and data-driven decision frameworks for energy efficiency.
Tae Eun Kim is an Associate Professor in Maritime Safety Management at UiT The Arctic University of Norway, working within the Department of Technology and Security. Her research, teaching, and industrial collaboration focus on maritime safety and human factors, with particular expertise in maritime safety management, accident analysis, Maritime Autonomous Surface Ships (MASS), and human factors in maritime operations. Dr. Kim's research spans four interconnected domains: maritime safety management and leadership, maritime accident and casualty analysis, Maritime Autonomous Surface Ships (MASS), and human factors in maritime operations. She has developed assessment instruments like the Safety Leadership Self-Efficacy Scale (SLSES) and conducted STAMP-based causal analyses of maritime accidents. Her work on MASS addresses safety challenges in mixed navigational environments and examines leadership competencies for autonomous shipping operations. Her human factors research explores how technological advancements impact navigators' performance, crew dynamics, and safety outcomes, including gender parity issues in the maritime industry. Dr. Kim's publication record reveals a strong focus on the intersection of maritime safety, technology, and human performance. Her recent work increasingly addresses autonomous shipping technologies, with numerous publications on AI decision transparency, learning analytics in maritime simulator training, and multi-modal data analysis for nautical skill development. She has conducted systematic reviews on simulator training approaches and scenario design, contributing significantly to methodology development in maritime education and training. Her research demonstrates a clear trajectory toward integrating emerging technologies with traditional maritime safety practices as the industry transitions toward greater automation. Dr. Kim is actively involved in several significant research projects, including the i-MASTER EU Horizon Europe Research and Innovation Project, the REFRAME project, and the SPRICE project (Multidisciplinary approach for spray icing modelling). She is a member of both the Advanced Maritime Ship Operations research group and the Maritime Safety Science (MARSCI) Research Group, demonstrating her commitment to collaborative research in maritime safety science. Dr. Kim teaches several specialized courses at UiT, including SVF-3206 Safety Management and Accident Investigation, TEK-3014 Navigation Technology, MFA-2100 Maritime Digitalization, MFA-8010 Maritime HTO (Human-Technology-Organisation) and Innovation, and MFA-2018 Maritime Administration and Leadership. Her teaching portfolio reflects the interdisciplinary nature of her expertise, bridging engineering, safety science, and organizational behavior in maritime contexts.
Dr. Danesh Tarapore is an Associate Professor at the University of Southampton specializing in robotics and AI. He focuses on human-robot interaction, swarm intelligence, and autonomous systems. His current research involves developing resilient robotic teams and optimizing learning algorithms for constrained environments. He supervises 6 PhD students in the iPhD MINDS and Computer Science programs. Dr. Tarapore's work bridges theoretical advancements with practical applications in autonomous navigation, multimodal dataset creation, and quality-diversity optimization. His publications span conferences like HRI and journals in robotics and AI. He collaborates with institutions like the University Hospital Southampton and the Boldrewood Innovation Campus. Research Interests: Human-robot collaboration, swarm systems, machine learning, and adaptive control Key Contributions: HRI-SENSE dataset, evolutionary subset selection algorithms, forest navigation frameworks Grants and Funding: Active projects in multi-agent systems and resilient robotics Dr. Tarapore maintains active roles in the robotics community through conference participation and interdisciplinary collaborations.
Hans Jonas Fossum Moen is an Associate Professor with a 20% appointment at the Department of Technology Systems, University of Oslo (UiO), and holds a 100% position as a researcher at the Norwegian Defence Research Establishment (FFI). His primary affiliation is with the Section for Autonomous Systems and Sensor Technologies. He is based at the Kjeller campus, with a visiting address at Gunnar Randers Road 19 and a postal address at Postboks 70. His research focuses on advancing autonomous systems and sensor technologies, particularly in the domains of swarm robotics, multi-agent coordination, and optimization algorithms. Key areas include UAV navigation, distributed localization in IoT networks, radar detection enhancement, and adaptive control systems for multi-functional swarms. He emphasizes the integration of biological principles into robotic systems, as evidenced by his participation in the ICRA 2018 Workshop on Swarms. His publications consistently highlight contributions to swarm intelligence, with a focus on improving data quality and efficiency in robotics applications. He has collaborated extensively with colleagues such as Kyrre Glette, Oleg Yakimenko, and Jan Dyre Bjerknes, exploring topics ranging from task allocation in multi-agent systems to evolutionary algorithms for filter optimization. His work bridges theoretical computer science with practical engineering challenges in autonomous systems. No scientific awards have been explicitly mentioned in the provided texts. Moen’s advising and grants narrative indicates no listed advisees or active grant projects, though his 20% UiO position suggests potential involvement in academic supervision. His primary research activities are embedded within FFI and the Autonomous Systems section at UiO, contributing to interdisciplinary efforts in sensor technologies and robotic systems.
Professor Ole-Christoffer Granmo is a distinguished academic at the University of Agder, Norway, where he serves as Professor in the Department of Information and Communication Technology. He is the Founding Director of the Centre for Artificial Intelligence Research (CAIR) at the University of Agder, leading cutting-edge research in artificial intelligence and machine learning. Dr. Granmo obtained his master's degree in 1999 and his PhD in 2004, both from the University of Oslo. His academic journey has been marked by significant contributions to the field of AI, most notably the creation of the Tsetlin machine in 2018, for which he received the AI research paper of the decade award from the Norwegian Artificial Intelligence Consortium (NORA) in 2022. Professor Granmo's research primarily focuses on logical and causal world modeling across multiple modalities including images, sound, and natural language. His work spans logical auto-encoding, convolution, regression, transformer architectures, and reinforcement learning, all with the overarching goal of creating ultra-low-power artificial general intelligence through transparent logical learning and reasoning. His publications reveal a strong emphasis on interpretable AI systems, hardware implementations, and applications across diverse domains including cybersecurity, healthcare, social media analysis, and bioinformatics. AI Research Paper of the Decade (2022) - Norwegian Artificial Intelligence Consortium (NORA) Eight paper awards in machine learning Professor Granmo has coordinated over seven research projects and mentored 55+ master's students and nine PhD students. His leadership extends to co-founding the Norwegian Artificial Intelligence Consortium (NORA) and establishing two companies: Anzyz Technologies AS and Tsense Intelligent Healthcare AS. As an advisor at Literal Labs, he actively bridges academic research with practical industry applications, demonstrating his commitment to translating theoretical innovations into real-world solutions that address complex challenges across multiple sectors.
Norwegian University of Science And TechnologyNorway
Hans Petter Hildre is Head of Department at the Department of Ocean Operations and Civil Engineering , part of the Faculty of Engineering at the Norwegian University of Science and Technology (NTNU). His work focuses on maritime engineering, digital twin technology, and marine operations. Research interests include: Digital Twin Applications in Maritime Industry Offshore Operations and Wind Turbine Installation Marine Robotics and Autonomous Systems Wave Field Estimation and Environmental Load Analysis Human-Machine Interaction in Maritime Contexts Co-simulation and Real-time Monitoring Recent publications highlight trends in: Wave shielding effects for offshore vessels Knowledge transfer from automotive/aviation to maritime Crane path planning using digital twins Visual attention zone recognition systems Hydrodynamic modeling and sensitivity analysis Smart city-maritime integration Scientific collaborations span institutions including: European Commission (Future Skills Reports) Royal Institution of Naval Architects The American Society of Mechanical Engineers (ASME) IEEE Transactions on multiple domains Springer Publishing
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.
Idar Dyrdal is a Lecturer at the University of Oslo's Institute of Transport Economics (ITS), holding a 20% part-time position. He is affiliated with the Section for Autonomous Systems and Sensor Technologies, focusing on research in autonomous systems and robotics. His work spans scene understanding for autonomous steering, leveraging sensor technologies and advanced algorithms. Research Interests: Idar's expertise centers on autonomous systems, sensor technologies, and their applications in vehicle control. His studies emphasize real-time data processing for safe and efficient autonomous navigation. Labs/Teams: Active within the Section for Autonomous Systems and Sensor Technologies at ITS, contributing to interdisciplinary projects in robotics and transportation systems.
Norwegian University of Science and TechnologyNorway
Kristin Y. Pettersen is a Professor at the Department of Technical Cybernetics, Norwegian University of Science and Technology (NTNU), and a Professor II at the Norwegian Defence Research Institute (FFI). She is a co-founder of Eelume AS, a company specializing in underwater robotics solutions. Education: Civil Engineering and PhD in Technical Cybernetics from NTNU Her research focuses on advanced control systems for marine and underwater vehicles, particularly snake robots and autonomous underwater vehicles (AUVs). Key areas include formation control, path following, adaptive guidance algorithms, and safety-critical control in dynamic environments. Recent work explores machine learning integration and energy-shaping techniques for robust locomotion. Publications highlight trends in Model Predictive Control (MPC) , Collision Avoidance , and Task-Priority Operational Space Control for redundant and underactuated systems. Her work bridges theoretical control theory with practical applications in marine robotics, including autonomous inspections and cooperative transport. Labs/Teams: Collaborates with NTNU's Faculty of Information Technology and Electrical Engineering and co-founded Eelume AS, advancing subsea robotic manipulation technologies.
Jim Tørresen is a Professor of Computer Science at the Department of Informatics, University of Oslo, where he has been employed since 1999 (Associate Professor 1999-2005, Professor since 2006). He serves as group leader for the Robotics and Intelligent Systems (ROBIN) research group and is also a Principal Investigator at the Centre for Interdisciplinary Studies in Rhythm, Time and Motion (RITMO). His academic career includes visiting positions at Cornell University's Creative Machines Lab (2010-2011) and Kyoto University in Japan (1993-1994). His educational background includes a Dr.ing. (Ph.D.) in Computer Architecture from the Norwegian University of Science and Technology (1996) and an M.Sc. in Computer Architecture from the same institution (1991). Before his academic career, he worked in industry at Navia Aviation (1998-1999) and NERA Telecommunications (1996-1998). Tørresen's research spans artificial intelligence, robotics, and bio-inspired computing. His work focuses on biology-inspired algorithms, programmable logic (FPGA), robotics (simulation, prototyping, control), and human-robot interaction. He has made significant contributions to areas including evolutionary computing, reconfigurable hardware, and adaptive systems. His research often bridges theoretical computer science with practical applications in healthcare, music, and industrial settings. His recent publications demonstrate a strong focus on human-robot interaction, particularly in healthcare contexts for elderly care, as well as applications in sports science, musical robotics, and geological engineering. His work shows a consistent pattern of interdisciplinary research that combines machine learning techniques with domain-specific challenges. Tørresen has also authored a popular science book on artificial intelligence in the "what is" series by Universitetsforlaget, which discusses fundamental concepts, methods, future perspectives, and ethical aspects of AI. He has been active in academic leadership, serving as General Chair for the 22nd International Conference on Field Programmable Logic and Applications (FPL) in 2012 and the 9th Joint IEEE International Conference of Developmental Learning and Epigenetic Robotics in 2019. As group leader of ROBIN, he oversees research on intelligent systems that operate in dynamic environments requiring runtime adaptation. The group works at both fundamental and applied levels, using evolutionary algorithms for robot learning and machine learning techniques for classification and recognition tasks in various application domains.
Georgios Kavallieratos is an Associate Professor at the University of Oslo's Institute of Transport Economics, specializing in the Section for Autonomous Systems and Sensor Technologies. His research focuses on cybersecurity in maritime systems, cyber-physical systems, and risk management. He actively contributes to the DESSI project on energy system security infrastructure. His research interests include maritime cybersecurity, cyber-physical system security, and the intersection of safety and security in autonomous systems. His work addresses threats to navigation systems, smart farming, and satellite communications, with a focus on developing risk assessment frameworks and robust cybersecurity controls. Recent publications emphasize maritime cybersecurity trends, integrated navigation system protection, and threat analysis in emerging technologies like Dairy Farming 4.0. He co-authored foundational papers on cyberattack defenses for autonomous ships and cybersecurity requirements for Shipping 4.0. Current projects involve enhancing societal awareness of cybersecurity risks and improving incident response strategies for critical infrastructure. His work bridges theoretical cybersecurity principles with practical applications in transportation and industrial systems.
Dr. Hongbin Liu is a Senior Lecturer at the Department of Informatics, King’s College London, UK, affiliated with the Centre for Robotics Research. His work focuses on robotic tactile sensing, soft robot design, and haptic exploration. Research Interests: Robotic tactile sensing Learning objects by touch Soft and flexible robot design Modelling of soft interactions Dr. Liu’s recent publications highlight advancements in robotics and sensor technology , particularly in tactile perception, medical device design, and continuum robot navigation. His work integrates Bayesian classifiers for autonomous object recognition, polymer-based optical waveguides for triaxial tactile sensors, and deep learning for medical diagnostics. Collaborations span institutions like Imperial College London, The University of Hong Kong, and Medical University of Vienna. Professional Affiliation: King’s College London Department of Informatics Centre for Robotics Research (research group)
/trymh/trym.jpg)
/hjmoen/j.png)
/tonnesfn/t.jpg)
/dyrdali/idar.jpg)
/georgkav/georg.jpg)