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Kai Olav Ellefsen is an Associate Professor at the Department of Informatics (IFI), University of Oslo, specializing in biologically inspired artificial intelligence and robotics. He leads research within the Robotics and Intelligent Systems (ROBIN) research group, focusing on how biological principles can inform the development of more intelligent robotic systems. Ellefsen's research interests span multiple areas of artificial intelligence, with particular emphasis on evolutionary algorithms, reinforcement learning, and neuroevolution. His work explores how robots can learn from experience without disrupting previously acquired knowledge, adapt to new situations, interpret sensor data, and build environmental models. He investigates these challenges at various levels of abstraction, from simple simulations to real-world robotic implementations. His research often bridges computer science with biological inspiration to create more robust and adaptive intelligent systems. His recent publications demonstrate a strong focus on quality-diversity optimization, evolutionary robotics, and the application of AI to environmental monitoring and network quality assessment. The research shows a consistent pattern of exploring how diversity in evolutionary algorithms can lead to more robust solutions, how robots can adapt to changing environments, and how predictive models can be transferred across different tasks. There's a clear progression from theoretical exploration of evolutionary algorithms to practical applications in robotics and networking. Norwegian Artificial Intelligence Society Best Master Thesis Award (2010) Ellefsen actively supervises numerous PhD and Master's students, with a current focus on evolutionary robotics, neuroevolution, and AI safety. His supervision portfolio includes both theoretical work on evolutionary algorithms and practical applications in robotics. He has been involved in several research projects including the Predictive and Intuitive Robotic Assistant (PIRC) project. His teaching includes courses such as IN3050/4050 - Introduction to Artificial Intelligence and Machine Learning, and IN5490/9490 - Advanced Topics in Artificial Intelligence for Intelligent Systems. As part of the Robotics and Intelligent Systems (ROBIN) research group, Ellefsen collaborates with researchers working on various aspects of intelligent systems, from theoretical foundations to practical implementations. His work often involves interdisciplinary collaboration, particularly with researchers in mechanical engineering, biology, and environmental science to develop robotic systems with real-world applications.

• Artificial Intelligence
• Deep Learning
• Evolutionary Algorithms
• +6 more

Arron Burnage is a Researcher affiliated with the University of Oslo's Department of Chemistry, part of the Faculty of Mathematics and Natural Sciences. He is associated with the Hylleraas Centre for Quantum Molecular Sciences. His academic background includes an MChem from the University of Sussex (UK) and a PhD from Heriot-Watt University (UK), where his research under Prof. Stuart Macgregor focused on computational studies of solid-state σ-alkane complexes. His research interests span Palladium Catalysis, Homogeneous Catalysis, and Theoretical Chemistry, with a focus on leveraging Molecular Modelling using Density Functional Theory (DFT) and AI-driven methodologies. Recent work includes applying AI to understand transition metal complexes in catalytic systems, as evidenced by his 2025 publication in ACS Catalysis . Burnage's research aligns with the Hylleraas Centre's mission in quantum molecular sciences, emphasizing computational and theoretical approaches to chemical systems.

• Palladium Catalysis
• Homogeneous Catalysis
• Theoretical Chemistry
• +3 more

Lucas Georges Gabriel Charpentier is a Doctoral Research Fellow at the University of Oslo's Faculty of Mathematics and Natural Sciences, affiliated with the Research Group for Language Technology and the Digital Security (SEC) group. His research focuses on Natural Language Processing, deep learning, privacy, and machine learning, with an emphasis on language models, computational linguistics, and ethical AI applications. He has contributed to studies on multilingual models, model fusion (BERT vs GPT), compositional generalization, and privacy-preserving techniques. Charpentier is actively involved in international conferences, including the BabyLM Challenge and NoDaLiDa/Baltic-HLT, and collaborates with researchers across institutions. His work bridges theoretical advancements and practical applications in NLP, addressing challenges in low-resource languages and model efficiency. Education: Pursuing a PhD in Informatics at the University of Oslo Research interests include language model architecture optimization, multimodal learning, and ethical considerations in AI. His publications span topics from continual training for Norwegian languages to re-identification risks in documents. Charpentier's contributions highlight innovations in neural network design and interdisciplinary approaches to computational linguistics.

• Natural Language Processing
• Deep Learning
• Privacy
• +3 more

Jefferson Molléri is an Associate Professor at Kristiania University College's School of Economics, Innovation and Technology. He specializes in evidence-based software engineering and empirical research methods, focusing on software process improvement, AI applications in software engineering, and human factors in technology development. PhD in Software Engineering (Blekinge Institute of Technology, 2019) Postdoctoral research at Simula Metropolitan Centre for Digital Engineering Academic experience since 2014 His research emphasizes methodological rigor, ethical considerations, and participatory approaches in software engineering. He has developed empirical standards and checklists for survey research validation. Recent publications focus on DataOps integration, hybrid workplace transformations, and research quality frameworks. Jefferson teaches software engineering, information technology, and computer science courses. He advocates for critical appraisal of scientific literature and has extensive experience supervising students across undergraduate, graduate, and doctoral programs.

• Software Engineering
• Computer Science
• Empirical Research Methods
• +10 more

Jon Petter Rui is Professor at both UiT Norway's Arctic University and the University of Bergen's Faculty of Law. His research intersects criminal law, data governance, and AI regulation, with projects like SupER (Supervision and Enforcement of EU Economic Regulation). He examines proportionality in sentencing, algorithmic accountability, and anti-money laundering protocols. Recent publications address machine unlearning ethics and human rights implications of digital surveillance in fisheries. Rui collaborates internationally on fintech compliance and cybersecurity frameworks.

• Criminal Law
• Data Protection
• AI Regulation
• +1 more

Dr. Jian Dai is an Associate Professor and Head of Studies for Civil Engineering at Oslo Metropolitan University's Faculty of Technology, Art and Design, Department of Built Environment. His research focuses on computational structural dynamics, railway systems, and very large floating structures, with applications to marine renewable energy systems and infrastructure dynamics. He holds a PhD from the National University of Singapore (2015) and a BEng from Tongji University (2009). Key research areas include hydroelastic analysis of floating photovoltaic systems, train-track interaction dynamics, and wave-structure interaction modeling. He leads the Net-Zero Future project aiming to reduce carbon footprints in built environments. He is a member of structural engineering research groups and has contributed to over 56 peer-reviewed publications. Current projects involve offshore floating solar arrays, submerged floating tunnel dynamics, and corrosion monitoring in suspension bridges. His work integrates experimental methods, numerical modeling, and machine learning for infrastructure resilience and sustainable energy solutions.

• Computational Structural Dynamics
• Railway Systems
• Very Large Floating Structures
• +6 more

Alejandro Jiménez Rios is a Lecturer in Structural Engineering at the Department of Architecture & Civil Engineering, University of Bath, UK. His research focuses on preserving historic structures, sustainable architecture, and integrating Industry 5.0 technologies like digital twins and AI into conservation practices. He holds a PhD from Trinity College Dublin and has held fellowships at Sapienza University of Rome and the ICCROM. Education: PhD in Civil, Structural and Environmental Engineering, Trinity College Dublin (2016–2019) Erasmus Mundus MSc in Structural Analysis of Monuments and Historical Constructions, Czech Technical University and UPC Barcelona (2015–2016) BSc in Civil Engineering, University of Guadalajara (2009–2014) Research Interests: Conservation of historic buildings, non-destructive testing, sustainable materials, digital twins, and Industry 5.0 applications in civil engineering. His work aligns with UN Sustainable Development Goals 9 and 11. Recent Articles: Focus on digital twin frameworks for heritage bridges, Industry 5.0 in conservation, and AI-driven corrosion prediction. Recent trends include interdisciplinary collaboration and technology-driven solutions for cultural heritage preservation. Grants & Awards: Marie Skłodowska-Curie Actions Individual Fellowship (€227K, 2022–2025) ICCROM Visiting Fellowship (2024) MCAA Micro Grant (€820, 2024) Advising & Labs: Supervises PhD and Master’s students in structural conservation and hosts a vibrant research team at the Centre for Regenerative Design & Engineering (RENEW) at Bath. Collaborates with NGOs, museums, and policymakers on heritage conservation projects.

• Structural Engineering
• Conservation of Historic Buildings
• Non-Destructive Inspection Methods
• +8 more

Alireza Khakpour is an Associate Professor at the Department of Computer Science and Communication at Østfold University College. He holds a PhD in Computer Science from the University of Oslo (2024), focusing on Visual Analytics Modeling for Decision-Support Systems. His academic journey includes bachelor's (MSRIT, 2013) and master's degrees in Software Engineering (Azad University, 2018) and Applied Computer Science (Østfold University College, 2020). His research interests span Visual Analytics, Information Systems, Explainable AI, and Machine Learning, with a focus on applying these fields to supply chain optimization and decision support. He contributes to the DigiMat project, aiming to enhance Norway's food supply chain through smart, sustainable technologies. He teaches courses such as Big Data Processing, Business Intelligence, and interdisciplinary projects, supervising both bachelor's and master's theses. His publications emphasize frameworks for Visual Analytics, supply chain analytics, and systematic reviews on topics like Domain-Specific Languages and Gamification-Machine Learning synergies. His work bridges theoretical models with practical applications in logistics, data science, and decision-making systems. Khakpour's academic contributions include developing ModelViz, a Model-Driven Engineering tool for Visual Analytics, and exploring greenable technologies in reality systems. His research aligns with real-world challenges such as sustainable supply chains and data-driven decision support in production and retail sectors.

• Visual Analytics
• Information Systems
• Explainable AI
• +3 more

Baltasar Enrique Beferull Lozano is a tenured Professor at the University of Agder , leading the Center Intelligent Signal Processing and Wireless Networks (WISENET) since 2015. With a PhD in Electrical Engineering from USC (2002) and prior roles at EPFL, AT&T Shannon Labs, and University of Valencia, his career spans 20+ years of academic and industrial research in signal processing, wireless systems, and AI. Education: PhD (USC), MSc (USC), MSc (University of Valencia) Expertise: Data Science, Machine Learning, Graph Signal Processing, Cyber-Physical Systems His research focuses on AI-driven wireless networks and in-network collective intelligence , addressing fundamental and applied challenges in smart water systems , energy management , and next-gen 5G/6G . He has secured 20+ international projects including 10 EU-funded initiatives (HYDROBIONETS, SENDORA) and 5 RCN-funded projects. Recent publications emphasize dynamic graph learning from time series data, quantized graph filters , and multi-agent reinforcement learning for networked environments. Awards include IEEE Best Paper Awards (2012, 2021), TOPPFORSK Grant (2015), and Ramón y Cajal Program Rank #1 (2005). As a Senior IEEE Member , he serves as Area Editor for IEEE Transactions on Signal Processing and evaluates research proposals for the European Commission , NSF , and Qatar National Research Fund . His lab has produced 15 PhD graduates and collaborates with 12+ industry partners including Telenor, IBM, and SINTEF.

• Data Science
• Machine Learning
• Signal Processing
• +3 more

Monica Nordbakke is an Associate Professor at the Department of Natural Sciences, Practical-Aesthetic, Social and Religious Studies (RES) at Østfold University College . Her academic interests focus on mathematics education, particularly student learning practices in diverse educational settings. She holds a master's degree in mathematics didactics, emphasizing adapted education strategies in mathematics. Nordbakke currently serves as Deputy Chairman of LAMIS Østfold (The National Team for Mathematics at School) and collaborates on projects like Alternative Practice at a Science Center and DigiLU, exploring student-active learning forms. Her work emphasizes curriculum development, teacher education, and fostering engagement in mathematics through innovative methods like flipped classrooms and exploratory learning. Notable awards include recognition as a 'Merittert Underviser' (Merited Teacher). She teaches mathematics courses for elementary and kindergarten teacher education programs, with a strong emphasis on practical, student-centered approaches. Education: 4-year general teacher education Master's degree in Mathematics Didactics (thesis: Adjusted Education in Mathematics) Research Focus: Nordbakke’s research bridges theory and practice in mathematics education, focusing on: Student learning dynamics across educational stages Teacher professional development through collaborative networks Innovative teaching tools like vertical boards and science center collaborations Curriculum alignment between schools and higher education Her work often highlights the transition between elementary and secondary education, emphasizing inclusive and mastery-oriented teaching strategies. Awards: Merittert Underviser (2024) Grants & Projects: Alternative Practice at a Science Center Collaboration and Study Intensity in Mathematics Teacher Education DigiLU: Digital Learning Innovations STIL: Student-Active Learning Forms Labs/Teams: Active in research groups like Collective Learning and Competence Development and Education in Mathematics, Science, and Technology .

• Mathematics Education
• Mathematics Didactics
• Educational Practices
• +3 more

Athanasios Vasilakos is a Professor at the University of Agder's Department of Information and Communication Technology. His research focuses on cutting-edge ICT domains including quantum computing, cybersecurity, and distributed systems. He maintains an extensive publication record with recent works concentrated in quantum machine learning, blockchain applications, and IoT security. Research interests span: Quantum computing architectures and cryptographic applications Secure federated learning frameworks for distributed networks AI-driven solutions for IoT and telecommunications systems Advanced cybersecurity techniques including steganalysis and homomorphic encryption Cross-domain applications in bioinformatics, smart grids, and autonomous vehicles Publication analysis reveals strong thematic focus on: security enhancements for emerging technologies (blockchain, quantum systems), privacy-preserving machine learning, and IoT optimization. Recent works demonstrate increasing attention to quantum-classical hybrid systems and their real-world implementations. Collaboration networks include extensive international partnerships across Europe and Asia, particularly in quantum computation, cybersecurity, and intelligent systems research.

• Quantum Computing
• Cybersecurity
• Artificial Intelligence
• +5 more

Troels Linde is a Professor at the University of Inland Norway (INN), affiliated with the Faculty of Film, TV and Games. His work is associated with the Norwegian Film School and research initiatives related to AI in art and digital media. He is based at the Oslo study site and can be contacted via email at troels.linde@inn.no or phone at +47 61 28 81 43. The Faculty of Film, TV and Games at INN emphasizes interdisciplinary collaboration with initiatives like Compass AI Art and AI Re:search, focusing on integrating artificial intelligence into creative practices. The faculty operates across multiple campuses, including Oslo, and offers programs aligned with digital storytelling, film production, and game development.

• Film Studies
• Television Production
• Game Design
• +2 more

Adam Leon Kleppe is an Associate Professor at the Norwegian University of Science and Technology (NTNU) , affiliated with the Department of ICT and Natural Sciences. He works extensively with MANULAB , focusing on robotic welding labs and Industry 4.0 labs , handling procurement, planning, installation, and maintenance. His research spans robotics, geometric algebra, point cloud processing, and automation technologies. Education : Master in Engineering Cybernetics with a specialization in robotics from NTNU (2013); Ph.D. (2018) on Point Cloud Registration for Assembly using Conformal Geometric Algebra. Research Interests revolve around robotics, including inverse kinematics, point cloud alignment, obstacle detection, and geometric algebra applications. He also explores automation in manufacturing and aquaculture, such as deformable body modeling for salmon equipment testing and machine vision for fish bin picking. Publication Trends show a consistent focus on geometric algebra-based solutions for robotic tasks, with recent work extending into biomechanical simulation and aquaculture automation. Teaching includes courses like Mechatronics and Systems Integration , Automation and Mechatronics , and Industrial Control Systems . He also contributes to outreach via program management for AI videos on platforms like YouTube and LinkedIn.

• Robotics
• Point Cloud Registration
• Conformal Geometric Algebra
• +4 more

Dr. Alexander Johan Nederbragt ("Lex Nederbragt") is a Senior Lecturer at the University of Oslo's Faculty of Mathematics and Natural Sciences, affiliated with the Centre for Ecological and Evolutionary Synthesis (CEES) and former member of the Centre for Computational Inference in Evolutionary Life Science (CELS). He leads the "Computing in Science Education" initiative within the Bioscience bachelor's program, developing courses like BIOS1100 that integrate Python programming with biological modeling. His educational philosophy emphasizes reverse instructional design and constructive alignment, with a focus on student-active learning and AI-driven pedagogical innovation. Researchwise, Nederbragt specializes in Bioinformatics and Genomics , particularly Evolutionary genomics of fish (Atlantic cod, haddock, grayling) Graph-based reference genome methodologies Genomic repeat element analysis Horizontal gene transfer in diatoms Computational microbiome studies His work spans comparative genomics, genome assembly validation, and bioinformatics software development (NucDiff, NucBreak). Scientific contributions reveal expertise in High-throughput sequencing Genomic architecture Evolutionary adaptation Computational methods Publication trends from 2012-2023 His research frequently intersects with ecological and evolutionary questions, particularly in teleost fishes. Scientific Awards Merittert Utdanner (Excellent Teaching Practitioner), University of Oslo (2023) Olav Thon Foundation National Award for Excellence in Teaching (2025)

• Bioinformatics
• Genomics
• Computational Biology
• +4 more

Jose David Patón-Romero serves as a Postdoctoral Fellow in the Department of IT Management at Simula Metropolitan, a research division of Simula Research Laboratory. His work bridges business governance, digital transformation, and sustainable technology practices, with a focus on real-world implementation challenges in organizational contexts. His core research domains include: Business governance and management frameworks Program and project management methodologies Benefits management in digitalization initiatives Assessment and auditing techniques Process improvement strategies Sustainability integration Green IT solutions Analysis of his publication trends reveals a strong interdisciplinary trajectory connecting management science with social impact. His work consistently addresses the human dimensions of technology, particularly through investigations of gender equality in AI systems, decolonizing academic narratives, and mobile applications for social justice. The recurring emphasis on benefits management and goal hierarchies demonstrates a methodological commitment to evaluating tangible outcomes in digital transformation projects, while his Green IT research explores environmental sustainability metrics within IT governance frameworks. No scientific awards were documented in the source material. Available information does not specify student advisement activities or research grant funding. His professional engagements include invited talks on internationalization, doctoral impact, and Green IT implementation at institutions including Unidad Central del Valle del Cauca and Universidad Tecnológica de Xicotepec de Juárez. Dr. Patón-Romero maintains active research collaboration through Simula Metropolitan's IT Management department, with documented partnerships across European institutions as evidenced by his multi-country publications on decolonizing academic practices and gender equality metrics.

• Business governance and management
• program and project management
• benefits management
• +4 more