Hans Kristian Høidalen is a Professor at the Department of Electric Energy , Faculty of Information Technology and Electrical Engineering , Norwegian University of Science and Technology (NTNU). His work focuses on computer simulations and modeling of power systems , particularly transformers and cables, and he leads the development of the ATPDraw simulation tool. Research areas include power system protection , distributed generation , resonant overvoltages in offshore wind farms , and lightning effects on electrical systems . He leads major projects like KPN-project ProSmart (2015–2019) and KPN-project ProDig (2019–2023) , focusing on smart grid protection and digital substation technologies. Recent publications highlight advancements in transient analysis , transformer modeling , and 5G-enabled protection systems . Collaborations span institutions such as Michigan Tech , SINTEF , and ABB , with applications in smart grids , digital substations , and offshore wind farms .
Kristoffer Rypdal is a Professor in the Department of Mathematics and Statistics at UiT The Arctic University of Norway. His academic work spans multiple disciplines with a strong focus on complex systems modeling, particularly in climate science, energy systems, and statistical methods. He is an active member of the Complex Systems Modeling (CoSMo) research group. Dr. Rypdal's research interests include climate variability across scales, pandemic modeling (particularly during the COVID-19 pandemic), renewable energy systems, and statistical methods for complex data analysis. His work often bridges theoretical mathematics with practical applications in environmental science and public policy. He has made significant contributions to understanding climate sensitivity, carbon budgets, and the statistical properties of climate time series. His publication record shows a strong trend toward interdisciplinary research that connects mathematical statistics with real-world problems in energy policy and climate science. Recent work demonstrates his increasing engagement with Norwegian energy policy debates, where he applies rigorous statistical analysis to contemporary issues like wind power integration, hydropower management, and energy market design. His publications reveal a consistent pattern of translating complex mathematical concepts into accessible insights for policymakers and the general public. Regular contributor to nordnorskdebatt.no on energy policy and climate issues Active researcher in pandemic modeling during the COVID-19 crisis Expert in statistical analysis of climate data and time series Frequent collaborator on interdisciplinary research projects Dr. Rypdal maintains an active public engagement profile, regularly publishing opinion pieces that translate complex scientific concepts into accessible discussions about energy policy, climate change, and statistical reasoning. His work demonstrates a commitment to applying rigorous mathematical approaches to pressing societal challenges, particularly in the Arctic context where UiT is situated.
Alexander Sønderland Skjønberg serves as Professor of Law at BI Norwegian School of Business and will assume the position of Professor II at the Department of Private Law, Faculty of Law, University of Oslo starting autumn 2024. His academic appointments reflect deep engagement with Norwegian and international labor law frameworks. Skjønberg's research interests span Norwegian labor law, international labor law, legal history, and EEA law. His scholarly work demonstrates particular expertise in collective bargaining, managerial prerogative, collective agreement after-effects, and Supreme Court jurisprudence in labor matters. The publication record reveals consistent focus on how Norwegian labor law interfaces with European legal frameworks and evolving social dynamics. His 15 most recent publications show strong thematic continuity in labor law scholarship, with particular emphasis on collective bargaining agreements, Supreme Court interpretations, and the evolving boundaries of managerial prerogative. The research demonstrates methodological diversity including case analysis, legislative commentary, and comparative studies across Scandinavian jurisdictions. Skjønberg holds significant professional positions including editor of labor law in Karnov Lovkommentarer, editor of The Nordic Journal of Labour Law, and chairman of the Norwegian Labour Law Association (NARF). He serves as national expert for the European Centre of Expertise in labor law and is a member of the Executive Committee of the International Society for Labour and Social Security Law. As an educator, Skjønberg has extensive teaching experience across bachelor's, master's, and postgraduate levels, specializing in individual and collective employment law and EEA law. He will teach JUS5511/JUR1511 – Individual Labor Law in fall 2025 and supervise master's theses in employment law at the University of Oslo. His practical legal experience includes service as deputy judge and former acting judge in the Labour Court.
Marit Mjøs serves as Professor of Special Education Pedagogy at NLA University College Bergen, where she actively researches inclusive educational practices and systemic collaboration between schools and psychological counseling services (PPT). Her work bridges academic theory with practical implementation in Norwegian educational contexts. Her educational background spans foundational teacher training to advanced academic specialization: PhD in Special Education, University of Oslo (2007) Middle Management Training, Statskonsult (2000) Master's in Pedagogy, NLA University College (1993) Special Education (2nd division), Bergen University College (1982) Special Education (1st division), Trondheim Municipal Teacher Training College (1977) Teacher Training, Trondheim Municipal Teacher Training College (1973) Mjøs's research centers on special education's transformative potential within inclusive systems. She examines the dynamic relationship between specialized and general education, advocating for innovative models where special education expertise elevates whole-school practices. Her work critically analyzes legislative frameworks for individually adapted education while documenting historical evolution of special education interventions. Analysis of her 15 most recent publications reveals consistent focus on collaborative innovation across educational levels. She documents how municipal governance structures enable or constrain inclusive practices, with particular emphasis on leadership roles in fostering school-PPT partnerships. Methodologically, her work combines qualitative case studies with action research, prioritizing practical implementation in real-world settings over theoretical abstraction. Professor Mjøs supervises master's students at NLA while leading externally funded projects including the NFR-supported SUKIP initiative (2019-2023) and the EU-funded INVESTT project (2012-2015). Her grant portfolio demonstrates sustained success in securing competitive research funding for applied educational innovation. She directs interdisciplinary research teams involving university partners (University of Stavanger), national agencies (Statped), and municipal PPT services. Current work focuses on implementing the SUKIP project's collaborative frameworks across Norwegian educational contexts through structured competence development programs.
Qixia Zhang is a Postdoctoral Research Fellow in Computer Science at UiT The Arctic University of Norway and a guest researcher at University of Oslo. Their research spans multiple cutting-edge domains including cloud/edge computing, AI and machine learning, distributed systems, energy efficiency, and IoT applications. Zhang is actively involved in several major research projects including HAPADS, MISO, EMLEMS, eX3, DILUTE, and AirQMan, which focus on environmental monitoring, energy efficiency, and advanced computing systems. Dr. Zhang completed their educational journey at Huazhong University of Science and Technology in China, earning a B.Eng. degree in 2016 and a Ph.D. degree in 2021. Additionally, they studied Economics at Wuhan University from 2014-2016. Their academic path demonstrates a strong interdisciplinary foundation combining computer science with economic perspectives. Zhang's research interests focus on the intersection of computing technologies and environmental sustainability. They investigate how edge and cloud computing architectures can be optimized for energy efficiency while supporting demanding applications like air pollution monitoring and renewable energy integration. Their work on machine learning applications spans multiple domains including wind energy forecasting, IoT data collection, and vehicular edge computing. The research demonstrates a consistent theme of applying computational intelligence to solve real-world environmental challenges. The publication record reveals a strong trajectory in both theoretical and applied research. Early work focused on network function virtualization and edge computing infrastructure, while more recent publications show increasing emphasis on environmental applications including air pollution monitoring, wind energy analysis, and climate-related computing challenges. The research demonstrates a clear evolution toward addressing sustainability challenges through advanced computing techniques, with recent publications heavily featuring Norwegian environmental contexts. Best Paper Award of IEEE/ACM IWQoS 2019 National Scholarship of China for PhD First-class Academic Scholarship Outstanding Graduate Award Excellent Student Cadre Scholarship Zhang serves as a guest editor for Journal Symmetry's Special Issue on Applications based on Symmetry in Machine Learning and Data Mining. They are actively involved in multiple research projects funded by the Research Council of Norway, including HAPADS, MISO, EMLEMS, eX3, DILUTE, and AirQMan. These projects represent significant funding commitments to advance computing technologies for environmental monitoring and energy efficiency. Zhang is also a member of the Arctic Green Computing (AGC) research group at UiT. Based at UiT's Department of Computer Science in Tromsø, Zhang collaborates with the Arctic Green Computing research group and maintains active connections with University of Oslo's Department of Informatics. Their research environment bridges theoretical computer science with practical environmental applications, leveraging Norway's unique position in Arctic research and renewable energy development. The recent guest researcher position at Karlsruhe Institute of Technology further demonstrates their international research network and collaborative approach.
Christian Walter Peter Omlin is a Professor at the Department of Information and Communication Technology, University of Agder. He holds an honorary position at the University of South Africa and has held academic roles across institutions in South Africa, Cyprus, and Fiji. His expertise spans artificial intelligence, machine learning, and ethical AI. Omlin’s research emphasizes explainable AI, reinforcement learning, and applications in Industry 4.0, healthcare, and particle physics monitoring. He leads projects like the Telkom/Cisco Center for IP Computing and has contributed to virtue ethics in AI agent design. Education: PhD from Rensselaer Polytechnic Institute (1995), M.Eng from ETH Zurich (1987). Research Highlights: Developed affinity-based reinforcement learning (ab-RL) for interpretable AI agents. Advanced data quality monitoring (DQM) for CERN’s CMS detector using time-aware deep learning. Explored virtue ethics in AI through role-playing agents and ethical dilemma modeling. Teaching: Courses include Principles of AI, Algorithms, Urban Computing, and Digital Health. Grants/Advising: Led the Telkom/Cisco Center and the South African Innovation Fund’s “HearSEE” consortium. Supervised theses at multiple universities. Labs/Teams: Involved in CERN’s HCAL detector anomaly detection and dental radiology AI applications.
Bernhard Fäßler is a Researcher at the University of Agder's Department of Engineering Sciences since 2018. His work focuses on stationary battery storage systems, repurposing electric vehicle batteries for grid balancing, and embedded systems programming. He has taught courses in MATLAB, battery systems, and energy projects. His research bridges renewable energy optimization, grid stability, and circular economy principles. Education and Background: PhD in Renewable Energy (University of Agder, 2018) Master's in Ultrashort-pulse Laser Machining (Vorarlberg University of Applied Sciences, 2014) Bachelor's in Automotive Engineering (Vorarlberg University of Applied Sciences, 2012) Research Interests: Second-life battery utilization for grid services Autonomous energy storage optimization Circular business models for lithium-ion batteries Decentralized demand-side management Recent Research Trends: His work emphasizes economic viability of battery storage systems, integration of repurposed EV batteries into grids, and policy frameworks for sustainable battery recycling. Recent studies explore hybrid storage systems and circular economy applications. Lab Affiliations: Battery Coast and Battery Recycling groups at UiA.
Kristjon Ciko is a Research Fellow at the University of Oslo's Faculty of Mathematics and Natural Sciences, affiliated with the Department of Informatics under the Networks and Distributed Systems group. His work focuses on advancing network architectures and distributed systems. Research Interests: Ciko's research spans network architecture, particularly Recursive InterNetwork Architecture (RINA), congestion control mechanisms, and energy-efficient computing. His studies address challenges in next-generation network design, throughput optimization, and sustainable computing systems. Publications: Recent work includes innovations in energy efficiency for throughput computing, software-based server energy management, and congestion control solutions for datacenter networks. His research bridges theoretical advancements with practical implementations.
Michael Kampffmeyer is a 33-year-old Professor at the Machine Learning Group at UiT The Arctic University of Norway in Tromsø, where he researches the development of deep learning algorithms that learn with limited data and their explainability. Born in 1991 in Hamburg, Germany, he developed an early relationship with Norway through family holiday trips, spending six months as an exchange student in Alvdal at age 15 before completing high school in the UK. Remarkably, just 14 years after beginning his integrated master's degree in Energy, Climate and Environment at UiT at age 18, he achieved the position of professor. Kampffmeyer's research focuses on addressing two critical challenges in contemporary AI: the interpretability aspect and the inefficient training processes that require massive amounts of data, computing power, and energy. His work aims to develop more efficient and explainable AI models that can function effectively with limited data, with particular applications in medical image analysis where he collaborates with Universitetssykehuset Nord-Norge (UNN). His team has grown significantly from 5 to around 35 members since he began his PhD in 2015. The analysis of Kampffmeyer's recent publications reveals a strong focus on medical imaging applications, particularly in cardiac analysis and mammography, alongside work on making AI models more efficient and explainable. His research spans few-shot learning techniques for medical image segmentation, uncertainty modeling in graph networks, and super-resolution techniques for satellite imagery. A consistent theme across his work is the development of methods that require less data while maintaining or improving performance, addressing his core research mission of creating more efficient AI systems. Kampffmeyer is actively involved in securing significant research funding, with his team working on a proposal to join a new national AI center that would distribute approximately 200 million NOK, with a substantial portion allocated to UiT. He emphasizes the importance of international visibility, recognizing that continued representation at major international conferences is essential for maintaining their position at the forefront of AI research. His vision for the future of AI includes multimodal approaches that incorporate various types of data beyond just text and images, inspired by how humans use multiple senses to understand the world.
Olav Aaker is an Associate Professor at the Department of Engineering at Østfold University College (now part of Høgskolen i Østfold/HIOF), located in Fredrikstad, Norway. His academic roles include serving as Program Coordinator for Mechanical Engineering and Chair of the Departmental Board of Engineering. He holds a PhD in Process Automation and has extensive professional experience in both academia and industry, including research fellowships at Telemark University College/NTNU and SINTEF MARINTEK. His research interests span Alternative Energy, Battery Technology, Mechanical Engineering, Control Engineering, Production Technology, LNG Utilization, and Stirling Engines. Key projects include collaborations with Beijing Jiaotong University and Hebei Geo University, focusing on energy recovery systems and sustainable technologies. Aaker's work emphasizes innovative approaches to energy storage, such as thermo-mechanical systems challenging traditional battery solutions, and the integration of LNG heat recovery with desalination processes. His publications highlight contributions to flow boiling performance analysis, osmotic energy systems, and computational studies of electromagnetic motors. Notable works include studies on geothermal energy in Norway and exergy recovery in LNG evaporators. Aaker has also explored micro-power generation and material recycling in construction, reflecting his broad expertise in sustainable technologies. Awarded no specific scientific awards are listed, but his active involvement in research groups like Green Energy and collaborative projects underscores his academic impact. He advises no formal students in the provided texts, but his interdisciplinary work likely involves student collaborations in energy and mechanical systems.
Håkon Kvale Stensland is an Associate Professor in the Department of Networks and Distributed Systems at the University of Oslo (UiO), affiliated with Simula Research Laboratory. His work focuses on multimedia systems, machine learning applications in medical imaging and sports analytics, distributed computing, and GPU optimization. He has contributed to projects like HyperKvasir (a gastrointestinal dataset) and SmartIO (PCIe networking for device sharing). Key research areas include real-time video processing, 3D convolutional neural networks for event detection in soccer, and energy-efficient multimedia workloads. He has co-authored over 50 publications in venues like ACM Multimedia, IEEE Transactions, and Nature Communications. His tools and datasets, such as Saga and Bagadus, emphasize collaborative machine learning and real-time sports analytics. Recent work (2024-2025) explores prompt generation for medical segmentation and multi-host device sharing in high-performance clusters. His research bridges theoretical computer science with practical applications in healthcare, sports, and distributed systems.
Alhassan Yakubu Alhassan is an Assistant Professor at the Department of Global Development and Planning, University of Agder. He holds a PhD from the University of Agder, focusing on actor networks in urban decision-making, and has advanced degrees in Sociology (MSc, University of Saskatchewan) and Global Development and Planning (MSc, University of Agder). He earned a BA (Hons) in Sociology and Social Work from Kwame Nkrumah University of Science and Technology (KNUST), Ghana. PhD in Development and Planning, University of Agder (2025) MSc in Sociology, University of Saskatchewan (2016) MSc in Global Development and Planning, University of Agder (2014) BA (Hons) in Sociology and Social Work, KNUST (2012) His research spans political ecology, sustainable development, and urban sociology, with a focus on governance structures, social participation, and inclusion. He employs computational social science and social network analysis to study how power dynamics influence knowledge and resource distribution in urban projects. Recent publications emphasize actor-network theory in road expansion, social capital in decision-making, and policy impacts in African agriculture and urban finance. Alhassan contributes to academic discourse through peer-reviewed journals like the Journal of Urban Affairs and SN Social Sciences , as well as book chapters in transdisciplinary learning and digital methodologies. He teaches courses on political ecology of environmental challenges, research methods, and sustainable transformation, and is affiliated with the Center for Digital Transformation (CeDiT).
Knut Erik Teigen Giljarhus is an Associate Professor at the University of Stavanger's Faculty of Science and Technology within the Department of Mechanical and Structural Engineering and Materials Science. Appointed to a full-time faculty position in 2018 after transitioning from industry roles, he currently serves as Study Program Leader for Mechanical Engineering programs since 2020. Education: PhD from the Norwegian University of Science and Technology (NTNU) Research Interests: His primary expertise lies in Computational Fluid Dynamics (CFD) , with significant contributions to multiphase flow systems (oil/water separation, annular displacements), urban aerodynamics (pedestrian wind comfort, building interactions), and biomedical fluid applications (blood pumps, vascular flow). He employs advanced numerical methods including lattice Boltzmann modeling, large eddy simulations, and machine learning integration for rapid wind prediction. Publication Trends: Analysis of his 2024-2025 output reveals strategic expansion into ML-enhanced CFD for urban wind assessment while maintaining core multiphase flow research. Key themes include non-Newtonian fluid behavior in medical contexts, density-unstable displacement mechanisms, and aerodynamic optimization for sports engineering—all published in high-impact journals like Physics of Fluids and Building and Environment . Scientific Awards: No awards or fellowships were documented in the provided materials Advising and Grants: Formal advisees are not listed in the source material No research grants or funding sources are explicitly mentioned Labs and Teams: As Study Program Leader, he directs mechanical engineering curriculum development at the University of Stavanger. His research leverages the Department's computational facilities and collaborates with SINTEF Energy Research (evidenced in publications) alongside international partners in biomedical engineering and urban wind studies.
Professor Souman Rudra is a faculty member at the Department of Engineering Sciences within the University of Agder (Norway) since 2022. He holds a Ph.D. in Energy Technology from Aalborg University (Denmark, 2013) and has served as Associate Professor (2013-2022) and Visiting Researcher at the University of Alberta (2012). His career spans institutions including Aalborg University, Ajou University, and CUET. Education : Ph.D. (Aalborg University, 2013), MSc (Aalborg University, 2010), BSc (Chittagong University, 2007) Pedagogical Training : Uniped courses, doctoral supervision qualifications, and lecturing skill development His research focuses on renewable energy systems with specialization in biomass conversion, thermal energy, quad-generation plants, and process simulation. Recent studies emphasize hydrodynamic cavitation for biomass processing, hydrogen production from waste, and advanced battery material development. His publications bridge chemical engineering, energy systems, and material science with applications in: Biofuel production from lignocellulosic materials Quad-generation system optimization Photocatalytic energy storage solutions Machine learning applications in thermal plants Industrial waste-to-energy technologies Current teaching responsibilities include courses on: ENE 415: Combined Heat and Power Systems ENE 227: Thermodynamic and Heating System ENE 230: Fluid Flow and HVAC System ENE 420: Bioenergy
Raul Ferrer Conill is a Professor in Journalism at the Department of Media and Social Sciences, Faculty of Social Sciences, University of Stavanger (UiS), Norway. His work bridges media sociology, institutional theory, and digital technology, with a strong focus on datafication, audience engagement, and the transformation of journalistic practices. He leads the interdisciplinary Digital Society Research Group and is a key researcher in a Research Council of Norway-funded project on media policy and digital infrastructures. Research Interests: His research explores how digital platforms, data metrics, and gamification reshape journalism. He investigates how social processes are quantified and instrumentalized, particularly focusing on engagement metrics, native advertising, and the erosion of journalistic autonomy. His work critically examines digital infrastructures, platform power, and the implications for democratic communication and media policy in Nordic welfare states. Publication Trends: Over the past decade, Ferrer Conill’s publications reveal a consistent trajectory from early work on gamification in journalism to current critical analyses of datafication, platform capture, and infrastructural dependencies. His research increasingly emphasizes the political economy of digital media, regulatory challenges, and the reconfiguration of public communication. Scientific Awards: Bob Franklin Journal Article Award (Taylor and Francis) Honorable Mention, Wolfgang Donsbach Outstanding Article Award (ICA) Best Dissertation Award (Swedish Media and Communication Research Association) Top Faculty and Top Student Paper Awards (ICA) Honorable Mention, Best Teacher Award (Karlstad Student Association) Advising and Grants: While no formal students are listed, he actively mentors through research projects and supervises within PhD and master’s programs. He currently leads a major research project funded by the Research Council of Norway on datafication and media policy. His leadership in the Digital Society Research Group fosters collaborative, interdisciplinary scholarship across methodological traditions. Labs and Teams: He leads the Digital Society Research Group at UiS, an interdisciplinary collective focused on the societal implications of digital transformation. He frequently collaborates with scholars such as Helle Sjøvaag, Michael Karlsson, and Steen Steensen on projects analyzing digital infrastructures, platform power, and journalistic change.
