Dr. Ngoc Nha Vi Tran is an Associate Professor of Computer Science at UiT The Arctic University of Norway. She holds a PhD from UiT and was a visiting scholar at Rutgers University, USA. Her research focuses on high-performance and energy-efficient computing, machine learning, and bioinformatics. She is a member of the NORA.startup Steering Group and leads the Arctic Green Computing Group. Education: PhD in Computer Science (UiT), M.Sc. in Software Engineering via Erasmus Mundus (Blekinge Institute of Technology, Sweden & Technical University of Kaiserslautern, Germany). Research interests include energy-efficient algorithms, bioinformatics tools (e.g., vCOMBAT), and applications of machine learning in healthcare and robotics. She teaches courses such as INF-2200 Computer Architecture, INF-2900 Software Engineering, and INF-2202 Concurrent Programming. Her work spans computational models for antibiotic target-binding, runtime energy optimization (REOH framework), and power models for embedded systems (RTHpower/ICE). She contributed to the EXCESS project on energy-efficient computing systems. Labs/Teams: Arctic Green Computing Group, EXCESS consortium.
Gwenn Peron is a Professor in Structural Geology at the Department of Geoscience, Norwegian University of Science and Technology (NTNU). Their research focuses on rifted margin architecture, extensional tectonics, and the interplay between tectonics and magmatism. Key areas of expertise include seismic interpretation, numerical modeling, and structural analysis of continental margins. Research interests emphasize the evolution of rifted margins such as the Mid-Norwegian and Angola-Gabon margins, with particular attention to crustal deformation, fault system dynamics, and the influence of pre-existing orogenic structures. Methodologies include geophysical data analysis, field mapping, and computational modeling. Publications span structural geology, tectonics, and geophysics, with notable contributions to understanding rift heterogeneity, detachment fault systems, and the geodynamic processes governing continental breakup. Recent work highlights the role of orogenic inheritance in shaping margin architecture. Teaching responsibilities include advanced courses in tectonics, structural geology, and petroleum geoscience. Active collaborations with industry and academic partners focus on applied structural analysis of hydrocarbon basins and continental margin evolution.
Mina Mirhosseini is a Research Fellow at the Faculty of Logistics, Molde University College, Norway. She holds a PhD in Computer Science from Shahid Beheshti University of Tehran, Iran, and has prior academic experience as a faculty member and lecturer in Iran and as a remote teaching assistant at the University of Hertfordshire, UK. Her primary research interests include Optimization Methods, Metaheuristics, Heuristics, Linear Integer Programming, Parallel Processing, Machine Learning, Artificial Intelligence, and Logistics. She has made significant contributions to solving complex computational problems such as the n-similarity problem and Mixed Integer Linear Programming (MILP) models using hybrid and parallel algorithms, particularly in the context of high-level synthesis and wireless sensor networks. The analysis of her recent publications reveals a strong focus on developing and applying advanced optimization techniques, especially quantum-inspired gravitational search algorithms and parallel genetic algorithms, to real-world engineering and computational challenges. Her work consistently emphasizes performance improvement, scalability, and load balancing in distributed and heterogeneous computing environments. Mina Mirhosseini has an extensive publication record in high-impact journals such as IEEE Transactions on Parallel and Distributed Systems, Journal of Parallel and Distributed Computing, Journal of Supercomputing, and Computers and Electrical Engineering. Her research has been published across a range of venues, reflecting interdisciplinary work at the intersection of computer science, electrical engineering, and applied optimization. She has actively contributed to the academic community through roles such as program committee member and executive committee member for conferences on fuzzy systems, swarm intelligence, and evolutionary computation. Her academic journey includes teaching and research roles in Iran, demonstrating a sustained commitment to higher education and scientific inquiry. Mina Mirhosseini is part of the research group focused on Planning, Optimization and Decision Support at Molde University College. Her current work continues to advance the state-of-the-art in parallel and metaheuristic optimization methods, with applications in logistics, synthesis, and sensor network design.
Dag Johansen is a Professor in the Department of Informatics at UiT The Arctic University of Norway, Tromso campus. His work spans multiple research areas at the intersection of computer science, sports science, medicine, health technology, and nutrition science. He leads the interdisciplinary "Corpore Sano" research center and is actively involved in several research groups including the Cyber Security Group (CSG) and Crime Control and Security Law. Professor Johansen's research focuses on developing fundamental software solutions for secure and error-free data processing in heterogeneous distributed systems, ranging from lightweight "Internet of Things" devices and mobile phones to large-scale cloud solutions. His work particularly emphasizes applications in sports technology, edge computing, and compliance technology. His research interests include distributed systems, cybersecurity, sports technology, edge computing, data privacy, AI for sports analytics, multimedia forensics, and compliance technology. His recent publication trends show a strong focus on AI applications for sports video analysis, particularly in soccer and ice hockey, where his team has developed AI-based cropping systems for social media representations. He also has significant work in data privacy and GDPR compliance, especially regarding the "third country problem," as well as applications of AI in sustainable fishing practices. His 2024-2025 publications demonstrate continued work in self-healing microservices, lightweight encryption for video feeds, and virtual reality training environments. Professor Johansen is actively involved in mentoring students and research collaborators, as evidenced by his extensive publication record with numerous co-authors including doctoral students and postdoctoral researchers. His work has received funding through various research projects focused on data analytics, privacy technology, cybersecurity, and sports technology applications. He leads the interdisciplinary "Corpore Sano" center, which brings together researchers from computer science, sports science, medicine, health technology, and nutrition science. His work also involves collaboration with the "Njord" project focused on sustainable fishing through AI applications, and he's involved in developing the "Áika" distributed edge system for AI inference.
Amir Taherkordi is a Professor in the Networks and Distributed Systems group at the Department of Informatics, University of Oslo, Norway. His research focuses on resource-efficiency, scalability, adaptability, and mobility in distributed systems for emerging technologies like IoT, Fog/Edge/Cloud Computing, and Cyber-Physical Systems (CPS). University: University of Oslo Department: Informatics Academic Rank: Professor His research spans IoT, Edge/Fog Computing, and Cyber-Physical Systems, emphasizing energy efficiency, privacy preservation, and self-adaptive architectures. Key areas include network traffic classification, computation offloading, and federated learning applications in vehicular systems. Recent publications highlight advances in latency-aware IoT data transmission , federated vehicular networks , energy-efficient wireless charging , and privacy-preserving data integration . These works often integrate machine learning with network optimization. Projects include the CPS Lab at UiO, DILUTE (Fluid Service Abstraction), and the Gemini Centre on IoT . He collaborates on initiatives like PACE for energy informatics curricula development.
Karl-Johan Malmberg is a Professor at the University of Oslo , affiliated with the Faculty of Medicine and leading research at the Radiumhospitalet . His work focuses on Natural Killer (NK) cell biology and precision immunotherapy , with a strong emphasis on cancer immunology , HLA-KIR interactions , and cell therapy engineering . He collaborates extensively with the PRIMA - Precision Immunotherapy Alliance and contributes to translational research in hematopoietic stem cell transplantation and solid tumor immunotherapy . Expert in NK cell education and functional reprogramming Develops allogeneic cell therapies for leukemia and multiple myeloma Pioneers single-cell and high-dimensional analysis of immune compartments Recent publications highlight innovations in NK cell migration inhibition via GPR56, NKG2A/C switch receptors , and nanoparticle-enhanced NK cell activation . His team drives computational tools like MetaGate for cytometry data integration. Key affiliations include the Research Council of Norway Center of Excellence (PRIMA) , with a focus on cell therapy translation and tumor immune microenvironment mapping .
Marita Jenssen is a Senior Lecturer in Skin and Venereological Diseases at the Department of Clinical Medicine , UiT The Arctic University of Norway. Her research focuses on inflammatory skin disorders, particularly psoriasis, and the interplay between vitamin D metabolism and disease epidemiology. Recent studies highlight her work in: Genetic and environmental risk factors for psoriasis miRNA profiling in psoriatic skin Vitamin D supplementation trials for skin disease management Her research spans molecular biology, clinical dermatology, and population health in Arctic regions. Key collaborative efforts include: Dermatoplastic Imaging Research Group Chronic Disease Epidemiology Group
Kjell Arne Brekke is a Professor in the Department of Economics at the University of Oslo, Faculty of Social Sciences. He is actively engaged in research and teaching, with a strong focus on behavioral, environmental, and resource economics. He is affiliated with the Centre for Equality, Social Organization, and Performance (ESOP) and the Health Economics Research Network (HERO). His office is located at Eilert Sundts hus, Moltke Moes vei 31, and he is available on Wednesdays from 10:00–11:00 or by appointment. Dr. Polit. in Economics, University of Oslo, 1990 Cand. scient. in Mathematics, University of Oslo, 1983 His primary research interests include Behavioral Economics , Experimental Economics , Environmental and Resource Economics , and Real Options with Stochastic Analysis . His work investigates how moral motivation, social norms, and psychological factors influence economic decisions, particularly in contexts involving public goods, climate change, and inequality. He explores how individuals respond to framing, scarcity, and social expectations in cooperative settings. The recent articles highlight a consistent research trajectory centered on social preferences , moral motivation , and behavioral responses to environmental and public policy challenges . Themes such as polarization, cooperation under scarcity, framing effects, and the measurement of health and income inequality recur across publications. His methodological approach blends theoretical modeling with experimental and empirical analysis, often addressing policy-relevant questions in sustainability and welfare economics. While no specific awards are listed in the provided text, his sustained publication record in top journals like Journal of Public Economics , Ecological Economics , PNAS , and Land Economics reflects significant scholarly impact. Kjell Arne Brekke has supervised numerous students, though specific names are not provided. He has held leadership roles, including Chair of the Master’s Thesis Committee since 2010. His research has been supported by projects such as ESOP and collaborations with institutions like Statistics Norway and Stanford University. He has contributed to modeling uncertainty in energy markets and analyzing the behavioral foundations of green production and consumer choices. He is actively involved in research groups including ESOP and HERO, which focus on equality, social organization, health economics, and performance. These affiliations support interdisciplinary research on welfare, inequality, and sustainable development.
Clinton Phillips Conrad is a Professor of Mantle Dynamics at the University of Oslo's Department of Geosciences and Centre for Planetary Habitability. His research focuses on understanding Earth's dynamic interior through 3D modeling of mantle deformation, constrained by seismic/geodetic observations and geological indicators. He studies interactions between Earth's interior and surface processes including topography, plate motions, volcanism, and climate change. Research Interests Conrad's group develops advanced models examining how mantle dynamics influence surface environments. Key research areas include: Mantle geodynamics and deformation mechanisms Interactions between deep Earth processes and surface topography/volcanism Impacts of ice mass changes on solid Earth deformation Seismic and magnetotelluric constraints on mantle properties Evolution of plate tectonics and continental stability His work integrates geophysical observations with computational modeling to understand planetary habitability. Publication Analysis Conrad's recent publications (2021-2025) demonstrate a strong focus on: Mantle water distribution and its role in volcanism Glacial-isostatic adjustment and ice sheet interactions Anisotropic viscosity and mantle rheology Plume-lithosphere interactions in continental settings Cratonic stability mechanisms Sea level and paleogeographic reconstructions Methodologically, his work combines numerical modeling with seismic, geodetic, and magnetotelluric data analysis. Projects and Leadership Conrad leads several major research initiatives: ANIMA: ANIsotropic Viscosity in MAntle Dynamics ERC Starting Grant: DYNAMICE (ice-mantle dynamics interplay) MAGPIE: Magnetotelluric Analysis for Greenland and Postglacial Isostatic Evolution POLARIS: Evolution of the Arctic in deep time He maintains the MAGPIE blog documenting field research and maintains a research group developing mantle convection models.
Manuela Zucknick is Professor and Director of the Oslo Centre for Biostatistics and Epidemiology at the University of Oslo's Faculty of Medicine, Department of Biostatistics. Her research integrates statistical learning with translational cancer research to advance personalized medicine through multi-omics data integration. PhD Biostatistics, Imperial College London (2008) MSc Bioinformatics, Imperial College London (2004) Diplom Statistik, University of Dortmund (2003) Her research focuses on Bayesian methods for integrating heterogeneous data sources in cancer research, particularly for drug response prediction in pharmacogenomic screens and patient prognosis. She develops structured high-dimensional regression models for 'large p, small n' problems in molecular medicine, with emphasis on incorporating prior biological knowledge into risk prediction frameworks. Her work bridges statistical methodology with clinical applications in personalized cancer therapies. Her recent publications demonstrate consistent contributions to multi-omics integration and survival modeling across diverse clinical contexts including cancer, pregnancy complications, and rheumatoid arthritis. The research shows strong methodological innovation in handling high-dimensional biological data while maintaining clinical relevance. Through the Oslo Centre for Biostatistics and Epidemiology, she leads collaborative projects spanning oncology, obstetrics, and rheumatology. Her work frequently involves designing statistical frameworks for pharmacogenomic screens and developing tools for biomarker discovery in complex disease settings.
Gudmund Horn Hermansen is an Associate Professor at the University of Oslo, affiliated with the Department of Mathematics within the Faculty of Mathematics and Natural Sciences. His research focuses on advanced statistical methodologies, including Bayesian analysis, time series modeling, and applications in fields such as conflict dynamics, neuroscience, and environmental science. He is a member of the Statistics and Data Science research group and collaborates with interdisciplinary teams on projects involving uncertainty quantification and statistical inference. Key research interests include change-point analysis, hidden Markov models, astrocytic calcium signaling in Alzheimer’s research, and probabilistic forecasting. His work bridges theoretical statistics with practical applications, such as analyzing democratization processes and reservoir parameter interactions. Hermansen has contributed to over 30 peer-reviewed publications, emphasizing methodological innovations and interdisciplinary collaborations. Notable publications include studies on Bayesian hidden Markov models in conflict research, astrocytic signaling mechanisms in sleep regulation, and statistical frameworks for temporal heterogeneity analysis. He maintains an active role in academic service, including editorial contributions and conference participation.
Omid Vakili Ebrahimi is a Researcher at the Department of Psychology, University of Oslo, and affiliated with PROMENTA and Modum Bad Psychiatric Hospital. He specializes in clinical psychology, psychiatric epidemiology, and complex systems modeling of mental health. Education: Cand.psychol. (University of Bergen, 2019), with visiting scholarships at Oxford, Amsterdam, Berkeley, Boston, and Hong Kong Key research areas: Mental health during pandemics, individual differences, network analysis, precision psychiatry, and integration of idiographic/nomothetic perspectives His work applies complex systems approaches to understand depression/anxiety dynamics during the COVID-19 pandemic, focusing on resilience, transdiagnostic mechanisms, and behavioral adherence to mitigation protocols. He has pioneered network models for mental health symptom interactions and developed scalable interventions. Recent publications (2024-2025) demonstrate strong trends in: Network analysis of mental health symptom dynamics Vaccination hesitancy modeling Pandemic-related psychological distress Cross-national mental health comparisons Digital well-being research Integration of computational methods in psychiatry Scientific recognition includes: International Council of Psychologists Early Career Award (2022) ABCT Mentorship Award (2022) Department of Psychology Research Dissemination Award (2020) Section Editor for The Great Norwegian Encyclopedia (2021-present) As a graduate student in the Norwegian Double Ph.D. Program, he investigated complex systems approaches to mental health disorders under advisors Sverre Urnes Johnson, Asle Hoffart, Ole Andre Solbakken, and Daniel J. Bauer. He teaches advanced psychopathology assessment and research communication.
Professor Talal Rahman is a faculty member at the Western Norway University of Applied Sciences, where he works in the Department of Computer Science, Electrical Engineering and Mathematical Sciences. His office is located at Bergen KRONSTAD D305, and he can be reached at phone number +47 55 58 72 46. Professor Rahman's research spans several key areas in computational mathematics and scientific computing. His primary research interests include: Scientific Computing Numerical Analysis Numerical Methods for Partial Differential Equations Preconditioning Finite Element with Domain Decomposition Methods Variational Image Processing Artificial Intelligence and Machine Learning applications Professor Rahman's extensive publication record demonstrates a strong focus on domain decomposition methods, particularly Schwarz methods and their applications to multiscale problems. His recent work shows an increasing integration of machine learning techniques with traditional numerical methods, as evidenced by publications on neural network applications for environmental modeling and capelin migration patterns. His research also extends to biomedical applications, including computational analysis of biodegradable materials and bone tissue engineering scaffolds. He has made significant contributions to the development of adaptive preconditioners and parallel algorithms for solving complex numerical problems, with his work on the TV-Stokes model for image processing representing an important contribution to the field of variational image processing. Professor Rahman has supervised numerous research projects and students, though specific student names are not provided in the available information. His research appears to be supported by grants related to computational science and engineering, though specific grant details are not mentioned in the provided text. Based on his research areas, Professor Rahman likely collaborates with various research groups focused on computational science, with potential connections to biomedical engineering labs and environmental research teams studying the Barents Sea ecosystem.
Per-Olof Åstrand is a Professor in the Department of Chemistry at the Norwegian University of Science and Technology (NTNU), specializing in theoretical and computational chemistry. His research focuses on molecular modeling, quantum chemistry, and statistical thermodynamics with applications in dielectric materials and electrical engineering. Based at Realfagbygget, D3-119, Gløshaugen, he maintains active research collaborations with SINTEF Energy and Imperial College London. Åstrand's research interests center on theoretical models for molecular properties, intermolecular interactions, and molecular models of condensed matter. His work spans multiple domains including electrically insulating materials, non-linear optics, electrical conductivity, carbon dioxide chemistry, and lattice models in statistical thermodynamics. He develops both quantum mechanical and classical models to understand molecular behavior under various conditions, particularly focusing on electric field effects and molecular polarization phenomena. His recent publications reveal a strong emphasis on dielectric liquids, streamer propagation in electrical insulation, molecular ionization energy in external electric fields, and computational modeling of catalytic systems. The research combines theoretical development with practical applications in electrical engineering and materials science, showing consistent productivity with publications spanning from fundamental quantum chemistry to applied engineering problems. Åstrand actively contributes to education through teaching courses including TKJ4215 Statistical Thermodynamics in Chemistry and Biology (B.Sc. level), TKJ4205/KJ8902 Molecular Modeling (M.Sc./Ph.D. level), and KJ8205 Advanced Molecular Modeling (Ph.D. level). He has authored the textbook 'Atomistic Modeling: Concepts in Computational Chemistry' (Bookboon.com, 2016), which is available as a free PDF download. His research group offers numerous project opportunities for undergraduate and graduate students across various computational chemistry topics.
André Brodtkorb is a Professor and Head of the Department of Information Technology at Oslo Metropolitan University. His research spans applied mathematics, numerical analysis, and computational science, focusing on physics simulations and GPU computing. He advocates for open and reproducible research and is actively involved in education and societal engagement through the Academy of Young Researchers (2024-2028). Research Interests: His work integrates applied mathematics and computer science to develop high-performance simulations for environmental phenomena, including ocean currents, volcanic ash dispersion, and coastal flooding. He specializes in GPU-accelerated parallel computing, finite-volume methods, and Python-based scientific programming. Publication Trends: Recent articles highlight advancements in GPU computing efficiency, ocean modeling, and inverse ash transport modeling for volcanic plume forecasting. His research bridges computational methods with real-world environmental challenges. Scientific Awards: Member of the Academy of Young Researchers (2024-2028) Contact Information: Office: Pilestredet 35, 0166 Oslo Phone: +47 456 19 070 (Mobile), +47 672 35 924 (Office) Email: andre.brodtkorb@oslomet.no
