Inga Berre is a Professor at the Department of Mathematics, University of Bergen, and serves as Director of the Center for Modeling of Coupled Subsurface Dynamics (CSD). She leads the Porous Media Research Group and was appointed Argyris Visiting Professor at the University of Stuttgart's SimTech Cluster of Excellence in 2023. Research Interests: Mathematical modeling, partial differential equations, numerical methods for coupled thermo-hydro-mechanical-chemical processes in subsurface systems, and fault reactivation induced by injection/production. Scientific Leadership: Member of SIAM Council (2022-2027), Chair of SIAM GS activity group (2021-2022), Co-Chair of SET-Plan Deep Geothermal Implementation Working Group (2019-2021), and Chair of the Joint Program Geothermal, European Energy Research Alliance (2018-2021). Awards: 2011 Meltzer Award for Young Researchers. Advisory Roles: Member of Scientific Advisory Boards for GFZ (2024-2027) and SFB1313 (2018-), among others. Teaching: Developed courses on calculus, functional analysis, mathematical modeling, and numerical methods at the Bergen Summer Research School.
Behzad Alaei serves as an Associate Professor in the Section for Study of Sedimentary Basins within the Department of Geosciences at the University of Oslo's Faculty of Mathematics and Natural Sciences. His office is located in room K38 of the Geology Building at Sem Sælands vei 1, 0371 Oslo, with a professional email contact at behzad.alaei@geo.uio.no. Dr. Alaei maintains an active research profile with publications spanning from 2005 to the present, demonstrating his ongoing contributions to geological sciences. Dr. Alaei's research spans multiple critical areas within structural geology and sedimentary basin analysis, with particular expertise in fault zone architecture, seismic interpretation techniques, and CO2 storage site assessment. His work bridges theoretical geological concepts with practical applications in petroleum geology and carbon sequestration. A significant portion of his research focuses on the Norwegian Barents Sea region, where he has conducted extensive studies on normal fault systems and their geometric characteristics. His recent work increasingly integrates machine learning and deep learning approaches with traditional geological analysis, reflecting the evolving nature of geoscience research methodology. The analysis of Dr. Alaei's publication record from 2018-2024 reveals a strong thematic continuity in fault characterization research, with progressive incorporation of advanced computational methods. Early publications focused primarily on traditional structural analysis of fault systems in sedimentary basins, while more recent work demonstrates increasing integration of machine learning techniques for fault detection and characterization. A notable trend is the application of these geological insights to practical challenges in carbon capture and storage, particularly regarding fault risk assessment for CO2 storage sites in the North Sea region. His collaborative work with Anita Torabi appears consistently throughout this period, suggesting a strong research partnership. Dr. Alaei maintains an active research program with multiple ongoing projects related to sedimentary basin analysis and fault characterization. His work appears to involve significant collaboration with both academic and industry partners, particularly in the context of CO2 storage research. While specific grant details aren't provided in the available information, his consistent publication record across multiple high-impact journals suggests successful funding of his research activities over the past two decades.
Roger Flage is a Professor of Risk Management at the University of Stavanger, affiliated with the Faculty of Science and Technology and the Department of Security, Economics and Planning. His research focuses on foundational and applied aspects of risk analysis, uncertainty quantification, and decision-making under uncertainty, with applications in critical infrastructure, environmental systems, and offshore energy. Roger Flage's research interests lie at the intersection of risk science, safety engineering, and decision theory. He investigates how uncertainty—especially epistemic uncertainty and assumptions—affects risk assessments, and advocates for more transparent and robust frameworks. His work spans theoretical advances, such as the treatment of 'black swan' events and the concept of 'real risk', as well as practical applications in offshore safety, power systems, and geohazards. He emphasizes the integration of data-driven methods, AI, and digital twins while critically assessing their limitations and associated security risks. His recent publications show a strong trend toward integrating dynamic, data-rich, and interdisciplinary approaches to risk analysis. Themes include the role of time in risk, AI applications, infrastructure interdependencies, and environmental risk in the oil and gas sector. He frequently publishes in top-tier journals like Risk Analysis , Reliability Engineering & System Safety , and Safety Science , often in collaboration with leading scholars such as Terje Aven and Seth Guikema. No scientific awards are mentioned in the provided text. Roger Flage has supervised or collaborated with several researchers, though no formal list of advisees is provided. His work is supported through academic collaborations and institutional affiliations rather than explicit grant mentions. He is actively involved in advancing risk science methodology, particularly in the treatment of assumptions and uncertainty, and contributes to both theoretical foundations and real-world applications in safety-critical domains. He is associated with research groups and collaborative networks at the University of Stavanger, particularly within the Department of Security, Economics and Planning. His work often involves interdisciplinary teams focusing on risk in complex engineered systems, including energy, transportation, and environmental systems.
Vidar Hepsø is a Professor at the Department of Computer Technology and Informatics, Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology (NTNU). His work bridges anthropology of science and technology with practical challenges in digitalization, energy transition, and remote operations. Research focuses on digital infrastructures, socio-technical systems, and human factors in oil and gas industries Active in NTNU Applied Information Technology and NTNU Energy Transition Initiative Publications emphasize open-source ecosystems, autonomous systems, and environmental monitoring His scholarly output spans computer-supported collaborative work, IT infrastructure governance, and risk-informed anomaly detection in subsea systems. He leads projects connecting digital innovation with offshore wind and petroleum geoscience.
Benjamin Ricaud is an Associate Professor and Group Leader in Machine Learning at UiT The Arctic University of Norway's Department of Physics and Technology. His core affiliations include membership in the Machine Learning Group, Visual Intelligence center, and co-directorship of the Digital Technology Innovation Lab focused on Arctic-region tech startups. He also co-chairs the annual Northern Light Deep Learning conference. Ricaud's research spans: Fundamental ML : Graph signal processing, explainable AI, and generative models Applications : Microfossil classification, medical diagnostics (retinal aging), drug analysis, and climate data interpretation Emerging domains : Self-supervised learning and biological data analysis using Raman spectroscopy His recent publications (2020-2025) cluster in three domains: Graph ML methodologies (35%) Biomedical/biological applications (40%) Geoscience/climate informatics (25%) with consistent focus on interpretability and real-world data challenges. Teaching includes Image Processing (FYS-2010), Pattern Recognition (FYS-3012), and Machine Learning (FYS-2021). He leads outreach initiatives developing AI exhibits for Tromsø Science Centre.
Iver Martens is a University lecturer in the Department of Geosciences at UiT The Arctic University of Norway in Tromsø, actively contributing to geoscience education and work-integrated learning initiatives. He is a member of the Geophysics, Glaciology and Oceanography research group and serves as office location Naturfagbygget 2.234. His research interests focus on practical orientation in academic programs, particularly through internship initiatives that bridge geoscience education with industry needs. Martens has developed significant expertise in work-integrated learning, with particular emphasis on how internship programs prepare students for future workforce challenges in geoscience disciplines. His work explores the long-term impacts of practical training on student development and industry relevance of academic programs. Analysis of his publication record reveals a clear trajectory from traditional geoscience research toward educational innovation. While his earlier work (2016-2019) focused on seismic interpretation, petroleum systems, and Barents Sea geology, his recent publications (2021-2025) demonstrate a strong shift toward geoscience education, internship program design, and work-integrated learning frameworks. This evolution reflects his commitment to enhancing the practical relevance of geoscience education. Martens leads and participates in significant educational projects including GeoPraksis and GeoIntern International, which aim to strengthen the connection between academic geoscience training and industry requirements. His work examines mentorship challenges, quality parameters in internships, and the long-term career impacts of work-integrated learning experiences. His contributions to geoscience education have established him as a thought leader in practical orientation within academic programs, with particular expertise in designing internship frameworks that address future workforce needs in geoscience disciplines.
Eduard Kamburjan is a Researcher at the University of Oslo , affiliated with the Reliable Systems (PSY) and Data and Knowledge Systems (DKM) research groups. His work bridges formal methods , digital twin engineering , and knowledge graph applications . Research interests include: Formal verification of hybrid systems using deductive methods Digital twin architecture with compositional correctness guarantees Semantic lifting and ontology-driven modeling for complex systems Concurrency analysis and non-determinism in program verification Interactive visualization as serious games for formal methods His 2024-2023 publications demonstrate expertise in digital twin reconfiguration , semantic interoperability , and knowledge-based runtime enforcement . Key contributions include Crowbar for active object verification and ABS simulator toolchain for model-driven engineering. Collaborations span institutions like Springer , ACM , and IEEE , with work featured in Lecture Notes in Computer Science (LNCS) , Software and Systems Modeling (SoSyM) , and Science of Computer Programming . His research integrates RDF data management , behavioral contracts , and modular analysis for distributed systems.
Prof. Chong-Yu Xu is a Professor of Hydrology at the University of Oslo's Department of Geosciences, affiliated with the Section for Geography and Hydrology (GeoHyd). He has held this position since 2005, having previously served as an Associate Professor at Uppsala University (1998–2005) and Assistant Professor (1994–1998). His research focuses on hydrological modeling, climate change impacts, regional evapotranspiration, and uncertainty analysis. He teaches courses such as GEO4310 (Stochastic Methods in Hydrology) and GEO4320 (Hydrological Modelling). Education: BSc in Hydrology (Nanjing University, 1978–1982), MSc in Regional Hydrological Modeling (Free University Brussels, 1986–1988), and PhD in Hydrological Modelling (Free University Brussels, 1988–1992). He has been honored with prestigious awards, including the NHF Lifetime Achievement Award (2022) and IWA Publishing Award (2022). He serves as an honorary professor at institutions like Hohai University and is a doctoral supervisor at multiple universities. His research spans global, regional, and local hydrological modeling, with a focus on climate change adaptation and water resource management. He leads projects such as the NORHED-II initiative on climate change and ecosystem management in Malawi and Tanzania. His work bridges theoretical hydrology with practical applications, including flood risk reduction and hydropower optimization. Publications highlight advancements in hydrological extremes, non-stationary drought assessment, and AI-driven flood prediction. Collaborative efforts with international networks like the Nordic Hydrological Association underscore his global impact in hydrological sciences.
Åse Manengen is a part-time Lecturer at the Department of Geosciences, University of Oslo. She holds a 20% position and is affiliated with the Section for Geodidactics. Her work focuses on educational outreach through the department's school visit program, promoting geoscience engagement with schools. She joined the University of Oslo in 2024 in this role, contributing to science communication and public education initiatives within the geosciences. No formal awards or grants are listed in her profile, though her current activities emphasize community and educational collaboration.
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.
Ashkan Jahanbani Ghahfarokhi is an Associate Professor in Reservoir Engineering at NTNU’s Department of Geosciences since 2019. He leads the CEORS Gemini Centre (CO2 Enhanced Oil Recovery & Storage) and is a core member of the BRU21 Reservoir Management group. His research focuses on data-driven subsurface modeling, CO2 storage, and optimization of oil recovery processes. Education: PhD, NTNU (2015); MEng, University of Calgary (2009); MSc/BSc, Petroleum University of Technology, Iran (2006–2009). Roles: Head of Reservoir Engineering Group (2021–2022), Project Manager for NORHED II (2022), and NTNU’s Outstanding Academic Fellow (2022–2026). Research interests include CO2-EOR/Storage, machine learning applications, proxy modeling, and reservoir simulation. He has supervised 20+ students and published over 40 journal/conference papers. Awards include DNVA postdoc scholarship (2015–2017) and PoreLab postdoc (wettability studies). Teaching: Masters/PhD courses in reservoir fluids, simulation, and geomechanics. Guest editor for Energies (AI in Oil & Gas).
Alexey Pavlov is a Professor of Petroleum Cybernetics at the Department of Geosciences and Petroleum, Norwegian University of Science and Technology (NTNU). He holds an MSc in Applied Mathematics from St. Petersburg State University, a PhD in Mechanical Engineering from Eindhoven University of Technology, and has industrial R&D experience from Statoil and Ford Motor Co. Education: MSc (Applied Mathematics, St. Petersburg State University), PhD (Mechanical Engineering, Eindhoven University) His research focuses on control systems for petroleum engineering applications, including nonlinear control theory, iterative learning control, and data-driven optimization methods. Publications reveal a strong emphasis on real-time drilling optimization, well integrity monitoring, and synchronization in networked systems. Recent work trends include machine learning integration for oil well monitoring, moment matching in model reduction, and extremum seeking control for multi-agent systems. Collaborations span institutions like Ford Motor Co., Statoil, and Eindhoven University of Technology. Current affiliations include the Department of Geosciences and Petroleum at NTNU. No scientific awards or advisee information is explicitly mentioned in the provided texts.
Tom Arne Rydningen is an Associate Professor in the Department of Geosciences at UiT The Arctic University of Norway, specializing in Arctic marine geology. His research focuses on Cenozoic continental margin development, glacial history, and source-to-sink sedimentary systems in high-latitude environments. He actively contributes to understanding the evolution of the Arctic Ocean and its connections to global ocean circulation. Dr. Rydningen's research interests center on high-latitude continental margin development, particularly examining the large-scale evolution of ocean circulation in the Norwegian-Greenland Sea and Arctic Ocean during the Miocene. He investigates the buildup and retreat of marine-based ice sheets through the Quaternary in Fennoscandia, the Barents Sea, Svalbard, and northeastern Greenland. His work employs diverse methodologies including contourite studies , glacigenic deposits analysis , source-to-sink system modeling , and seismic stratigraphy using 2D/3D seismic data and multibeam echosounder data. Analysis of his 15 most recent publications reveals a strong focus on Arctic geological processes, particularly concerning the Barents Sea region. His work spans multiple disciplines including glaciology, paleoceanography, and sedimentology, with significant contributions to understanding Pleistocene glaciations, Cenozoic tectonic influences on sediment transfer, and microplastic pollution in Arctic marine sediments. Recent publications demonstrate increasing interdisciplinary approaches, connecting geological processes with contemporary environmental concerns. Dr. Rydningen is actively involved in several major research projects including DYPOLE (Dynamics of polar confined basins), Arven etter Nansen, TUNU, Euro-arctic marine fishes, iEarth, and GoNorth. He is a member of the Sedimentary Systems, Paleoclimates and Environments research group and contributes to science didactics in higher education. His teaching portfolio includes courses in marine geology, geological interpretation, and Arctic marine geology fieldwork. His research combines fieldwork, seismic data interpretation, and sediment core analysis to reconstruct past environmental conditions and ice sheet dynamics in the Arctic. This work has significant implications for understanding current climate change impacts on polar regions and provides crucial context for interpreting modern Arctic environmental changes.
Eirik Keilegavlen is a Researcher at the Department of Mathematics, University of Bergen. His primary research focuses on developing mathematical models, numerical methods, and simulation tools for multiphysics processes in porous media, particularly in geothermal energy, CO 2 storage, and subsurface energy systems. He leads the development of the open-source software PorePy, designed for simulating processes in fractured porous media. His work emphasizes coupled problems involving fluid flow, heat transfer, and mechanical deformation. Key research interests include: Mathematical modeling of coupled thermal-hydro-mechanical processes Numerical discretization methods for fractured media Development of open-source simulation tools Applications in geothermal energy extraction and carbon sequestration Recent publications highlight advancements in: Uncertainty quantification for CO 2 leakage Viscous fingering in fractured reservoirs Automated solver selection for multiphysics systems Collaborations involve interdisciplinary teams addressing challenges in geothermal reservoir stimulation, fault mechanics, and high-performance computing. His work bridges theoretical developments with practical applications in energy and environmental systems.
Isabelle Lecomte is a Professor in Reservoir and Near-Surface Geophysics at the University of Bergen's Department of Earth Science. Her research focuses on seismic modeling, reservoir characterization, and near-surface geophysics, with applications to paleokarst reservoirs, fault zone analysis, and archaeological geophysics. She has supervised numerous master's theses and contributed to projects funded by the Research Council of Norway. Her work integrates field observations, numerical modeling, and geophysical data interpretation to advance understanding of subsurface structures and processes. Affiliations: Department of Earth Science, University of Bergen Research Groups: Geodynamics and Basin Studies Research Interests: Development of seismic modeling techniques for reservoir characterization and near-surface imaging Application of ground-penetrating radar (GPR) in archaeology and environmental studies Seismic expression of faults, sand injectites, and carbonate systems Paleokarst reservoir dynamics and flow simulation Publications: Over 30 peer-reviewed articles focus on seismic modeling, subsurface imaging, and geohazard assessment. Recent work emphasizes 3D/4D seismic interpretation, fault zone analysis, and outcrop-subsurface analogues. Grants & Awards: Involved in projects funded by the Research Council of Norway, including studies on paleokarst reservoirs and CO2 storage feasibility. Advising: Supervised 14 master's students, with thesis topics ranging from seismic attribute analysis in archaeology to reservoir characterization of paleokarst systems.
