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Bastiaan StarView profile

Professor

• Ancient DNA
• Population Genomics
• Evolutionary Ecology
• +7 more

Bastiaan Star is a Professor at the Centre for Ecological and Evolutionary Synthesis (CEES) at the University of Oslo, where he leads research integrating ancient DNA, genomics, and evolutionary ecology to study historical environmental changes and human impacts on marine organisms. His work spans Atlantic walrus, cod, herring, and New Zealand snapper, examining genetic variation, population structure, and responses to human exploitation over centuries to millennia. Star's research focuses on ancient DNA analysis of archaeological material (hundreds to thousands of years old), collaborating closely with archaeologists and zooarchaeologists. Key interests include population genomics , local adaptation , thermal physiology , and bioinformatics development for degraded samples. His group investigates how long-distance trade networks, climate change, and fisheries exploitation have shaped marine biodiversity through time. His recent publications reveal trends in marine historical ecology , demonstrating how ancient DNA exposes millennial-scale population dynamics in exploited species. Work spans walrus ivory trade chronology, Atlantic bluefin tuna demographic collapse, puffin hybridization due to climate shifts, and medieval cod trade routes. This research combines high-throughput sequencing, computational biology, and interdisciplinary archaeological approaches. Star actively collaborates on major projects including: BEEDIVERSE: Wild bee conservation through functional ecology and genomics SeaChanges: Human exploitation thresholds in marine vertebrates The Impact of Art: Ancient DNA tracing historic walrus trade EvoCave: Population genomics of Atlantic puffins He leads the Archaeogenomics group at CEES, developing methodologies for ancient DNA extraction from challenging substrates like fish bones and degraded archaeological specimens. His work bridges molecular biology, ecology, and archaeology to reconstruct past ecosystems and inform conservation strategies.

• Robotics
• Intelligent Systems
• Reconfigurable Computing
• +3 more

Alexander Wold is an Associate Professor at the University of Oslo, affiliated with the Research Group for Robotics and Intelligent Systems within the Faculty of Mathematics and Natural Sciences. His work focuses on reconfigurable computing, embedded systems, and robotics, with notable contributions to FPGA design, real-time systems, and educational technology. He holds a position at the Institute of Informatics (IFI) and can be contacted at alexawo@ifi.uio.no . Research interests include optimizing hardware-software co-design, thermal management in 3D-IC systems, and developing open-source tools like EasyPR for pattern recognition. His publications span topics such as remote cloud labs for reconfigurable logic education, network traffic management in industrial Ethernet, and constraint programming for module placement in FPGAs. Dr. Wold’s articles reflect a strong emphasis on practical applications of robotics and intelligent systems, with a focus on safety-critical industrial systems and autonomic computing. He has contributed to multi-core system design, thermal-aware FPGA architectures, and self-aware systems.

• Remote Sensing
• Arctic Sea Ice Monitoring
• Environmental Monitoring
• +3 more

Malin Johansson is an Associate Professor and Group Leader of the Earth Observation group at the Department of Physics and Technology, UiT The Arctic University of Norway . Her research connects remote sensing with numerical modeling and in-situ data to advance understanding of Arctic sea ice properties , environmental monitoring (oil spills, harmful algae blooms), and multi-frequency SAR observations . She teaches courses like FYS-1009 (Climate and Environmental Monitoring), FYS-3001 (Physics of Remote Sensing), and FYS-3023 (Applied Remote Sensing). Research Focus : Arctic sea ice dynamics using SAR and optical imagery Environmental risk assessment (oil spills, algae blooms) Climate-ice-ocean interactions Machine learning for SAR data analysis Article Trends : Her recent work emphasizes multi-decadal SAR analysis of Arctic sea ice types, Lagrangian drift prediction for environmental hazards, cross-polar comparisons of ice classification methods, and incidence angle modeling for SAR calibration. Students : Truls Karlsen (Multi-Frequency Sea Ice Observations) Jakub Petříček (Permafrost Remote Sensing) Labs/Teams : Leads the Earth Observation group at UiT, collaborating with international institutions on projects like INTERAAC (Norway-China) and MOSAiC expeditions.

• Scientific Computing
• Applied mathematics
• Numerical methods
• +2 more

Marie E. Rognes is a Chief Research Scientist at Simula Research Laboratory's Numerical Analysis and Scientific Computing department. She specializes in computational mathematics and biomedical modeling, particularly focusing on cerebral fluid dynamics, electrodiffusion, and poroelasticity. Her work bridges advanced numerical methods with clinical applications in neuroscience. Research Pillars: Brain waterscape modeling, finite element methods, and biophysical simulations Software Leadership: Key contributor to FEniCS and Dolfin-adjoint projects Application Domains: Neurodegenerative diseases, cardiac electrophysiology, and personalized medicine Recent publications reveal methodological innovations in perivascular flow modeling , ionic transport simulations , and multi-scale brain mechanics . Her work on glymphatic system dynamics and cardiac tissue modeling demonstrates cross-disciplinary impact. While no explicit awards are listed, her extensive publication record in top-tier computational journals (SIAM, PLOS, Nature Computational Science) and invited talks at premier conferences (SIAM, ECCOMAS, FEniCS workshops) establish her as a leading figure in biomedical computing.

Maben RabiView profile

Professor

• Cyber-Physical Systems
• Networked Control
• Hybrid Systems
• +5 more

Maben Rabi is a Professor at the Department of Information Technology and Communication, University of Southeast Norway. His work focuses on cyber-physical systems, networked control, and hybrid systems with applications in intelligent transportation and robotics. Current projects: CriSp (Research Council) and SafeSmart (KK Foundation). Research keywords: Cyber-Physical Systems, Networked Control, Hybrid Systems, Digital Society, DigiTech. Research Trends : His recent publications emphasize road friction estimation for autonomous vehicles, nonlinear control in relay feedback systems, probabilistic sampling for networked estimation, and packet loss modeling in vehicular networks. These works bridge control theory, cyber-physical systems, and transportation safety. Teaching : Courses include Technology Project (ITD25018) and Digital Control and Cyber-Physical Systems (ITD30019) .

Phuong H. HaView profile

Professor

• Green Computing
• Energy-Efficient Systems
• Machine Learning
• +4 more

Phuong H. Ha is a Professor at the Department of Computer Science, The Arctic University of Norway (UiT), located in Tromsø, Norway. He leads the Arctic Green Computing Group and is affiliated with the Faculty of Science and Technology. His research focuses on energy-efficient computing systems, machine learning, parallel programming, and cyber-physical systems. He holds a Ph.D. from Chalmers University of Technology (Sweden). Key roles include leading EU-funded projects such as EXCESS (FP7) and TAILOR (H2020), as well as national projects like PREAPP and eX3. He has pioneered research in energy informatics, edge intelligence, and parallel programming systems. His work emphasizes sustainable energy solutions and efficient resource management in distributed systems. Teaching responsibilities include courses on Green Computing, Operating Systems, and Parallel Programming. He has developed innovative frameworks for energy harvesting in wireless devices and contributed to Arctic observational systems through projects like the Arctic Observatory (DAO). Research highlights include over 30 peer-reviewed publications in top venues like IEEE Transactions on Parallel and Distributed Systems and Journal of Parallel and Distributed Computing. His work bridges theoretical foundations with practical applications in smart grids, IoT, and environmental monitoring.

Julia RomanowskaView profile

Researcher

• Bioinformatics
• Epigenetics
• Statistical genetics
• +4 more

Julia Romanowska is a senior engineer and bioinformatician at the Department of Global Public Health and Primary Care, University of Bergen . She actively contributes to research projects including the DRONE (Drug Repurposing for Neurological Diseases) and START (Study of Assisted Reproductive Technology) initiatives. Romanowska co-founded R-Ladies Bergen to promote gender diversity in computational sciences. PhD in Theoretical Biophysics (University of Warsaw) Former postdoc at Institute of Genetic Medicine, University of Bergen Developed HaplinMethyl software for DNA methylation analysis Her research spans epigenetics , X-chromosome methylation , and drug-disease associations , with recent publications in Human Genomics and bioRxiv . Romanowska specializes in genetic association studies , computational modeling , and high-dimensional data analysis .

Einar Broch JohnsenView profile

Professor

• Programming Models
• Formal Methods
• Concurrency
• +3 more

Einar Broch Johnsen is a Professor at the Department of Informatics , University of Oslo . His research focuses on formal methods , distributed systems , and digital twins , with applications in cloud computing , robotics , and healthcare . Leadership: Strategy Director of SIRIUS (2015-2023), Coordinator of EU projects Envisage and HyVar . Community Roles: Board member of Formal Methods Europe , editorial board member of Formal Aspects of Computing , and chair of conferences like FM 2015 and FASE 2022 . His recent work explores symbolic execution , probabilistic logic , and self-adaptive systems , as reflected in his 15 most recent publications . He teaches courses such as IN2031 – Project in Programming and IN5170: Models of Concurrency .

• Condensed Matter Physics
• Superconductivity
• Spintronics
• +2 more

Morten Amundsen is a Postdoctoral Fellow in the Department of Physics at the Norwegian University of Science and Technology (NTNU), actively contributing to cutting-edge research in condensed matter physics. His work bridges theoretical and experimental approaches in superconductivity and spintronics, with affiliations centered at NTNU's physics department where he maintains active research and teaching roles. His research spans: Superconducting hybrid structures and quantum transport phenomena Spin-orbit coupling effects in topological materials Geometric curvature manipulation of magnetic and superconducting states Josephson effect engineering in novel geometries Antiferromagnetic spintronics and altermagnetism Analysis of his 15 most recent publications (2020-2025) reveals a dominant focus on the interplay between superconductivity and magnetism, particularly through spin-orbit coupling mechanisms. Key trends include geometric engineering of quantum states (via curvature and fractal structures), electrical control of superconducting spin valves, and exploration of Rashba altermagnets. His work frequently employs quasiclassical theory and Keldysh formalism to model complex hybrid systems, with strong emphasis on topological aspects and non-equilibrium phenomena. Dr. Amundsen maintains extensive collaborative networks, frequently publishing with NTNU researchers including Jacob Linder, Henning Goa Hugdal, and Sol Hernæs Jacobsen. His active conference participation—such as presentations at the European School on Superconductivity and Magnetism (2024) and New Avenues in Quantum Materials (2024)—demonstrates ongoing engagement with the international research community. While specific grant details aren't provided, his high publication output in premier journals indicates sustained research funding.

Anne C. ElsterView profile

Professor

• High-Performance Computing (HPC)
• Parallel Computing
• GPU Computing
• +6 more

Prof. Anne C. Elster is a Professor of Computer Science at NTNU's Department of Computer & Information Science (IDI), leading the HPC-Lab. She specializes in High-Performance Computing (HPC), GPU acceleration, and heterogeneous systems. Her work spans HPC applications in medical imaging, seismic processing, and oil & gas simulations, with collaborations at CERN, NVIDIA, and Schlumberger. Elster holds a PhD in Electrical Engineering from Cornell University (1994) and is an IEEE Senior Member since 2000. She has supervised over 70 master students and numerous PhD candidates, emphasizing GPU computing. Her teaching includes courses like Parallel Computing and Compilers , with a focus on programming and problem-based learning. She leads EU projects like CLOUDLIGHTNING (2015–2018) and has organized major conferences (e.g., ISC, SC, PARA). Her HPC-Lab is a CUDA Research and Teaching Center, and she advocates for HPC infrastructure investments in Norway through policy engagement.

• Fluid Dynamics
• Computational Fluid Dynamics
• Turbulence
• +3 more

Jørgen Røysland Aarnes is a Research Fellow at the Department of Energy and Process Engineering, Norwegian University of Science and Technology (NTNU). His research spans fluid dynamics, computational methods, and philosophy of science, with particular focus on turbulence, multiphase flows, and structural realism in Ernst Cassirer's philosophy. He completed his PhD in 2018 with a thesis on particle-laden flows impinging on cylinders. Research Interests: Computational fluid dynamics (CFD), including high-order methods and overset grids Turbulent flows and free-surface vortex structures Particle-laden flow dynamics and impaction mechanisms Philosophy of science, structural realism, and symbolic forms Recent Contributions: His 2025 work on free-surface vortex patterns and 2024 philosophical papers on Cassirer's symbolic forms demonstrate interdisciplinary expertise. He has developed computational tools like the Pencil Code for fluid simulations. Awards: No scientific awards explicitly listed, though his work has been presented at major conferences including the European Turbulence Conference and European Geosciences Union meetings. Advising & Grants: No explicit grants or advisees listed, though his PhD supervision experience is implied through his postdoctoral role. Labs/Teams: Collaborates with the Pencil Code Collaboration and NTNU's energy engineering research groups.

Xing CaiView profile

Professor

• Parallel programming
• High-performance computing
• Performance modeling
• +8 more

Xing Cai is a Professor at the Department of Informatics, University of Oslo, specializing in Scientific Computing and Machine Learning. His academic career spans several decades with a consistent focus on high-performance computing and its applications to complex scientific problems. He maintains an active research profile with numerous publications in top-tier journals and conferences. Professor Cai's research interests encompass parallel programming and high-performance computing, performance modeling and optimization, automated code generation, heterogeneous computing, and numerical methods for solving partial differential equations. His work extends to specialized applications in computational cardiology, computational geoscience, and biomedical computing. His research bridges theoretical computer science with practical applications in medicine and earth sciences, demonstrating exceptional interdisciplinary reach. An analysis of his recent publications (2019-2024) reveals a strong trend toward leveraging novel hardware architectures (GPUs, AI processors, specialized accelerators) for scientific computing, with particular emphasis on cardiac modeling applications. His work shows increasing sophistication in hardware-aware algorithm design, with publications spanning from fundamental performance modeling to domain-specific applications. The interdisciplinary nature of his work is evident in the diverse range of journals and conferences where he publishes, from computer science venues to specialized medical and geoscience publications. Professor Cai leads or participates in several significant research projects including the EuroHPC Centre of Excellence: Numerical Modeling of Cardiac Electrophysiology at the Cellular Scale (MICROCARD-2), High resolution simulation of cardiac electrophysiology on realistic whole-heart geometries, Maelstrom Associate Team, ODISSEE, Simula-Berkeley Education and Research collaboration (SIMBER), and aCG eX3: Experimental Infrastructure for Exploration of Exascale Computing. These projects reflect his leadership in both computational methodology development and domain-specific applications. His research group maintains strong collaborations with medical researchers, particularly in cardiac electrophysiology, and with geoscientists working on reservoir simulation. The publications list demonstrates consistent mentorship of junior researchers, with frequent co-authorship patterns suggesting an active supervision of PhD and postdoctoral researchers. His work on the EMI model for cardiac tissue represents a significant contribution to computational cardiology with potential clinical applications. The laboratory environment surrounding Professor Cai's work appears to be well-equipped for high-performance computing research, with access to advanced hardware platforms including GPU clusters, AI processors, and specialized accelerators. His publications on the use of Graphcore IPUs, Xeon Phi processors, and NVIDIA architectures indicate a well-resourced research environment capable of experimenting with cutting-edge hardware.

Hans A. WintherView profile

Associate Professor

• Theoretical Cosmology
• Large-Scale Structure Formation
• Modified Gravity
• +3 more

Hans A. Winther is an Associate Professor at the Institute of Theoretical Astrophysics, University of Oslo, specializing in theoretical cosmology with a focus on large-scale structure formation. He holds a Master’s (2010) and PhD (2013) from the University of Oslo, followed by postdoctoral research at the University of Oxford and the University of Portsmouth. His work bridges cosmological theory with advanced numerical simulations, emphasizing modified gravity, dark matter models, and N-body codes. Winther leads courses such as AST5220 Cosmology II and AST1010 Introduction to Astronomy , integrating computational tools like FML and MG-PICOLA . His research includes developing simulation frameworks for modified gravity (e.g., ISIS , SCALAR ) and axion-like dark matter. He actively contributes to the Euclid mission through simulations and data analysis, addressing nonlinear cosmological structures and parameter constraints. Notable projects include the FML C++ library for parallel grid-particle algorithms and the MG-PICOLA code for fast modified gravity simulations. His work underscores the interplay between theory and computation in cosmology, aiming to test gravity and dark matter hypotheses using observational data from surveys like Euclid and LSST.

Diana Sousa Marques SantosView profile

Professor

• Natural Language Processing
• Corpus Linguistics
• Translation Studies
• +4 more

Roles and Affiliations: Diana Sousa Marques Santos is a Professor of Portuguese Linguistics at the University of Oslo (UiO), affiliated with the Institute for European Languages, Literature, and Area Studies (ILOS) within the Faculty of Humanities. Since 2011, she has held positions as Associate Professor (until 2012) and subsequently Full Professor. Her research focuses on computational linguistics, corpus-based studies, and cultural analysis, particularly in the context of Portuguese and Lusophone literature. Education: She earned a 5-year engineering degree in Electronics and Computers from the Technical University of Lisbon (IST), followed by an MSc in Machine Translation and a PhD in contrastive corpus-based semantics, both from IST. Research Interests: Diana’s work spans computational processing of Portuguese, natural language processing, semantics, translation, and distant reading. She leads the Linguateca project, fostering computational resources for Portuguese and collaborates internationally with institutions like the University of Southern Denmark. Key projects include PANTERA (parallel corpus for Portuguese-Norwegian translation studies) and contributions to the European Literary Text Collection (ELTeC) for distant reading. Teaching: She teaches Portuguese grammar, linguistics, and cultural studies at undergraduate and graduate levels, including courses like Introduction to Statistical Thinking for PhD students. Her pedagogical efforts include co-authoring textbooks such as Viva! for Portuguese language education. Projects and Activism: Diana advocates for open-source software in academia, notably opposing the University of Oslo’s shift to Microsoft Exchange. She promotes Lusophone cultural studies and participates in initiatives like the BILLIG project (GIS and NLP in literary geography). Her work bridges computational methods and humanities, emphasizing interdisciplinary approaches. Labs and Teams: She contributes to research groups such as Digital Humanities, Grammar and Meaning Representations, and the Ibero-American Research Hub (IberoARH), fostering collaborative projects in language technology and cultural analysis.

Carsten GriwodzView profile

Professor

• Computer Networks
• Distributed Systems
• Network Security
• +5 more

Carsten Griwodz is a Professor in the Department of Informatics (IFI) at the University of Oslo, specializing in digital infrastructure and security. He leads the Distributed Infrastructure and Security (DIS) research group and contributes to several specialized labs including the Sustainable Immersive Networking Lab (SINLAB), Imagine Beyond 5G Blockchain Lab, and the AliceVision Association. Professor at Department of Informatics, University of Oslo Section leader for DIS: Distributed Infrastructure and Security Group member in Networks and Distributed Systems (ND) Active in sustainable immersive networking and blockchain labs Co-founder of AliceVision open-source photogrammetric framework His research focuses on network performance, edge computing, and immersive technologies. He has pioneered work in cloud gaming QoE, real-time 3D reconstruction, and low-latency systems. Current projects explore redirected walking in VR, GPU programming for tracking, and sustainable networking solutions. Recent publications (2021-2024) demonstrate his expertise in network delay analysis, point cloud compression, virtual reality environments, and GPU-accelerated systems. His work bridges computer science fundamentals with cutting-edge applications in multimedia, security, and health informatics. He supervises numerous master's theses covering diverse topics from wireless streaming challenges to medical imaging advancements, consistently mentoring on topics related to network optimization, immersive technologies, and GPU computing. Supervised 40+ master's theses (2004-2024) Thesis topics span network performance, GPU programming, VR systems, and multimedia processing Active in both theoretical and applied research domains Mentoring interests include HCI, distributed systems, and real-time processing Contributes to education through research-led supervision As a permanent faculty member with extensive publication records and active research groups, Griwodz maintains significant influence in academic circles through both his technical contributions and educational mentorship.