جست‌وجوی استاد و پژوهشگر

• Bioinformatics
• Genomics
• Computational Biology
• +۴ مورد دیگر

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

Leiv Rønnebergمشاهده پروفایل

پژوهشگر ارشد

• Statistics
• Data Science
• Biostatistics
• +۲ مورد دیگر

Leiv Rønneberg is a Postdoctoral Fellow in Statistics and Data Science at the University of Oslo (UiO), with a primary affiliation at the Department of Mathematics. His research focuses on Bayesian statistical methods, machine learning, and data science, particularly applied to biomedical and astrophysical domains. Key research trends in his publications include: Development of flexible Bayesian models (FlexKnot, bayesynergy) for complex datasets Applications in 21 cm cosmological signal processing and drug combination analysis Creation of bioinformatics tools (screenwerk) for experimental design Interdisciplinary work spanning astrophysics, pharmacology, and sports science Scientific Awards: No awards explicitly mentioned in the provided text. Students: No advisees or students listed in the current description.

Lars Hoffمشاهده پروفایل

استاد

• Ultrasound Technology
• Acoustics
• Medical Technology
• +۲ مورد دیگر

Lars Hoff is a Professor at the University of Southeast Norway within the Department of Microsystems , Faculty of Technology, Natural Sciences and Maritime Studies . He leads research in ultrasound technology , focusing on transducer and electronics as part of the Centre for Innovative Ultrasound Solutions (CIUS) . Research : Develops advanced ultrasound transducers for medical imaging, underwater sonar, and NDT. Collaborates with NTNU, University of Oslo, and industry partners. Teaching : Coordinates courses in Measurement Engineering , Acoustics and Ultrasound Technology , and Elastic Waves in Solids at PhD level. Software : Developed Bubblesim , a MATLAB-based tool for simulating contrast agent bubbles for medical ultrasound. Industry Impact : Co-founded Cardiaccs AS to commercialize microsensors for cardiac monitoring developed in collaboration with Rikshospitalet. Publications : Authored a foundational book on contrast agent acoustics and key papers on microbubble dynamics. His work underpins widely used clinical agents like Optison and Sonazoid .

• Security
• Theoretical Computer Science
• Formal Methods
• +۷ مورد دیگر

Christian Johansen is a Professor in the Department of Information Security and Communication Technology at the Norwegian University of Science and Technology (NTNU), Faculty of Information Technology and Electrical Engineering. He leads the Systems Security group (S2G) and is affiliated with the Center for Cyber and Information Security (CCIS), the Norwegian Cyber Range, and the S2G Playground. Professor Johansen's research focuses on Security and Theoretical Computer Science, with emphasis on developing formal methods and tools for ensuring reliability of complex systems. His work spans security, safety, and concurrency properties in software systems, cyber-physical systems like Smart Grids, Internet of Things security, and modeling concurrency in multi-core and high-performance computing. Among his notable contributions are the Timed Distributed pi-calculus, ST-structures, Dynamic Structural Operational Semantics, Synchronous Kleene Algebra, and Higher Dimensional Modal Logic. His research interests include modeling of security protocols, programming language semantics, verification of distributed systems, concurrent systems modeling, and legal electronic contracts. His recent publications show a strong trend toward concurrency theory, security, and privacy, with significant contributions to pi-calculus variants, higher-dimensional automata, attribute-based encryption, and semantic access control frameworks. Many of his papers appear in top venues such as CONCUR, ATVA, FM, POST, CCS, JLAMP, IJCIP, FMSD, and LMCS. Professor Johansen actively mentors students and collaborators, having worked with Manish Shrestha on the LightSC Security Classification Method for Smart Grids and IoT, and with Bjørnar Luteberget on the SAT modulo Discrete Event Simulation method for railway capacity verification. He has secured funding from competitive sources including EU-FP7-FET-Young-Explorers, Horizon-2020, NFR-FRINATEK, UK's EPSRC, and ECSEL-JU. His work often bridges theoretical computer science with practical security applications in critical infrastructure domains.

• Computer Networking
• Quality of Experience (QoE)
• Video Streaming
• +۳ مورد دیگر

Bjørn Jonny Villa serves as Associate Professor at the Norwegian University of Science and Technology (NTNU), specializing in computer networking with emphasis on adaptive video streaming and Quality of Experience (QoE) optimization. His research addresses critical challenges in home networks, public WiFi security, and bandwidth management, as evidenced by publications spanning 2010-2014 in top venues including IEEE, Springer, and international journals. Villa earned his PhD from NTNU in 2014 with the dissertation "Enhancing Quality Aspects of Adaptive Video Streaming in Home Networks," establishing foundational work for his subsequent research. His academic journey reflects deep specialization in network performance optimization for multimedia delivery systems. Core research interests include adaptive HTTP video streaming, QoE measurement and optimization, network security vulnerabilities (particularly in public WiFi), and active probing techniques for bandwidth estimation. Villa employs experimental user studies and traffic analysis to develop practical solutions for improving streaming fairness and network resource allocation, with significant contributions to understanding how burst durations and traffic shaping impact user-perceived quality. Analysis of Villa's publication timeline reveals consistent focus on video streaming challenges: early work (2010-2011) established monitoring frameworks and home gateway optimization, mid-period research (2012-2013) advanced fairness algorithms and traffic shaping, while his 2014 output expanded into security implications of public networks. His collaborative approach is evident through recurring partnerships with Poul Einar Heegaard and Anders Instefjord across multiple publications. No scientific awards are documented in the available records. Similarly, no information regarding research grants or student supervision appears in the provided materials. Villa actively engages with the research community through conference presentations including Forskningsdagene (2013) and NIK conferences, and contributes to public discourse through media appearances in Aftenposten and Inside Telecom. His work operates within NTNU's telecommunications research ecosystem, focusing on practical implementations of network optimization techniques for real-world video delivery systems.

• Autonomous Systems
• Machine Learning
• Computer Vision
• +۳ مورد دیگر

Muhammad Adnan serves as a Research Fellow at the Department of Technology and Safety, UiT The Arctic University of Norway, with contact details including email muhammad.adnan@uit.no and phone +47 77 66 02 47. His research spans critical domains in modern engineering and computer science, with primary focus areas: Autonomous Maritime Systems : Developing operational frameworks for remotely controlled vessels and onshore operation centers Machine Learning Applications : Advancing ensemble methods for classification, spam detection, and remote sensing Computer Vision Integration : Leveraging electro-optical/NIR sensors for maritime object detection Cybersecurity Solutions : Enhancing email security through stacking ensemble techniques Recent publications (2023-2024) reveal a concentrated research trajectory merging maritime autonomy with AI-driven solutions, demonstrating significant interdisciplinary work across navigation support systems, sensor fusion, and transfer learning applications. His output shows consistent publication in high-impact journals with practical engineering implementations. No scientific awards were documented in the provided materials. Information regarding student supervision, grant funding, or laboratory affiliations was not available in the source text.

Trine Ballestad Roungeمشاهده پروفایل

استاد

• Bioinformatics
• Genomics
• Epigenomics
• +۵ مورد دیگر

Trine Ballestad Rounge is a Professor at the Section for Pharmacology and Pharmaceutical Biosciences at the University of Oslo. Her research focuses on genomics, epigenomics, transcriptomics, and microbiome-related research with the primary goal of identifying biomarkers in tissues, biofluids, or associated microbes that reveal early-stage cancer progression. Her research interests include: Bioinformatics and molecular biology Development of sequencing protocols and advanced bioinformatics analyses Identification of cancer biomarkers through genomic, epigenomic, and microbiome approaches Development of bioinformatics tools including GENOMICON-Seq, VirMake, HoCoRT, and TAME-seq Dr. Rounge leads several major research projects including CRCbiome (funded by the Norwegian Cancer Society and HSØ), which aims to identify biomarkers in the gut microbiome for colorectal cancer screening. She is the Norwegian PI for the Genome of Europe project, part of the 1+MG initiative, collaborating with Helsedirektoratet and Elixir. She also leads the JanusRNA project funded by the Norwegian Research Council, which aims to identify circulating RNAs as cancer biomarkers using serum samples. In this project, her team has analyzed more than 4000 samples from pre-diagnostic samples across seven different cancer sites. Her scientific work shows a strong focus on cancer biomarker discovery, particularly using multi-omics approaches. Her recent publications demonstrate expertise in microbiome analysis, circulating RNA profiling, and bioinformatics tool development. Her research spans colorectal cancer, ovarian cancer, endometrial cancer, testicular germ cell tumors, and HPV-related cancers. Dr. Rounge collaborates extensively with researchers across Europe and leads cross-institutional groups working on genomic events in persistent HPV infection. Her work bridges computational biology with clinical applications, aiming to translate genomic findings into practical cancer screening tools.

Bjørn Solvangمشاهده پروفایل

استاد

• Manufacturing Systems
• Robotics and Automation
• Industrial Engineering
• +۳ مورد دیگر

Bjørn Solvang is a Professor in the Department of Industrial Engineering at UiT The Arctic University of Norway, campus Narvik. His research focuses on advanced manufacturing systems, robotics, and digital transformation in industrial contexts. His primary research interests include: Reconfigurable Manufacturing Systems Industry 4.0/5.0 Technologies Human-Robot Collaboration Digital Twins and Virtual Reality Applications Supply Chain Optimization Cognitive Infocommunication in Robotics He investigates how these technologies enhance flexibility, efficiency, and sustainability in manufacturing, particularly for small and medium enterprises (SMEs). Analysis of his recent publications reveals a strong trajectory toward smart manufacturing systems with increasing emphasis on Industry 5.0 principles. His work consistently addresses real-world industrial challenges through robotics integration, digital twin implementations, and AI-driven optimization, often involving European cross-organizational collaborations. Professor Solvang actively contributes to the ArcLog research group (Intelligent Manufacturing and Logistics) and the "Industry 5.0 enabled Smart Logistics" project. He has participated in multiple European cooperation initiatives providing educational frameworks for SMEs transitioning to advanced industrial paradigms. Based at Campus Narvik (room A4050), he maintains active industry engagement through research projects targeting practical manufacturing innovations and sustainable logistics solutions.

• Machine Learning
• Health Informatics
• Cancer Research
• +۵ مورد دیگر

Jan Franz Nygård is an Associate Professor at the Department of Physics and Technology , UiT The Arctic University of Norway. His work bridges Machine Learning with Health Informatics , focusing on cancer registries, AI for medical diagnostics, and data-driven healthcare solutions. UiT The Arctic University of Norway Department of Physics and Technology His research spans Cancer Research , Artificial Intelligence , and Data Science , with recent studies on synthetic data applications, federated learning, and quantum computing in healthcare. Over 15 recent publications highlight his contributions to breast cancer detection, cervical cancer risk prediction, and software testing for medical systems. Key collaborations include partnerships with the Cancer Registry of Norway , international consortia on federated networks, and interdisciplinary teams in Medical Imaging and Bioinformatics . His work addresses challenges in Secure Health Data Analysis and Population Health Management .

• Advanced optical systems
• Light-sheet microscopy
• Mechanosensitive microscopy
• +۹ مورد دیگر

Dr Florian Ströhl is a Senior Researcher (equivalent to Research Professor) at the Department of Physics and Technology , UiT The Arctic University of Norway in Tromsø. He leads a highly interdisciplinary program that bridges optics, biology and medicine, acting as Principal Investigator on the ERC Starting Grant LiBriNa , the RCN FRIPRO SOLIS project, and the EU MSCA MitoQuant consortium. Education: Ph.D. Biotechnology (2018), University of Cambridge, UK M.Sc. Advanced Optical Technologies with honours & distinction (2014), University of Erlangen-Nuremberg, Germany B.Sc. Medical Engineering with BMBF award (2012), University of Erlangen-Nuremberg, Germany Research Interests: Dr Ströhl’s work revolves around advanced optical system development , spanning the full chain from optical theory and photolithography to instrumentation and biomedical application . Core themes include light-sheet microscopy , mechanosensitive Brillouin nanoscopy , label-free super-resolution techniques , and integrated photonics . Application domains cover dementia research , kidney & liver pathology , cardiac imaging and sustainable aquaculture . Scientific Awards & Funding: 2025 ERC Starting Grant—20 million NOK 2023 RCN Innovation Grant—1 million NOK 2021 RCN FRIPRO Young Research Talent Grant—8 million NOK 2019 EU Horizon 2020 MSCA Grant—2.1 million NOK EMBO Fellow, Nano DTC Fellow, OPTICA Senior Member Grants, Teams & Mentoring: Dr Ströhl currently directs a diverse team of post-docs, PhD candidates and engineers in the Ultrasound, Microwaves and Optics research group. He actively welcomes master’s thesis students and visiting scientists. All projects are supported by Norwegian and European funding frameworks and emphasize open science , cross-disciplinary collaboration and public outreach via video tutorials and popular-science talks.

• Computational Geoscience
• Scientific Computing
• Numerical Analysis
• +۳ مورد دیگر

Magnus Bruaset is a Professor and Director of the Software & AI Department at Simula Research Laboratory , with expertise in computational geosciences, numerical methods, and quantum computing. His work spans geological modeling, PDE solvers, and software development frameworks like Diffpack. Education : PhD in preconditioned iterative methods for elliptic problems (1992), Master's in preconditioning symmetric systems (1988). Research Interests : Focus on numerical analysis, GPU acceleration of geological simulations, stochastic modeling for uncertainty quantification, and quantum computing strategy. Key projects include Hamilton-Jacobi solvers, particle-based flow models, and contributions to digital contact tracing systems. Advising & Collaboration : Co-developed PhD training workshops for scientific communication and contributed to industrial-academic partnerships. Collaborated with institutions including ChevronTexaco, Wolfram Research, and University of Oslo.

• Maritime Safety
• Deep Learning
• Anomaly Detection
• +۳ مورد دیگر

Dogan Altan serves as a Postdoctoral Fellow at Simula Research Laboratory within the Department of Validation Intelligence for Autonomous Software Systems. His research focuses on developing artificial intelligence solutions for maritime safety and operational efficiency, leveraging advanced machine learning techniques to address complex vessel navigation and performance challenges. His primary research interests include maritime anomaly detection, vessel traffic prediction, and physics-informed neural modeling for shaft power optimization. Altan specializes in integrating sensor data, passage plans, and environmental features into deep learning frameworks to enhance predictive accuracy in maritime contexts. Key methodologies involve transfer learning, trajectory segmentation, and multi-stream anomaly identification systems applicable to both vessel operations and robotic manipulation. Analysis of his publication trends reveals a consistent focus on transforming maritime domain knowledge into robust AI frameworks. Recent work demonstrates innovation in temporal graph analysis for port classification, transformer-based waypoint detection, and physics-guided hybrid models that bridge engineering principles with neural network architectures. His contributions span theoretical algorithm development and practical implementations validated through real-world maritime datasets.

• Computational Biology
• Mathematical Modeling
• Neuroscience
• +۴ مورد دیگر

Marius Causemann is a Postdoctoral Researcher in the Numerical Analysis and Scientific Computing department at Simula Research Laboratory , focusing on computational modeling of brain mechanics and fluid dynamics. His work bridges mathematics, neuroscience, and biomedical simulation through high-fidelity numerical methods. Research Interests include: Computational Neuroscience Biomechanics of Gliovascular Systems Poroelastic and Fluid-Structure Interaction Models Numerical Methods for Multi-Physics Problems Mathematical Physiology His recent publications emphasize in-silico modeling of molecular clearance in intracranial spaces, dual-poroelasticity solvers, and high-resolution meshing of brain tissues. These works contribute to understanding glymphatic pathways, neurovascular coupling, and cerebrospinal fluid dynamics.

• Scientific Computing
• Finite Element Methods
• Mixed-Dimensional Coupling
• +۴ مورد دیگر

Cécile Daversin-Catty is a Research Scientist at Simula Research Laboratory in the Department of Numerical Analysis and Scientific Computing. Her work bridges computational mathematics and biomedical engineering through advanced finite element methods. Education: PhD in Applied Mathematics (2016, Université de Strasbourg), thesis titled 'Reduced basis method applied to large non-linear multi-physics problems: application to high field magnets design' Her research focuses on scientific computing , finite element methods , and mixed-dimensional coupling , with applications spanning fluid mechanics , cardiac electromechanics , and neurovascular modeling . Recent publications highlight her expertise in computational fluid dynamics for cardiac flow simulations, development of FEniCS-based tools for mixed-domain problems, and modeling of perivascular networks. Key trends in her work include: Development of robust numerical frameworks for multi-physics problems Advancing cardiac electromechanical modeling for heart failure studies Exploring glymphatic system dynamics via mixed-dimensional finite elements Software innovation in computational science tools She collaborates extensively with researchers across computational cardiology and neuroscience, contributing to open-source platforms like FEniCS.

• Medical Imaging
• Computer Vision
• Artificial Intelligence
• +۲ مورد دیگر

Akriti Sharma serves as a Postdoctoral Fellow in the Department of Validation Intelligence for Autonomous Software Systems at Simula Research Laboratory, specializing in artificial intelligence applications for medical diagnostics and maritime engineering. Her core research interests span: Medical Image Analysis for human embryo development in IVF procedures Computer Vision using deep learning architectures (YOLO) for embryo cleavage detection Transfer Learning techniques applied to maritime shaft power prediction Explainable AI frameworks for clinical decision support systems Energy efficiency optimization in shipping through sensor data analysis From 2022-2025, her publication trajectory shows progression from embryo cell tracking automation to cross-domain transfer learning applications. Early work focused on time-lapse video analysis for cleavage timing prediction, evolving toward AI-driven embryo quality assessment and maritime power forecasting, demonstrating consistent innovation in real-world AI deployment. No scientific awards or honors were documented in the source material. Information regarding student advisement, research grants, or educational background was not provided in the available text. As part of Simula's Validation Intelligence for Autonomous Software Systems department, she contributes to developing rigorous validation methodologies ensuring safety and reliability in autonomous AI systems across healthcare and maritime sectors.