جستجوی استاد راهنمای دانشگاهی

• Asteroid mineralogy
• Planetary science
• Space weathering
• +۵ مورد دیگر

Thais Mothe-Diniz is a Researcher and Adviser at the Faculty of Natural Sciences, NTNU, holding roles such as Research Adviser in the NV Faculty Administration and Admin Coordinator for the FME-Hydrogeni Project. She specializes in asteroid mineralogy and surface composition, with expertise in EU project management. Her research focuses on asteroid family dynamics, spectroscopic analysis, and planetary science. PhD in Astronomy (2002, mineralogy of small planets) MSc in Astrophysics (1998, Celestial Mechanics) Bachelor in Pure Mathematics (1994, Maxwell's equations) Research interests include asteroid mineralogy, space weathering processes, and the structural analysis of asteroid families. She has extensive experience in coordinating international projects like REVITALISE and SisAl Pilot, and manages NTNU's collaborations with institutions like Jotun and the Paris Observatory. Publications span asteroid taxonomy, volatile detection (e.g., ice on 24 Themis), and compositional studies of basaltic asteroids in the outer main belt. Her work bridges observational astronomy and planetary formation theories, with contributions to missions like NASA's Dawn targeting Ceres and Vesta. Notable competencies include certified conflict mediation (Red Cross), project leadership, and technical skills in Linux/macOS systems.

Marija Slavkovikمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Ethics
• Computational Social Choice
• +۴ مورد دیگر

Marija Slavkovik is a Professor at the Department of Information Science and Media Studies, Faculty of Social Sciences, University of Bergen. She serves as Head of Department and is a leading researcher in artificial intelligence, with expertise in multi-agent systems, machine ethics, and computational social choice. Research Interests: Focuses on automating moral reasoning, ethical behavior in computational agents, and trust in algorithmic decision-making within public institutions. Grants: Leading applications for ERC Synergy Grants and managing ongoing projects like MediaFutures and Better Video Workflows via AI Techniques. Outreach: A vocal advocate for responsible AI, she participates in public debates and media discussions on AI's societal impact. Supervision: Advises doctoral students Than Htut Soe and Mina Young Pedersen, with past co-supervision of Flavio Tisi, Einar Søreide Johansen, and Hanna Kubacka. Scientific Awards: Received the Best Paper award at Norsk Informatikkonferanse 2020 for bias mitigation studies. Her work bridges logic, ethics, and AI, emphasizing societal trust, fairness, and interdisciplinary collaboration. She co-organizes Dagstuhl Seminars and serves on the editorial board of AI Magazine.

Paal Engelstadمشاهده پروفایل

استاد

• Machine Learning
• Wireless Communications
• Renewable Energy Systems
• +۴ مورد دیگر

Paal Engelstad is a Professor at the University of Oslo, affiliated with the Section for Autonomous Systems and Sensor Technologies at the Institute of Transport Economics (ITS). He holds a full-time academic position. His research focuses on machine learning, wireless communications, renewable energy systems, and network security, with applications in IoT, reinforcement learning, and graph neural networks. His work addresses challenges in energy forecasting, autonomous systems, and secure information exchange. Key research interests include: Deep learning for solar and wind energy forecasting Graph neural networks and their applications in recommendation systems and network analysis Non-orthogonal multiple access (NOMA) in IoT and wireless networks Reinforcement learning for autonomous systems and control Security classification and anomaly detection in networks His recent publications highlight contributions to probabilistic solar irradiance forecasting, graph-based wind prediction models, and reinforcement learning algorithms for autonomous vehicles. He collaborates extensively with international researchers and has led projects like DESSI (Distributed Energy System and Security Infrastructure). Engelstad is involved in the following initiatives: Development of secure cross-domain information exchange frameworks Advances in energy-efficient IoT and sensor networks Applications of machine learning in cybersecurity and network optimization His research lab focuses on interdisciplinary solutions bridging transport economics, energy systems, and intelligent sensor technologies.

Rebecca E. Holtمشاهده پروفایل

پژوهشگر

• Population Ecology
• Climate Change Impacts
• Fisheries Management
• +۵ مورد دیگر

Rebecca E. Holt is a Researcher at the University of Oslo (UiO), affiliated with the Centre for Ecological and Evolutionary Synthesis (CEES) within the Institute of Biosciences (IBV). Her work focuses on population ecology, particularly the effects of environmental variability, climate change, and fishing on North Atlantic fish stocks like Barents Sea cod. She holds a PhD from the University of Bergen (2015) and conducted postdoctoral research at Griffith University and CEES. Holt leads the NFR Young Research Talent Grant project 'Back to the Future for Cod,' investigating cod resilience under climate and food web changes. Her research combines mechanistic modeling, statistical analysis, and historical data to address fisheries sustainability. Major projects include CoDINA (Cod Diet and Food Web Dynamics) and FISHCOM, collaborating with international institutions like IMR and CEFAS. Holt’s expertise spans fisheries management, climate adaptation, and biodiversity conservation. Key contributions include studies on cod dietary shifts, climate-driven population dynamics, and predator-prey interactions. She has published extensively in journals like Scientific Reports , Ecology , and ICES Journal of Marine Science , with a focus on interdisciplinary solutions for marine ecosystems.

Luca Cibinelمشاهده پروفایل

پژوهشگر ارشد

• Statistics and Data Science
• Machine Learning
• Graph-Structured Data
• +۳ مورد دیگر

Luca Cibinel is a Doctoral Research Fellow at the University of Oslo, affiliated with the Department of Mathematics and the Statistics and Data Science group. His PhD project, supervised by Basil Ell, Johan Pensar, and Riccardo De Bin, focuses on developing statistical learning techniques for assessing and generating transition metal complexes based on observational data and theoretical knowledge. Prior to this, he earned a master's degree in mathematics from the University of Trento (2023), with a thesis on penalized likelihood inference for Gaussian covariance graph models. He also worked as an early-stage researcher at the University of Padua, investigating probabilistic graphical models for count data in high-dimensional scenarios. His research interests include statistical relational learning, probabilistic logic, and machine learning applications for graph-structured data. Luca is based at the Niels Henrik Abels hus in Oslo. Education: Master's in Mathematics, University of Trento (2023) Early-stage Researcher role at University of Padua (2024) Research Focus: Luca's work bridges statistical methodology and computational modeling, particularly in contexts requiring integration of theoretical and empirical data. His current project aims to create frameworks for evaluating and generating transition metal complexes, with potential applications in materials science and chemistry. Professional Affiliations: Faculty of Mathematics and Natural Sciences (student status), Statistics and Data Science research group. Links: LinkedIn Profile

Thordis Linda Thorarinsdottirمشاهده پروفایل

استاد

• Statistics
• Data Science
• Environmental Science
• +۵ مورد دیگر

Thordis Linda Thorarinsdottir is a Professor of Statistics and Data Science at the University of Oslo's Department of Mathematics, affiliated with the Faculty of Mathematics and Natural Sciences. She previously worked as a Chief Research Scientist and Research Leader for Climate and Environment at the Norwegian Computing Center (2006–2023). Her research focuses on developing stochastic models for environmental sciences, emphasizing uncertainty quantification and probabilistic prediction in climate, weather, and hydrology. Key areas include spatial and spatio-temporal modeling, Bayesian frameworks, and forecast evaluation. **Education**: PhD in Mathematical Statistics from Aarhus University (2006). **Research Interests**: Environmental applications in climate science, spatial modeling, probabilistic forecasting, and extreme event analysis. She collaborates with experts in meteorology, hydrology, and climate science to address data deficiencies and real-world challenges. **Projects**: Leads initiatives like CONFER (Climate Futures) and is part of the Integreat research group. Her work integrates statistical theory with environmental process understanding to enhance predictive accuracy and decision-making under uncertainty. **Awards**: Not explicitly listed, but her contributions to climate and environmental statistics are recognized internationally. **Grants & Labs**: Active in interdisciplinary collaborations, including the Norwegian Research Council-funded projects. Her team focuses on probabilistic modeling and ensemble forecasting techniques.

Hans Christian Farsethåsمشاهده پروفایل

مدرس

• Legal Writing
• Language Technology
• Legal Text Analysis
• +۳ مورد دیگر

Hans Christian Farsethås is a University lecturer at the Department of Philosophy and First Semester Studies , University of Bergen (UiB), and holds a postdoctoral position at UiB’s Faculty of Law since 2020, funded by the Plain Language Project at the University of Oslo’s Faculty of Law. His research focuses on legal writing, language technology applications in law, and historical analysis of clear language norms in legal texts. He teaches courses such as JUS329 (UiB) and JUS1211 Legal Argument (UiO) . Key research themes include language technology and law , linguistic analysis of legal texts , and norms for clear legal language . Recent work explores AI-driven tools for legal clarity, such as ChatGPT’s role in comma rule guidance and Norwegian legal source analysis in large language models. Farsethås has presented at events like Klarspråk 2025 and the annual social security law course , addressing topics like benchmarking language models and AI ethics in legal education. His publications span over 15 articles since 2006, including co-authored work on copyrighted material’s impact on language models and solo contributions on Norwegian legal text analysis. He collaborates with institutions like DigiVestland and the European Digital Agency . No awards or formal advisees are listed, though his postdoctoral role reflects sustained funding for legal language research. Farsethås’s work bridges theoretical legal research with practical communication challenges, emphasizing technology’s role in improving legal accessibility and precision.

Weihai Yuمشاهده پروفایل

دانشیار

• Distributed Systems
• Collaborative Editing
• Conflict-Free Replicated Data Types (CRDTs)
• +۴ مورد دیگر

Weihai Yu is an Associate Professor at the Department of Computer Science, UiT The Arctic University of Norway. His research focuses on distributed systems, collaborative editing, conflict-free replicated data types (CRDTs), edge computing, and decentralized service orchestration. He leads the Open Distributed Systems (ODS) research group and contributes to projects like the Conflict-free Replicated Relation (CRR) and Nudge Project. Yu has authored over 50 publications since 2009, with recent work emphasizing replicated data streams, undo mechanisms in collaborative systems, and edge-cloud integration. Key research interests include: distributed database replication, real-time collaborative editing with CRDTs, fault-tolerant service orchestration, and asynchronous systems design. His work bridges theory and practice, addressing challenges in consistency, scalability, and user experience in distributed applications. Publications trends show a strong focus on CRDT advancements (e.g., low-cost set CRDTs, generic undo support) and edge computing applications. He collaborates extensively with industry partners on projects like the Nudge Project, exploring IoT-driven transportation systems. Yu's contributions are published in top venues such as Springer Nature, ACM, and IEEE journals/conferences. Maintains the Open Distributed Systems (ODS) group at UiT, focusing on collaborative systems and distributed computing innovations. Current research includes local-first software architectures and conflict-free replicated relations for multi-synchronous database management.

Ines Heilandمشاهده پروفایل

استاد

• Systems Biology
• Metabolic Modeling
• Bioinformatics
• +۹ مورد دیگر

Ines Heiland is a Professor of Molecular Biology and Bioinformatics at the Department of Arctic and Marine Biology, UiT The Arctic University of Norway. She leads research in systems biology with a focus on metabolic modeling, particularly of NAD and tryptophan pathways, and their implications in aging and disease. She is Chair of the board of the National Research School for Bioinformatics, Biostatistics and Systems Biology (NORBIS), and teaches courses in bioinformatics, systems biology, and scientific programming. Research Interests: Her work lies at the intersection of computational biology and biochemistry. She develops dynamic models to simulate metabolic networks, especially those involving NAD homeostasis, tryptophan metabolism, circadian rhythms, and metabolic signaling. Her research aims to uncover mechanisms underlying aging and disease, guiding therapeutic development through predictive modeling. She emphasizes close collaboration with experimentalists to validate model predictions. Publication Trends: Her recent publications reflect a strong focus on NAD metabolism, systems modeling, and bioinformatics tool development. Key themes include genome-scale metabolic modeling, stable isotope labeling, epigenetic-metabolic crosstalk, and evolutionary analysis of metabolic pathways. Her work appears in high-impact journals such as Nature Metabolism , Cell , and PNAS . Scientific Awards: No specific awards mentioned in the provided text. Advising and Grants: While specific advisees are not listed, she has mentored junior researchers and collaborated widely. She leads or contributes to multiple research projects, including those on metabolic biomarkers, protein-protein interactions, and stable isotope approaches. She has led modeling components in collaborative grants, particularly those involving experimental validation of metabolic hypotheses. Labs and Teams: She is a member of the Bioinformatics and Systems Biology research group at UiT and leads modeling efforts within collaborative projects. She is actively involved in NORBIS, supporting national training in bioinformatics and systems biology.

• Machine Learning
• Recommender Systems
• Natural Language Processing
• +۳ مورد دیگر

Lemei Zhang is a Postdoctoral Fellow at the Norwegian University of Science and Technology (NTNU) in the Department of Computer Technology and Informatics. Their work focuses on advanced machine learning techniques for recommendation systems and social media analysis. Research interests include Deep learning architectures for news recommendation Aspect-based sentiment analysis in multilingual contexts Temporal and graph embedding methods for social recommendation Contextual augmentation in session-based systems Time series modeling for user interest prediction Creation of large-scale datasets like Adressa for media analytics Recent publications demonstrate a trajectory from foundational work on news recommendation datasets (2016-2017) to increasingly sophisticated neural approaches incorporating attention mechanisms, multimodal fusion, and real-time graph analysis across ACM Transactions, Machine Learning, and Human-Computer Studies venues.

• Human-Computer Interaction
• Quality of Experience (QoE)
• User Experience (UX)
• +۶ مورد دیگر

Katrien De Moor is an Associate Professor at the Department of Information Security and Communication Technology, Norwegian University of Science and Technology (NTNU), with research focusing on socio-technical approaches in ICT. Her work bridges user experience, digital ethics, and cybersecurity, particularly in immersive environments and next-generation networking. Co-Editor-in-Chief, Quality and User Experience (Springer) Steering Committee, QoMEX Member, Young Academy of Norway Her research spans Quality of Experience (QoE) , User Engagement , and Digital Ethics , with projects like TufiQoE (2020-2024) on ecological validity in immersive media evaluation, and Digital Carbon Footprint studies. Since 2023, she leads NTNU's 5-year Master program in Cybersecurity and Data Communication. She supervises multiple PhD students including Camille Sivelle (Secure XR Experiences), Kaja Ystgaard (Smart Environments), and Ole Martin Edstrøm (Cryptology Modeling). Current projects like Amplify (EU-funded) and Societal Security and Digital Identities (NFR-funded) emphasize ethical AI and human agency. Scientific Recognition: Founding member, Young Academy of Norway Editorial roles in TOMM and QoMEX Conference leadership at ACM IMX and MMSys Her lab collaborates with the Department of Sociology and Political Science at NTNU on cryptology's social dimensions, while mentoring early-career researchers through the PERSEUS Doctoral Programme.

• Electricity Market Design
• Flexibility Trading
• Energy Economics
• +۳ مورد دیگر

Felipe van de Sande Araujo is a researcher at the Department of Industrial Economics and Technology Management, Norwegian University of Science and Technology (NTNU), focusing on flexibility trading and electricity market design under Professor Stein-Erik Fleten. His work is supported by the Centre for Environment-friendly Energy Research NTRANS. Education: Master's in Business Administration Research, IAG School of Business, Pontifical Catholic University of Rio de Janeiro (PUC-Rio) Bachelor's in Economics, Federal University of Rio de Janeiro His research explores the economic and technical aspects of integrating flexibility into energy markets, covering hydropower systems, building heating flexibility, and future grid infrastructure. Publications highlight market design challenges and knowledge gaps in integrated energy systems. Recent academic activities include lectures at SINTEF/NTNU, European Conference on Stochastic Optimization, Real Options Group conferences, and multiple digital workshops with NTRANS and FME ZEN collaborators.

• Computer Vision
• Biometrics
• Artificial Intelligence
• +۸ مورد دیگر

Kiran Raja is an Associate Professor at the Department of Computer Science within the Faculty of Information Technology and Electrical Engineering at the Norwegian University of Science and Technology . With a focus on biometric security , computer vision , and educational technology , Raja's academic career spans both technical innovation and pedagogical research. Research interests include: Biometric Security – Face morphing attack detection, deepfake defense, and cancelable template protection Computer Vision – Facial recognition, image generation, and UAV-based person re-identification Medical AI – Healthcare data protection and medical image super-resolution Educational Reform – Redesigning computer science curricula and cross-campus teaching methodologies Recent work trends show a strong emphasis on privacy-preserving AI , ethical biometric systems , and educational technology . Key technical contributions include Vision Transformers for morphing attack detection GAN-based synthetic face morphing datasets Quantization-enhanced models for edge computing Graph Neural Networks for activity recognition Collaborations span institutions like IEEE, Springer, and SPIE, with consistent co-authorship with researchers such as Christoph Busch , Raghavendra Ramachandra , and Haoyu Zhang .

• Software Engineering
• Agile Methodology
• Simulation and Modeling
• +۴ مورد دیگر

Arne Styve is an Associate Teaching Professor at the Department of Information and Communication Technology and Natural Sciences, Norwegian University of Science and Technology (NTNU). He serves as a Studyprogram coordinator for Computing Science and teaches object-oriented programming and system development at the Bachelor level, along with simulation and visualization at the Master level. Education: B.Eng. w/Hons (Sivilingeniør) in Microelectronics and Software Engineering, University of Newcastle upon Tyne Research Interests: Specializing in Agile development, simulation modeling, and technology education. His work focuses on programming pedagogy, digital twin applications, and co-simulation frameworks. Recent research explores integrating generative AI into critical thinking practices in programming courses. Publication Trends: His publications over the past decade demonstrate expertise in simulation modeling for maritime systems, educational technology innovations, and software engineering frameworks. Key themes include digital twins, flipped classroom methodologies, and cross-campus programming education. Teaching Contributions: Instructs courses including IDATA2505 (Practice-Based Learning), IDATT2003 (Programming 2), and IDATA2302 (Algorithms & Data Structures). His pedagogical approach combines industry experience with academic innovation. Industry Experience: Over 20 years in Norwegian IT industry, including roles at Offshore Simulator Center (OSC AS), developing advanced maritime simulators and command control systems for defense applications.

• Sleep epidemiology
• Cardiovascular disease epidemiology
• Mendelian randomization
• +۱ مورد دیگر

Linn Beate Strand is an Associate Professor at the Department of Community Medicine and Nursing, Norwegian University of Science and Health Sciences (NTNU), with ongoing work in sleep epidemiology, cardiovascular disease risk factors, and Mendelian randomization. She is affiliated with the Epidemiology and Medical Statistics and MR Nursing research groups. Research Interests: Environmental determinants of health outcomes Population-level sleep disorder analysis Genetic epidemiology of cardiovascular diseases Application of Mendelian randomization Recent Research Trends: Her work bridges sleep science and cardiovascular health through Mendelian randomization, investigating insomnia's role in atrial fibrillation, stroke, and myocardial infarction. She also explores psychosocial factors in nursing education and aging populations' health behaviors. Collaborations: Regularly partners with researchers from University of Bristol, QUT, and St. Olav's Hospital.