جست‌وجوی استاد و پژوهشگر

Jon Michael Granمشاهده پروفایل

استاد

• Biostatistics
• Causal Inference
• Lifetime Analysis
• +۴ مورد دیگر

Jon Michael Gran is a Professor at the Department of Biostatistics , Institute of Basic Medical Sciences (IMB), University of Oslo, since 2022. He also holds a 20% senior researcher position at the Norwegian Institute of Public Health since 2024. PhD in Biostatistics (University of Oslo, 2011) MSc in Statistics (NTNU, 2005) His research focuses on causal inference , lifetime analysis , multistate models , and epidemiological methods , with applications in infectious disease modeling, clinical data analysis, and public health policy evaluation. Recent work examines opioid use in trauma patients, prenatal drug exposure effects, and interventions for inclusive working life. Publications (2025-2023) span journals like Acta Anaesthesiologica Scandinavica , Biometrika , and JAMA Network Open , emphasizing translational biostatistical methods applied to clinical registries and public health datasets. Notable collaborations include the Causal Inference Research Group and IPOT project on trauma outcomes. He serves as Associate Editor for Biometrika (since 2018) and Statistics in Medicine (since 2025), with teaching roles in medical statistics and machine learning at the University of Oslo.

Bjørn Rønning Fjærliمشاهده پروفایل

پژوهشگر

• Political parties
• Public opinion
• Political trust
• +۴ مورد دیگر

Bjørn Rønning Fjærli is a current Researcher at the Department of Political Science, University of Oslo, with a focus on political parties, public opinion, and causal inference. He also serves as a seminar lecturer for courses like STV1010 – Political Analysis 1: Research Design and Qualitative Methods and STV2220 – International Political Economy . His academic work explores intersections between private companies' political influence, interest groups, and comparative politics. Research Interests include: Political parties and corporate influence Public opinion and political trust Causal inference methods Comparative political analysis Education: Master in Political Science (2022-2024), University of Oslo Bachelor in International Studies with specialization in Political Science (2016-2019), University of Oslo Experience: Research assistant roles in the WELTRUST project and for courses at UiO.

Eivind Hovigمشاهده پروفایل

استاد بازنشسته

• Bioinformatics
• Cancer Genetics
• Genomic Analysis
• +۳ مورد دیگر

Eivind Hovig is an Emeritus Professor at the Department of Informatics, University of Oslo. His research focuses on bioinformatics, cancer genetics, and genomic analysis, with contributions to clinical applications in precision medicine and genetic disease management. He is affiliated with projects like the Centre for Computational Inference in Evolutionary Life Science (CELS) and RESCUER, and has collaborated extensively on initiatives such as the Prospective Lynch Syndrome Database. Research Interests: Dr. Hovig’s work spans bioinformatics tools (e.g., MirGeneDB, FuSViz), cancer genomics (Lynch syndrome, polygenic risk scores), and computational methods for genomic data analysis. His research integrates clinical and molecular data to advance personalized oncology and genetic screening strategies. Publications: His recent work highlights advancements in polygenic risk modeling, microRNA databases, and colorectal cancer surveillance strategies. Collaborations across international consortia underscore his role in translating genetic insights into clinical practice. Labs/Teams: Active in the CELS research group and projects like CoMorMent, focusing on computational biology and evolutionary life science applications.

Marieke Kuijjerمشاهده پروفایل

پژوهشگر

• Gene Regulatory Networks
• Cancer Genomics
• Bioinformatics
• +۴ مورد دیگر

Marieke Kuijjer is a Group Leader at the Norwegian Centre for Molecular Bioscience and Medicine, University of Oslo, leading the Computational Biology and Systems Medicine Group. Her academic focus spans gene regulatory networks, cancer genomics, bioinformatics, and systems medicine. She holds a PhD from Leiden University Medical Center (2013) and postdoctoral experience at Harvard and Dana-Farber Cancer Institute (2013–2018). Her research integrates multi-omics data to predict cancer outcomes and develops computational tools for gene network analysis. Key awards include the Charles A. King Postdoctoral Fellowship and National Cancer Institute grants. She has authored over 50 peer-reviewed articles, emphasizing tumor microenvironment dynamics, sarcoma genomics, and machine learning in immunology. Her work bridges computational methods with clinical applications, such as creating digital twins for cancer patients and improving bioinformatics software quality through collaboration. Current initiatives include studying osteosarcoma progression through longitudinal genomic analysis and leveraging single-cell transcriptomics for population-level gene regulatory insights. She collaborates internationally, including in the Fight Osteosarcoma and Euro Ewing consortia, advancing sample collection standards for rare cancers.

Kim Pedersen Phillipsمشاهده پروفایل

مدرس ارشد

• Philosophy
• Linguistics
• Educational Research
• +۳ مورد دیگر

Kim Pedersen Phillips is a Senior Lecturer at the University of Oslo , affiliated with the Department of Philosophy, Classics, History of Art and Ideas within the Faculty of Humanities. His research focuses on intersections of philosophy, linguistics, and education, including topics like linguistic perception, cognitive foundations of language, and educational research methodologies. Education & Background: While formal educational details are not explicitly listed, his academic profile suggests advanced training in philosophy and linguistics, given his publication focus on perception, semantics, and educational frameworks. Research Interests: His work bridges philosophical inquiry with empirical approaches, particularly in linguistic understanding mechanisms and the philosophical underpinnings of educational research. He explores how perception and inference interact in language processing, as well as the application of philosophical frameworks to educational practices. Publications: Recent works include analyses of linguistic perception (2025) and the philosophical foundations of educational research literacy (2023). These studies reflect a dual focus on cognitive science and pedagogical theory, emphasizing interdisciplinary methodologies. Awards & Grants: No specific honors or grants are listed in the provided text. Labs/Teams: No active research groups or labs are explicitly mentioned, though collaborations are indicated through co-authorship (e.g., with Anna Drożdżowicz and Sølvi Mausethagen).

• Machine Learning
• Predictive Analytics
• Time Series Analysis
• +۵ مورد دیگر

Nurilla Avazov is an Associate Professor of Data Science at the Inland School of Business and Social Sciences, Inland Norway University of Applied Sciences. He holds dual PhDs: a PhD in Computer Science (2021) from the University of Auckland and a PhD in Information and Communication Technology (2015) from the University of Agder. His research focuses on machine learning, predictive analytics, time series analysis, wireless communication modeling, IoT systems, e-healthcare solutions, and human activity recognition through advanced signal processing techniques. Dr. Avazov’s academic career includes significant contributions to high-impact refereed journals and conferences. His work spans theoretical developments in algorithm design, practical implementations in sensor networks, and interdisciplinary applications in healthcare and smart environments. He has developed novel trajectory-driven channel models for mm-wave systems and pioneered backscattering-based human activity recognition methods. His expertise combines data science with telecommunications engineering, addressing challenges in non-stationary channel analysis, radar systems for indoor localization, and cybersecurity through wireless signal inference. Current research trends emphasize multimodal sensor fusion, real-time activity tracking, and privacy-aware IoT architectures. Dr. Avazov has advised no formally recorded students in the provided data. His research grants and funded projects are not explicitly detailed here, though his publications indicate sustained external collaboration and funding support. He is affiliated with the Business Analytics research group at his institution.

Bård Inge Austigard Pettersenمشاهده پروفایل

استادیار

• Statistical Machine Learning
• Mathematical Logic
• Functional Analysis
• +۶ مورد دیگر

Bård Inge Austigard Pettersen is an Assistant Professor at the Faculty of Logistics, Molde University College. He specializes in logistics, mathematics, and educational technology. His roles include Study Leader for an online logistics program and Coordinator for online teaching in logistics. He teaches courses such as Applied Calculus, Statistics, and Production Planning. He holds a degree in mathematics and physics from the Norwegian University of Science and Technology (NTNU). His research focuses on statistical machine learning, mathematical logic, functional analysis, combinatorics, and complexity theory, with a strong emphasis on applying digital tools to enhance teaching and learning. His publications span textbooks in mathematics, logistics, and statistics, including foundational texts like Grunnleggende matematikk and specialized works on inventory management. He has contributed to improving online education through projects on Learning Management Systems (LMS) and digital book simulation. His work highlights the intersection of theoretical research and practical educational innovation, with a commitment to student success through technology integration.

• Marine Ecology
• Fisheries Management
• Conservation Biology
• +۳ مورد دیگر

Even Moland is an Associate Professor at the Department of Natural Sciences, University of Agder. His research focuses on marine ecology, fisheries management, and conservation biology, with an emphasis on understanding the impacts of climate change, marine protected areas (MPAs), and human activities on marine ecosystems. His work explores topics such as fish population dynamics, spatial behavior of marine species, and the effectiveness of conservation strategies. He uses advanced techniques like acoustic telemetry and Bayesian modeling to study animal behavior and habitat use. Collaborations with institutions globally underscore his interdisciplinary approach to solving complex ecological challenges. Key contributions include studies on the effects of marine heatwaves on fish communities, the role of MPAs in preserving biodiversity, and the ecological consequences of climate change on marine species. His research has been published in high-impact journals such as Science , Biological Conservation , and Ecology and Evolution .

Magne Mogstadمشاهده پروفایل

استاد مدعو

• Econometrics
• Labor Economics
• Public Policy
• +۳ مورد دیگر

Magne Mogstad is an Adjunct Professor at the University of Oslo, specializing in econometrics, labor economics, and public policy. His research focuses on topics such as instrumental variables, policy evaluation, social mobility, and the impact of technology on markets. Key research interests include statistical inference methods, labor market dynamics, and the application of econometric techniques to analyze policy outcomes. He has contributed to studies on topics like broadband internet's effect on stock market investments, the role of print media in digital markets, and the economic implications of production networks. Mogstad has published extensively in top journals such as the Journal of Econometrics , American Economic Review , and Journal of Labor Economics . His work often bridges theoretical econometrics with applied policy analysis, emphasizing causal inference and empirical rigor.

Philipp Christian Bronieckiمشاهده پروفایل

پژوهشگر

• European Union Politics
• Legislative Politics
• Data Science
• +۷ مورد دیگر

Philipp Christian Broniecki is a postdoctoral researcher in the Department of Political Science at the University of Oslo, affiliated with the Strategy of Recorded Voting in the European Parliament (StREP) project. He holds a Senior Research Officer position at the ESRC Business and Local Government Data Research Centre (University of Essex) and has advised local governments and NGOs on research methodology. His work focuses on EU legislative politics, political negotiations, and advanced quantitative methods including machine learning and Bayesian statistics. Education & Positions: Postdoctoral researcher at University of Oslo (current) Senior Research Officer at University of Essex Research Interests: Broniecki examines EU institutional dynamics, Euroskepticism in the European Parliament, and methodological innovations in political science. Key areas include: Political negotiations and transparency Subnational public opinion estimation via machine learning Quantitative text analysis of development surveys Conflict escalation prediction from big data Peace agreement mediator strategies Advising & Grants: Engaged in methodological training for local governments and NGOs. Participates in multi-institutional projects funded by ESRC and other research councils. Labs/Teams: Member of Comparative Institutions and Regimes (CIR) and Political Data Science (PODS) research groups at UiO.

Jukka Coranderمشاهده پروفایل

استاد

• Bayesian Statistics
• Inference Methods
• Stochastic Simulation Algorithms
• +۷ مورد دیگر

Jukka Corander is a Professor at the University of Oslo's Department of Biostatistics, Faculty of Medicine, and concurrently holds positions at the University of Helsinki's Department of Mathematics and Statistics. He specializes in Bayesian statistics, microbial genomics, and evolutionary biology, with a focus on bacterial pathogen evolution and antibiotic resistance mechanisms. Affiliations: Professor, Department of Biostatistics, University of Oslo (since 2016) Professor, Department of Mathematics and Statistics, University of Helsinki (since 2009) Former roles at Åbo Akademi University and Churchill College, University of Cambridge Research Interests: Bayesian inference methods, stochastic simulation algorithms, machine learning applications in genomics, population genetics of bacteria, and forensic statistical analyses. Key Awards: 2015 Cozzarelli Prize (PNAS) for groundbreaking work on bacterial pathogen evolution 2008 Per Brahe Award (Young Scientist of the Year) Grants & Leadership: ERC StG Grant (SmartBayes, 2009–2014) COIN Centre of Excellence (Vice-Director, 2015–2017) Leadership roles in Helsinki Institute of Information Technology (HIIT) Labs & Collaborations: Leads the Corander Lab, focusing on computational methods for microbial genomics and evolutionary analysis. Collaborates globally on projects involving antibiotic resistance, pathogen transmission, and epidemiological modeling.

• Computational Mathematics
• Differential Equations
• Signal Processing
• +۳ مورد دیگر

Øyvind Ryan is a Senior Lecturer at the Department of Differential Equations and Computational Mathematics at the University of Oslo. He specializes in computational mathematics, signal processing, and random matrix theory. His research integrates theoretical mathematics with practical applications in signal processing, image compression, and wireless communication systems. Research interests include wavelet analysis, numerical methods, statistical inference, and the asymptotic behavior of random matrices. His work often bridges pure mathematics and engineering challenges, such as optimizing channel capacity estimation and developing efficient compression techniques for low-bit-depth images. Key contributions span topics like Vandermonde matrices in cognitive radio systems, free probability theory applications, and runlength-based processing for map images. His articles frequently appear in top journals such as IEEE Transactions on Signal Processing and Acta Applicandae Mathematicae. Affiliated with the Computational Mathematics research group at the University of Oslo, Ryan collaborates on projects involving advanced signal processing methodologies. No specific advising roles or grants are explicitly listed in the provided materials, though his extensive publication record reflects sustained scholarly activity.

Sven Ove Samuelsenمشاهده پروفایل

استاد

• Biostatistics
• Epidemiology
• Public Health
• +۴ مورد دیگر

Sven Ove Samuelsen is a Professor in Statistics and Data Science at the University of Oslo's Department of Mathematics, part of the Faculty of Mathematics and Natural Sciences. His research spans epidemiology, biostatistics, and public health, with a focus on occupational health risks (e.g., petroleum workers' exposure to carcinogens), maternal and child health, and statistical methodology development. He leads the Norwegian Epidemiologic Osteoporosis Studies (NOREPOS) and collaborates with institutions like the Centre for Computational Inference in Evolutionary Life Science (CELS) and PharmaTox. Notable contributions include work on cohort sampling, inverse probability weighting in nested case-control studies, and risk assessments for benzene exposure, night shift work, and maternal anxiety effects. Education & Affiliations: Professor at University of Oslo; affiliated with the International Alliance for PharmacoGenetic Epidemiology Excellence (iAPOGEE). No explicit education details provided. Research Interests: Biostatistical methods, occupational epidemiology, maternal/fetal health, chronic disease risk factors, and survival analysis. Active in projects like the Norwegian Offshore Petroleum Workers (NOPW) cohort study, analyzing cancer risks from chemical exposures and shift work. Grants & Projects: Leads NOREPOS and iAPOGEE initiatives. Research funded by grants addressing environmental and occupational health, maternal health, and statistical methodology. Labs/Teams: Centre for Computational Inference in Evolutionary Life Science (CELS), PharmaTox, and Statistics and Data Science groups at the University of Oslo.

Niklas Erdmannمشاهده پروفایل

پژوهشگر ارشد

• Machine Learning
• Deep Learning
• Time series analysis
• +۵ مورد دیگر

Niklas Erdmann is a Research Fellow and PhD candidate at the University of Oslo, affiliated with the Section for Autonomous Systems and Sensor Technologies. He holds a Master's in Artificial Intelligence and a Bachelor's in Psychology from the University of Groningen (NL). His research focuses on applying machine learning to energy systems, particularly solar irradiance forecasting using weather data. Education: Master's in Artificial Intelligence, University of Groningen (NL) Bachelor's in Psychology, University of Groningen (NL) Research interests include time series forecasting, explainable AI, and probabilistic machine learning. His work emphasizes uncertainty quantification and applications in energy systems. Recent publications include a conference paper on solar irradiance forecasting at the Arctic Circle using deep learning methods. Labs/Teams: Active in the Section for Autonomous Systems and Sensor Technologies.

Tarjei Widding-Havneråsمشاهده پروفایل

پژوهشگر ارشد

• Psychiatric Epidemiology
• Social Stratification
• Causal Inference Methods
• +۳ مورد دیگر

Tarjei Widding-Havnerås is a Research Fellow at the CREATE Centre for Research on Equality in Education, University of Oslo. He holds a PhD in Epidemiology from the University of Bergen, an MPhil in Sociology, and a BA in Economics. His research focuses on policy interventions in health, education, and the labor market, utilizing causal inference methods such as instrumental variables and Mendelian randomization. He has been affiliated with the EQOP project and has held visiting positions at the University of Wisconsin-Madison. His work combines administrative, genotyped, and survey data to address societal inequalities. Key achievements include Honorary Fellowships at the University of Wisconsin-Madison (2021 and 2024). He teaches advanced causal inference methods and has contributed to studies on ADHD treatment effects, criminality, and educational outcomes. His current projects explore educational inequalities using registry and genetic data.