Morten Brun is an Associate Professor at the Department of Mathematics, University of Bergen. His research spans computational topology, persistent homology, and applications in biology and data science. Email: morten.brun@uib.no Research Interests: He specializes in topological data analysis, focusing on sparse nerves, relative persistent homology, and computational geometry. His work applies topological methods to biological problems, including drug resistance modeling in tuberculosis and immune profiling in multiple sclerosis. Recent Publications: His 2025 work includes hypercubic modeling of tuberculosis drug resistance and high-dimensional immune profiling post-stem cell transplantation. Earlier articles explore computational topology techniques (2017-2024) and interdisciplinary applications in toxicology and systems biology.
Simen Markussen is a Director at the Frisch Centre for Economic Research, affiliated with the Department of Economics at the University of Oslo. Holding a PhD in Economics (2010), he focuses on labour economics , social insurance programs , and health economics using empirical methods and Norwegian registry data . Education : PhD in Economics, University of Oslo (2010) His research explores economic mobility , sickness absence , and policy evaluation , with recent work on pandemic employment gradients, ADHD treatment outcomes, and housing market dynamics. Articles span Education Economics , BMJ Mental Health , and Journal of Health Economics , emphasizing causal inference and policy implications. Collaborations include projects on pension reforms , vocational rehabilitation , and social insurance fraud . Though no scientific awards are listed, his work informs Norwegian welfare and labor policies through Nordic comparative micro-data and randomized field experiments . Current projects address adult education incentives , corona crisis economic impacts , and interventions for crime-prone individuals . His 15 recent publications (2023–2025) highlight cross-disciplinary applications in public sector productivity , health policy , and economic inequality .
Carlos José Díaz Baso is a Research Fellow at the Rosseland Centre for Solar Physics (RoCS), part of the Institute of Theoretical Astrophysics at the University of Oslo. His research focuses on solar chromospheric phenomena, Bayesian statistics, and deep learning applications in solar physics. Education: Ph.D. in Astrophysics (2014-2018, Universidad de La Laguna, Spain), followed by postdoctoral positions at Stockholm's Institute for Solar Physics (2018–2022) and currently at RoCS (2022–present). Research emphasizes analyzing solar spectra and magnetic field dynamics using advanced statistical and machine learning techniques. Key projects include the ISSRESS initiative studying small-scale solar reconnection events. Recent publications explore spectral resolution impacts, coronal oscillations, and sunspot light bridges. Active in international collaborations using instruments like SST/CRISP and SolO/EUI. Engaged in developing observational strategies for solar telescopes and improving data analysis methodologies.
Ingrid Hobæk Haff is an Associate Professor in insurance mathematics and statistics at the Department of Mathematics, University of Oslo since 2015. She holds a master's degree in Industrial Mathematics from NTNU (2002) and a PhD from the Statistics for Innovation center (2008–2012), with a 20% position as a research scientist at the Norwegian Computing Centre. Previously, she worked there as a research scientist and senior scientist. Her research interests focus on multivariate statistics, copulae, skew and heavy-tailed distributions, and applications in insurance and finance. She has contributed to advancements in statistical modeling, particularly in copula constructions and their applications to risk assessment and extreme value analysis. Key awards include the Sverdrup award for young scientists and the mathematical award of Hanna og John Olav Stubban . She is affiliated with the Statistics and Data Science research group and the completed Stochastics of Renewable Energy Markets (STORE) project. Her work spans interdisciplinary collaborations, including applications in immunology and bioinformatics, leveraging machine learning for antibody-antigen interaction studies and synthetic data generation.
Pedro Lind is a Professor at Oslo Metropolitan University's Faculty of Technology, Art and Design, where he serves in the Department of Information Technology with a focus on Artificial Intelligence. His academic appointments include active participation in research groups for Applied Artificial Intelligence and Mathematical Modeling. Dr. Lind's research spans interdisciplinary domains including: Biomedical AI applications (EEG classification, ECG analysis, eye tracking) Stochastic processes and complex systems modeling Trustworthy machine learning for security/privacy Physics-inspired computational methods Renewable energy statistics and modeling His recent publications demonstrate strong focus on developing novel AI methodologies for medical diagnostics (2024-2025), particularly using generative models and interpretable AI approaches for physiological data analysis. He leads significant research initiatives including the AI-Mind project developing diagnostic tools for dementia. Additional projects include international technology transfer collaborations with Czech Republic institutions. Dr. Lind maintains active research teams and labs focused on computational neuroscience and applied AI.
Jo Thori Lind is a Professor in the Department of Economics at the University of Oslo, Faculty of Social Sciences. He is actively engaged in research and teaching, with recent courses including Data Science for Economists (Fall 2024). His scholarly work spans political economics, development economics, economic inequality, and econometrics, with a strong focus on behavioral and institutional dimensions of economic decision-making. His research interests include: Political economics and the political economy of beliefs Development economics and conflict-induced production Economic inequality and redistribution Econometric methodology, including instrumental variables and tests for nonlinear relationships Behavioral aspects of public goods, altruism, and information avoidance Lind's recent publications (2019–2025) reveal a consistent trajectory in political and behavioral economics, with increasing attention to health, technology, and climate. His work often employs rigorous empirical methods, including instrumental variables and experimental designs, to explore questions of voter behavior, physician decision-making, information avoidance, and social cooperation. Themes such as asymmetric information, strategic ignorance, and institutional design recur across his research. Notable scientific contributions include: Co-development of the Stata module utest for testing U-shaped relationships Research on fractionalization and government size Studies on altruism across professions (e.g., nurses vs. real estate brokers) Analysis of conflict-induced narcotics production in Afghanistan Work on the role of information in welfare and voting behavior Lind has advised or collaborated with numerous economists and has been affiliated with research groups such as the Centre of Equality, Social Organization, and Performance (ESOP) and the Nordic Welfare Developments (NoWeDe) project. He has not been noted to supervise specific students in the provided texts, nor are any grants or awards explicitly mentioned. His research is supported by ongoing institutional affiliations and publications in leading economics journals. He is associated with the following research initiatives: Centre of Equality, Social Organization, and Performance (ESOP) Environmental Exploitation of Political Economics (EXPLOIT) Nordic Welfare Developments (NoWeDe) – completed
Nils-Ole Stutzer is a Doctoral Research Fellow at the Institute of Theoretical Astrophysics , University of Oslo, specializing in Cosmology , Line Intensity Mapping , and Cosmic Microwave Background (CMB) data analysis. He contributes to major projects like COMAP COSMOGLOBE BeyondPlanck and develops computational tools in Python/C++ for mitigating systematic errors in radio telescope data. His research interests focus on Galactic and extragalactic CMB analysis Radio interferometry for molecular gas mapping Bayesian methods in cosmological parameter estimation Instrumental signal deconvolution Open science data frameworks His work addresses fundamental questions about cosmic structure formation and early universe physics. Key publication trends include: 2024 studies on 30GHz spinning dust emission in dark clouds Advanced CO power spectrum constraints at z ∼ 3 2023-2024 Bayesian reanalysis of Planck/WMAP missions LiteBIRD mission forecasts for gravitational waves Projects emphasize reproducibility and end-to-end data modeling. He teaches AST2000 project groups and collaborates across institutions on CMB&CO initiatives. Current affiliations include the Faculty of Mathematics and Natural Sciences at the University of Oslo.
Joakim Sundnes is a Chief Research Scientist and Research Professor at the Department of Scientific Computing, Simula Research Laboratory. He specializes in computational physiology, cardiac biomechanics, and mathematical modeling of cardiovascular systems. Key Research Areas: Cardiac electromechanics, computational fluid dynamics in cardiology, uncertainty quantification in cardiac models, and mechano-electric feedback mechanisms Recent Trends: Focus on patient-specific modeling, left atrial flow dynamics, right ventricular mechanics in pulmonary hypertension, and personalized treatment simulations Scientific Contributions: Active participant in international conferences and editorial work. Co-author of multiple benchmark studies and educational texts on physiological modeling.
Ben Michael Brumpton is an Associate Professor in the Department of Community Medicine and Nursing at the Norwegian University of Science and Technology (NTNU), affiliated with the Faculty of Medicine and Health Sciences. His research focuses on genetic epidemiology, particularly leveraging population-based health surveys (e.g., HUNT Study), electronic health records, and omics data to establish causal relationships in public health. Methodologically, he emphasizes Mendelian randomization and genetic epidemiology frameworks. Major Research Projects: HUNT Genotyping HUNT-COVID Questionnaire HUNT Metabolomics HUNT Methylation Research Interests: His work spans DNA methylation analysis, metabolomics, and the integration of omics data into epidemiological studies. He investigates causal links between genetic traits and diseases such as cardiovascular disorders, cancer, and respiratory conditions. Recent studies have explored intergenerational effects of maternal glycemic traits and parental BMI on offspring health outcomes. Publications Overview: His recent work highlights novel genetic loci for chronic low back pain, venous thromboembolism, and celiac disease. He has also contributed to large-scale meta-analyses of atrial fibrillation and breast cancer risk, emphasizing polygenic prediction and Mendelian randomization approaches. Labs/Teams: Primary affiliation with the HUNT Research Center and collaborations within NTNU’s epidemiology and genetics research groups.
Einar Malvin Rønquist is a Professor and Head of the Department of Mathematical Sciences at NTNU since August 2013. He holds a MSc from NTNU (1980) and a PhD from MIT (1988). His research focuses on numerical solutions of partial differential equations, spectral element methods, reduced basis methods, and computational fluid dynamics. He has been a leader in several research initiatives, including the Computational Science and Visualization program at NTNU (2003–2011). Rønquist is a member of prestigious academies: NTVA (since 2005) and DNKVS (since 2010). He has supervised 8 PhD students and 25 MSc students. His work spans computational science, with notable contributions to parametric modeling, parallel computing, and fluid dynamics simulation. His administrative roles include Vice President of R&D at Nektonics, Inc. (1991–1999) and Deputy Head of NTNU’s Department of Mathematical Sciences (Fall 2012). His publications highlight advancements in numerical methods for PDEs, including spectral element techniques, reduced basis approaches, and high-order approximations for complex geometries.
Hennes Alexander Hajduk is a Research Fellow at the University of Oslo's Section for Meteorology and Oceanography, part of the Department of Geosciences. He holds a PhD in Applied Mathematics from TU Dortmund University (2022). His work focuses on physical oceanography, numerical methods for fluid dynamics, and the influence of bottom topography on ocean flows. He develops property-preserving numerical schemes for conservation laws and shallow-water equations, with applications in geophysics and computational fluid dynamics. Education: PhD in Applied Mathematics (TU Dortmund University, 2022). Research Interests: Physical Oceanography: Investigating jet formation in stratified fluids and topographic effects on oceanic flows. Numerical Methods: Specializing in algebraic flux correction schemes, discontinuous Galerkin methods, and entropy-stable algorithms. Geophysical Modeling: Developing tools like FESTUNG for DG-based simulations in MATLAB/Octave. His publications emphasize stability, accuracy, and computational efficiency in simulating complex fluid systems. He collaborates on projects such as The Rough Ocean Research Group, advancing understanding of fluid dynamics in geophysical contexts. Affiliations: Section for Meteorology and Oceanography, University of Oslo Rough Ocean Research Group
Gudmund Horn Hermansen is an Associate Professor at the University of Oslo, affiliated with the Department of Mathematics within the Faculty of Mathematics and Natural Sciences. His research focuses on advanced statistical methodologies, including Bayesian analysis, time series modeling, and applications in fields such as conflict dynamics, neuroscience, and environmental science. He is a member of the Statistics and Data Science research group and collaborates with interdisciplinary teams on projects involving uncertainty quantification and statistical inference. Key research interests include change-point analysis, hidden Markov models, astrocytic calcium signaling in Alzheimer’s research, and probabilistic forecasting. His work bridges theoretical statistics with practical applications, such as analyzing democratization processes and reservoir parameter interactions. Hermansen has contributed to over 30 peer-reviewed publications, emphasizing methodological innovations and interdisciplinary collaborations. Notable publications include studies on Bayesian hidden Markov models in conflict research, astrocytic signaling mechanisms in sleep regulation, and statistical frameworks for temporal heterogeneity analysis. He maintains an active role in academic service, including editorial contributions and conference participation.
Esther Ulitzsch is an Associate Professor at the University of Oslo 's Centre for Educational Measurement (CEMO) . Her research focuses on advancing psychometric models, particularly Bayesian latent variable techniques for small-sample conditions, and analyzing digital interaction data from simulated learning environments. She holds a PhD from Freie Universität Berlin and previously worked as a Research Associate at the IPN – Leibniz Institute for Science and Mathematics Education in Kiel, Germany. Education: PhD in Educational Measurement (Freie Universität Berlin) Research Associate at IPN Kiel Research Interests: IRT model development for aberrant response detection Efficient estimation in small samples Clickstream analysis for student behavior Test-taking engagement dynamics Publications: Over 20 peer-reviewed articles since 2017, including work on mixture models for careless responding, neural networks for IRT estimation, and Bayesian factor modeling. Recent contributions address response time analysis, cross-country measurement invariance, and sequential process mining in interactive tasks. Affiliations: Active in the CREATE (Research on Equality in Education) and FREMO (Frontier Research in Educational Measurement) groups at CEMO.
Kolbjørn Engeland is a Professor at the Section for Geography and Hydrology, University of Oslo. His work focuses on hydrology, flood risk assessment, and climate change impacts on water resources, utilizing Bayesian and stochastic modeling techniques. He collaborates on international projects like 'Advancing frequency analysis of nonstationary hydrological extremes' and 'SnowSub'. Affiliation: University of Oslo, Department of Geosciences Research Groups: Hydrology and Water Resources, LATICE (Land-Atmosphere Interactions in Cold Environments) His research integrates climate science, statistical hydrology, and renewable energy planning. Key projects address flood risk reduction, snow sublimation in hydropower, and long-term hydrological variability. He has published extensively on Bayesian modeling, flood frequency, and climate-hydrology interactions. Recent publications include advancements in geostatistical runoff modeling, climate change adaptation in flood mapping, and stochastic methods in Nordic hydrology. His work spans both theoretical and applied hydrology, with applications to Norwegian and European catchments. Engeland’s advising and project leadership include collaborations with researchers in geosciences and water management, though specific student names are not listed. He contributes to sustainable hydropower analysis and climate change scenarios.
Prof. Dr. Pia Pinger is a Full Professor of Economics at the University of Cologne, specifically within the Faculty of Management, Economics and Social Sciences (WiSo-Fakultät) and the Department of Economics. She has held this position since 2019 and serves as a Cluster Faculty Member and Speaker of the excellence cluster ECONtribute - Markets & Public Policy. Dr. Pinger is also a Principal Investigator in the Center for Social and Economic Behavior (C-SEB) and the Collaborative Research Center Economic Perspectives on Societal Challenges. Her institutional affiliations include IZA Research Fellow and CESifo Affiliate status. Dr. Pinger earned her PhD from the University of Mannheim in 2013, following research positions at the University of Mannheim and the Centre for European Economic Research (ZEW). Prior to her current role, she served as an Assistant Professor at the University of Bonn (2013-2019) and completed visiting scholar appointments at the University of Chicago. Her research program focuses on human capital and socioeconomic inequalities, with particular emphasis on educational decision-making, early childhood health, applied microeconometrics, and behavioral economics. Dr. Pinger investigates how socioeconomic background influences educational and labor market outcomes through rigorous empirical analysis using natural experiments and causal inference methods. Her work examines gender wage gaps, decision-making at critical life junctures, and the formation of economic preferences from childhood, providing insights into inequality mechanisms and potential policy interventions. Dr. Pinger's publication record reveals a consistent focus on socioeconomic inequality across the life course, with recent work examining gender differences in wage expectations (2024), socioeconomic status effects on children's cognitive development (2021), and causal evidence on prosocial behavior formation (2020). Her research spans labor economics, health economics, and behavioral economics, often connecting micro-level decision-making to broader societal outcomes through sophisticated econometric techniques. ERC Starting Grant (2023) - €1.5 million for OPPORTUNITY project Prize for best dissertation in education economics (2015) Karin Islinger dissertation award (2014) Dissertation prize 'The Future of Labor' (2014) HCEO Emerging Scholar designation (2014) Elected to 'Ausschuss für Bildungsökonomie' (2017) As a Principal Investigator in multiple research centers, Dr. Pinger leads collaborative projects examining economic behavior and policy. Her ERC-funded OPPORTUNITY project represents a major research initiative analyzing how ability signals like grades influence educational trajectories based on socioeconomic background. She actively contributes to academic discourse through media appearances in Süddeutsche Zeitung, DER SPIEGEL, and multiple podcasts addressing educational inequality and economic decision-making. Recent press releases indicate ECONtribute's funding extension through 2025, highlighting the ongoing significance of her research environment.
