Find Academic Supervisors

• Sexology
• Gender Studies
• Behavioral Sciences
• +3 more

Christian Graugaard is a Professor of Sexology at Aalborg University, affiliated with the Faculty of Medicine and the Department of Clinical Medicine. He is a key member of the Center for Sexology Research and leads Project SEXUS, aiming to study Danish sexual behavior comprehensively. His work emphasizes the intersection of biological, psychological, and cultural factors in human sexuality, challenging simplistic gender-based stereotypes. Research interests include gender differences in sexual behavior, societal norms influencing sexual health, and the cultural dimensions of human sexuality. He actively participates in public discourse, as seen in his DR-podcast interview on 'Ramt af kærlighed,' where he discussed the complex interplay between biology and culture in shaping sexual identities. Though no specific awards or grants are detailed here, his publications span advanced technical domains like spatiotemporal data analysis, federated learning, and trajectory modeling, suggesting interdisciplinary research collaborations. His work on systems like OneDB and SWASH highlights contributions to distributed computing and data science, which may underpin his methodologies in large-scale sexual behavior studies. He currently holds no listed students or formal advisees in the provided texts, and his involvement in labs/teams is limited to the Center for Sexology Research and Project SEXUS.

• Artificial Intelligence
• Machine Learning
• Bayesian Mathematics
• +3 more

Petr Taborsky is a postdoctoral researcher affiliated with the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU). His work focuses on artificial intelligence, machine learning, and computational methods within the Cognitive Systems group. Research interests include Bayesian inference , deep learning generalization , and graph-based learning , with applications in high-performance computing and federated learning . Key contributions involve developing the Bayesian Cut method for clustering and analyzing gradient noise in AI models. Recent publications highlight trends in European HPC/AI collaboration (2025) Bayesian graph cut techniques (2022) Statistical modeling in machine learning (2021)

Steffan Wittrup McPhee ChristensenView profile

Associate Professor

• Medicine
• Musculoskeletal Pain
• Pain
• +15 more

Steffan Wittrup McPhee Christensen is an Associate Professor at the Department of Medicine and Health Technology , Aalborg University , Denmark. His work bridges musculoskeletal physiotherapy and clinical biomedicine , focusing on neck and back pain , pain sensitivity , and exercise-based interventions . Academic Roles : Board member of the International Association for the Study of Pain (IASP) and Danish Physiotherapists Research Foundation since 2023. Teaching Philosophy : Emphasizes problem-based learning (PBL) and clinical simulation to develop clinical reasoning and rehabilitation planning skills. Research Interests include: Musculoskeletal disorders (neck/shoulder/back pain) Pain sensitivity and movement analysis Exercise interventions and clinical guidelines Global Burden of Disease applications to chronic pain management His scientific contributions span 114 publications (2011–2025) and 19 media appearances , including critiques of postural correction clothing as pseudoscience. Education : PhD in Clinical Science and Biomedicine (2018) Assistant Professor of Education (2016–2017) External Associate Professor at University College of Northern Denmark (2018–present)

Manja Gersholm GrønbergView profile

Researcher

• Statistical Genetics
• Machine Learning
• Biostatistics
• +5 more

Manja Gersholm Grønberg is a Postdoctoral researcher at the Technical University of Denmark (DTU) in the Department of Applied Mathematics and Computer Science, specifically within the Statistics and Data Analysis group. Her interdisciplinary research bridges statistics, computer science, and biomedical applications, contributing to several UN Sustainable Development Goals related to health and well-being. Her research interests span statistical genetics, machine learning, biostatistics, neuroscience, and data analysis with particular expertise in ordinal data modeling and single-cell RNA sequencing analysis. Dr. Grønberg's work demonstrates strong methodological innovation in crossed random effects models and neighborhood analysis techniques applied to complex biological datasets. Her recent publications (2024-2025) reveal a strong trend toward interdisciplinary applications, with significant contributions in both bioinformatics (scRNAseq data analysis) and neuroscience (brain stimulation techniques for Alzheimer's disease treatment). These works demonstrate her ability to develop sophisticated statistical methods and apply them to cutting-edge biomedical problems. Expertise in Crossed Random Effects modeling Specialization in Imbalanced Data techniques Research in Intranasal Oxytocin applications Advanced Neighborhood Analysis methods Cell Specification computational approaches Dr. Grønberg has served as an internal examiner for Statistical Genetics courses at DTU, demonstrating her expertise and teaching capabilities in this specialized field. Her completed PhD project on 'Computational methods for ordinal mixed models applicable to online user ratings' established her foundation in advanced statistical modeling. Her research team collaborations span multiple disciplines, connecting statistical methodology with biological and medical applications, particularly in the areas of neurodegenerative disease research and single-cell genomics.

Aksel Karl Georg JensenView profile

Assistant Professor

• Causal inference
• Mediation analysis
• Observational vaccination studies
• +3 more

Aksel Karl Georg Jensen is an Assistant Professor in the Section of Biostatistics within the Department of Public Health at the Faculty of Health and Medical Sciences, University of Copenhagen. His research profile is centered around developing and applying advanced statistical methodologies to address complex questions in epidemiology and public health. His primary research interests include: Causal inference methodologies Mediation analysis techniques Observational vaccination studies Epidemiological study designs Regression modeling approaches Survival analysis methods Dr. Jensen's scholarly work demonstrates a strong focus on methodological development for clinical trials, vaccination studies in global health contexts (particularly in Guinea-Bissau), and investigations into social determinants of health outcomes through European birth cohort studies. His research spans both theoretical methodological development and applied epidemiological investigations, with particular emphasis on causal frameworks and mediation techniques. His scientific contributions include numerous peer-reviewed publications across biostatistics, epidemiology, and clinical research domains. His collaborative network extends internationally, with significant work in West African vaccination research and multinational European cohort studies. His research has received attention from news outlets, academic social media, and scholarly platforms, indicating substantial impact within both academic and broader communities.

• Animal Welfare
• Veterinary Epidemiology
• Precision Livestock Farming
• +3 more

Dan Børge Jensen serves as Associate Professor at the University of Copenhagen's Department of Veterinary and Animal Sciences, holding dual appointments in the Production, Nutrition and Health section and Animal Welfare and Disease Control section. His research integrates veterinary science with advanced data analytics to address critical animal welfare challenges across diverse production systems. His primary research interests focus on precision livestock farming methodologies , particularly video-based behavioral monitoring for early detection of welfare issues like piling in hens and tail-biting in pigs. He develops statistical models for predicting health outcomes such as footpad lesions in broilers and post-operative complications in equine dentistry, while also pioneering decision-support systems through the DECIDE project that transform surveillance data into actionable farm management tools. Analysis of his recent publications reveals a strong interdisciplinary trend combining veterinary epidemiology with machine learning and dynamic modeling, spanning poultry, swine, equine, and aquaculture sectors. His work demonstrates consistent application of data-driven approaches to improve animal health monitoring and production efficiency. Dr. Jensen maintains active international collaborations, with research outputs appearing in journals including Smart Agricultural Technology , Frontiers in Marine Science , and Equine Veterinary Journal . His work shows significant practical impact through measurable downloads and academic engagement, though no formal awards or student supervision details are documented in available sources.

• Geogenetics
• Ancient DNA
• Population Genetics
• +3 more

Cristina-Irina Tica serves as a Postdoctoral Researcher (Research Fellow) at the Section for Geogenetics within the Globe Institute, University of Copenhagen. Her work bridges geogenetics and forensic anthropology through advanced statistical modeling. Her primary research focuses on Geogenetics and Ancient DNA analysis, with specialized interests in Population Genetics, Forensic Anthropology, and Bayesian statistical applications for human decomposition modeling. This interdisciplinary approach integrates taphonomic processes with genetic methodologies to reconstruct postmortem timelines. Her 2025 publication in Forensic Science International demonstrates a clear trend toward computational forensic anthropology, utilizing Bayesian frameworks to analyze decomposition variables. This reflects broader shifts in the field toward data-driven approaches for death investigation and postmortem interval estimation. As part of the Section for Geogenetics team, she contributes to collaborative projects examining ancient human DNA signatures in forensic contexts, working within Copenhagen's interdisciplinary research ecosystem focused on evolutionary genetics and anthropological applications.

• Computational Biology
• Structural Biology
• Molecular Dynamics
• +4 more

Emil Thomasen serves as a Guest Researcher in the Department of Biology within the Biomolecular Sciences unit at the University of Copenhagen's Faculty of Science. His research integrates computational methods with experimental structural biology approaches to investigate complex biomolecular systems. Position: Guest Researcher Institution: University of Copenhagen Department: Department of Biology Research Unit: Biomolecular Sciences Contact: fe.thomasen@bio.ku.dk | +4535323586 Thomasen's research focuses on developing and applying computational methodologies to understand protein structure, dynamics, and interactions. His work bridges quantum mechanics, molecular dynamics simulations, and experimental techniques including small-angle X-ray scattering (SAXS) and cryo-electron microscopy. He has made significant contributions to coarse-grained modeling, particularly with the Martini force field, and has pioneered approaches combining machine learning with quantum mechanical calculations for large molecular assemblies. His publication record demonstrates a clear trajectory in computational structural biology, with recent work emphasizing the integration of multiple experimental and computational techniques to characterize complex protein systems. The research shows increasing sophistication in handling large-scale biomolecular assemblies and applying advanced statistical methods like Bayesian inference for model refinement. Thomasen has established strong collaborative networks, frequently working with Professor K. Lindorff-Larsen and other researchers across computational chemistry and structural biology disciplines. His work has appeared in high-impact journals including Nature Communications, eLife, and Journal of Chemical Theory and Computation. As a recently completed Ph.D. graduate (2024), Thomasen continues to advance his research program as a Guest Researcher, building on his doctoral work focused on integrating coarse-grained molecular dynamics with SAXS data for characterizing multidomain protein assemblies.

Michael Charles SachsView profile

Associate Professor

• Biostatistics
• Causal Inference
• Survival Analysis
• +3 more

Michael Charles Sachs serves as Associate Professor in the Department of Public Health, Section of Biostatistics at the University of Copenhagen's Faculty of Health and Medical Sciences. He holds a Doctorate in Biostatistics from the University of Washington (awarded August 15, 2011) and maintains an active research program with publications spanning 2022-2025. His primary research focuses on biomarker signatures for treatment selection , computational methods for deriving symbolic bounds on causal effects , and regression modeling of cumulative estimands with censored event history data . His general areas of interest include reproducible research, computational statistics, R programming, Bayesian nonparametric models, and survival analysis. Professor Sachs teaches the advanced course "Programming and Statistical Modeling in R" for PhD students and health researchers, covering programming principles, loops, functions, and efficient data manipulation. His recent publications demonstrate expertise in causal inference methodology, survival analysis techniques, and statistical software implementation, with multiple articles accepted for publication in 2025. His work spans theoretical methodology development and practical applications in medical research, particularly in gastroenterology and celiac disease prediction. His scholarly output shows consistent productivity with multiple first-author publications in high-impact biostatistics journals including Journal of Statistical Software, Journal of Computational and Graphical Statistics, and Biostatistics. He actively organizes academic activities, including a May 2025 workshop on statistical modeling in R.

• Reward decision-making
• risk-taking
• neuroeconomics
• +4 more

Oliver James Hulme serves as Associate Professor in the Department of Psychology within the Faculty of Social Sciences at the University of Copenhagen. His office is located at Øster Farimagsgade 2A, 1350 København K, with scheduled office hours on Thursdays from 12:00-13:00. His research focuses on: Reward decision-making risk-taking neuroeconomics functional neuroimaging Bayesian modelling cognitive computational neuroscience open science Publications from 2013-2024 demonstrate sustained investigation into neural mechanisms of decision processes, particularly in Parkinson's disease, aging populations, and eating disorders. His methodology integrates fMRI, computational modeling, and behavioral paradigms to examine risk assessment, neural connectivity, and cognitive control under varying physiological states. No scientific awards were documented in the source material. Details regarding student supervision, grant funding, and laboratory infrastructure were not provided in the available information.

• Epistemology
• Disagreement
• Bayesian Modelling
• +5 more

Josefine Lomholt Pallavicini serves as a Teaching Assistant Professor in the Department of Science Education within the Faculty of Humanities at the University of Copenhagen. Her research bridges formal epistemology, Bayesian modeling, and the philosophy of scientific practice. Her primary research interests span epistemology, social epistemology, Bayesian modeling of disagreement, higher-order evidence, and diagrammatic reasoning in mathematics. She investigates how statistical formal models can explain phenomena like polarization and trust dynamics in epistemic communities, with particular focus on updating Bayesian frameworks to incorporate higher-order beliefs about belief formation reliability. Analysis of her four recent publications reveals a cohesive research trajectory focused on formal modeling of epistemic phenomena. Her work spans historical analysis of mathematical formalism (2022), computational modeling of group polarization (2021), and typological studies of mathematical diagrams (2018-2021), consistently applying formal methods to philosophical questions about evidence, disagreement, and representation. She is affiliated with the Social Epistemology Research Group (SERG) and contributed to the DFF-project 'The social epistemology and social psychology of disagreement.' Her research involves interdisciplinary collaboration with mathematicians and cognitive scientists, particularly on diagrammatic representation projects with M. W. Johansen and M. Misfeldt. Her laboratory and team involvement centers on SERG (Social Epistemology Research Group), where she collaborates on projects examining disagreement dynamics and higher-order evidence. Her work integrates computational modeling with traditional philosophical analysis, operating at the intersection of formal epistemology and cognitive science.

• Epigenetics
• Paleontology
• Conservation Genetics
• +2 more

Farideh Moharrek serves as an Academic Research Officer in the Department of Immunology and Microbiology within the Faculty of Health and Medical Sciences at the University of Copenhagen. Based at the FACS Core Facility (Nørre Allé 14, 2200 København N), she contributes to immunological and microbiological research through advanced cellular analysis infrastructure and collaborative scientific projects. Her research spans epigenetics, paleontology, and conservation genetics with emphasis on evolutionary mechanisms and biodiversity applications. Key investigations include epigenetic plasticity in organ speciation via sperm DNA methylation, Bayesian modeling of bryozoan diversification from fossil records, and policy-relevant genetic diversity indicators for the Convention on Biological Diversity. This interdisciplinary work bridges molecular biology, evolutionary history, and conservation science. Analysis of her 2021-2022 publications reveals strong transdisciplinary collaboration across epigenomics, paleontology, and conservation policy domains. Her work integrates high-throughput genomic data, statistical fossil record modeling, and conservation genetics frameworks, demonstrating methodological versatility in addressing both fundamental evolutionary questions and practical biodiversity challenges. As part of the FACS Core Facility team, Moharrek supports flow cytometry and cell sorting services essential for immunological research at the university. This facility provides critical infrastructure for cellular analysis across multiple research groups within the Department of Immunology and Microbiology.

Jørgen Holm PetersenView profile

Associate Professor

• Inter-rater agreement
• Reference curves
• Latent variable models
• +2 more

Jørgen Holm Petersen serves as an Associate Professor in the Department of Public Health within the Faculty of Health and Medical Sciences at the University of Copenhagen. His primary academic affiliation centers on the Section of Biostatistics, where he maintains an active research profile with over 240 research outputs and significant collaborative networks across international institutions. His research expertise spans specialized statistical methodologies including inter-rater agreement analysis, reference curve development, latent variable modeling, and variance components models. Current work focuses on Bradley-Terry models with variance components for estimation and inference, particularly in rater agreement contexts. His methodological innovations directly support clinical and epidemiological investigations across endocrinology, environmental health, and public health domains. Recent publication trends reveal strong engagement with endocrine development research (puberty studies, hormone assays), environmental carcinogenesis (PFAS/organochlorine exposures), and health disparities (long COVID, vaccination uptake). His statistical frameworks enable sophisticated analysis of complex human exposures and longitudinal health outcomes, frequently applied through collaborations with clinical researchers at Copenhagen University Hospital. Petersen actively contributes to academic discourse through lectures on biostatistical applications in diverse fields (astronomy, voice research, cosmology) and service on review committees. His methodological presentations address critical issues in clinical trial randomization, instrumental variable techniques, and rating scale modeling for observer variation. Professional activities include editorial roles, committee chairmanships (e.g., Assessment Committee since 2014), and extensive lecture contributions. His work bridges theoretical statistics with practical healthcare applications, particularly in developmental endocrinology and environmental epidemiology.

• Critical Care Medicine
• Anaesthesiology
• Intensive Care Unit (ICU)
• +4 more

Morten Hylander Møller serves as Clinical Professor in the Department of Clinical Medicine at the University of Copenhagen, with clinical responsibilities in Anaesthesiology at Copenhagen University Hospital (Region H). His academic work centers on advancing evidence-based practices in intensive care through large-scale collaborative research. His research portfolio spans critical care methodology and clinical implementation: Development of core outcome sets for ICU trials using Delphi consensus Pharmacovigilance in critical care (e.g., amiodarone toxicity) Adaptive clinical trial design innovations Nationwide antibiotic consumption surveillance Sepsis guideline evaluation frameworks Scandinavian end-of-life care standardization Recent publications reveal a strategic focus on methodological rigor in ICU research, particularly through platform trials and international consensus-building. His work consistently addresses implementation gaps between clinical evidence and ICU practice, with strong emphasis on Scandinavian healthcare contexts and multinational collaboration patterns visible across all 2025 publications. Professor Møller actively contributes to major initiatives including the CLASSIC septic shock trial and Scandinavian Delphi consensus projects, demonstrating leadership in translating research into standardized ICU protocols across Nordic healthcare systems.