Find Academic Supervisors

• Longitudinal Data Analysis
• Time-to-Event Analysis
• Survival Analysis
• +5 more

Alessandra Meddis serves as an Assistant Professor in the Section of Biostatistics within the Department of Public Health at the University of Copenhagen's Faculty of Health and Medical Sciences. Her academic work centers on developing and applying advanced statistical methodologies for longitudinal and time-to-event data analysis, with significant contributions to public health research in Denmark and internationally. Her institutional affiliation is clearly established through university contact details and departmental listings. Her primary research interests include correlated survival data analysis, competing risk modeling, informative cluster size methodology, causal inference techniques for observational studies, and environmental epidemiology applications. Dr. Meddis has developed specialized expertise in handling complex survival data structures while maintaining focus on real-world public health problems, particularly in HIV comorbidity patterns, environmental exposure effects, and pandemic-related mortality analyses. Her methodological innovations directly address challenges in clustered and censored data common across medical research domains. Analysis of Dr. Meddis's recent publication record reveals a consistent trajectory of high-impact interdisciplinary research spanning clinical medicine, epidemiology, and statistical methodology. Her work appears in leading journals across biostatistics, infectious diseases, and public health, demonstrating strong collaborative networks with clinical researchers and epidemiologists. Key thematic areas include HIV treatment outcomes, environmental health exposures, and critical care applications during the pandemic, with recent methodological papers advancing survival analysis techniques for complex data structures. Scientific Awards: No scientific awards were specified in the available institutional profile. Advising and Grants: The institutional profile does not provide details regarding graduate student supervision or specific research grant funding. Her collaborative publications suggest involvement in multi-investigator projects including the COCOMO HIV cohort study and pandemic-related research initiatives. Labs and Teams: Dr. Meddis is affiliated with the Section of Biostatistics within the Department of Public Health, though specific laboratory facilities or dedicated research teams are not described in the source material. Her extensive co-authorship patterns indicate active participation in multiple research consortia across medical specialties.

John W. EdmundsView profile

Professor

• Infectious Disease Modelling
• Epidemiology
• Public Health Policy
• +6 more

Professor John W. Edmunds is a leading academic in Infectious Disease Modelling at the London School of Hygiene and Tropical Medicine (LSHTM). Holding a Professor position since 2013 and serving as Dean of the Faculty of Epidemiology and Population Health (2013-2019), he combines mathematical, statistical, and economic models to inform public health policy. His part-time role at the Health Protection Agency (HPA) since 2008 underscores his policy advisory contributions. PhD in Infectious Disease Modelling (Imperial College, 1994) MSc in Health Economics (University of York, 1995) BSc in Biology (Imperial College, 1989) His research focuses on understanding disease transmission and optimizing control strategies. He has pioneered methods integrating social contact surveys , participatory surveillance (e.g., Influenzanet), and economic analysis to evaluate vaccines and interventions. Recent work includes SARS-CoV-2 dynamics , Ebola spatial forecasting , and typhoid vaccine prioritization . His 15 most recent publications highlight social contact patterns (Reconnect, CoMix studies), vaccine impact (HPV, typhoid), and real-time outbreak analytics (Ebola, cholera). Key trends include digital epidemiology , behavioral surveillance , and cross-country modeling for global health. Knighthood (2024) for services to epidemiology Weldon Memorial Prize (2022) for biostatistics contributions FMedSci (2018) for medical science excellence OBE (2016) for public service As an educator, he teaches "Modelling and the Dynamics of Infectious Diseases" and co-organizes "Pandemics: Emergence, Spread and Response" . Current grants include National Institute for Health and Care Research projects on post-pandemic surveillance and Bill & Melinda Gates Foundation funding for polio eradication. He leads collaborations with the Centre for Mathematical Modelling of Infectious Diseases , Vaccine Centre , and Health in Humanitarian Crises Centre , while advising UK and WHO committees on zoonotic influenza , variants , and testing programs .

Søren Lundbye-ChristensenView profile

Associate Professor

• Biostatistics
• Medical Statistics
• Cardiovascular Research
• +7 more

Søren Lundbye-Christensen is an Associate Professor and Biostatistician affiliated with the Clinical Institute at the Faculty of Health Sciences, Aalborg University, and Aalborg University Hospital in Denmark. He specializes in biostatistical support for medical research, with a strong emphasis on cardiovascular and epidemiological studies. His research interests include biostatistics, survival analysis, cohort studies, clinical epidemiology, and statistical modeling in public health. He has contributed to a wide array of healthcare research, particularly in cardiovascular diseases, cancer, maternal health, and infectious diseases. His methodological expertise spans time-to-event analysis, registry-based research, and interval-censored data modeling. The recent publications highlight a strong trend in applying advanced statistical methods to large-scale clinical and population-based datasets. His work often involves collaboration with medical researchers to derive prognostic models, validate clinical databases, and assess public health outcomes. Key themes include cardiovascular risk, fertility, cancer biomarkers, and implementation of medical training programs. Scientific Contributions and Recognition: Published over 320 research articles and datasets. Active contributor to methodological advancements in biostatistics. Regular peer reviewer, including for journals like the R Journal. Public engagement through media appearances on statistics and health. Academic Advising and Grants: Søren has supervised 31 student theses, formally serving as PhD supervisor for 14 theses and as a biostatistical advisor for 19 others, primarily in mathematics and statistics. He has participated in numerous research projects funded through institutional and national grants, including studies on seasonal disease trends, postoperative complications, and metabolic disease prediction. His work often involves interdisciplinary collaboration across medicine, public health, and data science. Labs and Research Teams: He is embedded in collaborative research networks at Aalborg University Hospital and Aalborg University, contributing statistical expertise to clinical research groups. He is involved in projects utilizing Danish national health registries and has contributed to the development and validation of clinical databases. His work supports both hypothesis-driven medical research and methodological innovation in biostatistics.

• Statistical Inference
• Stochastic Processes
• Biomathematics
• +5 more

Susanne Ditlevsen is a Professor at the Department of Mathematical Sciences , University of Copenhagen. Her research focuses on statistical inference for stochastic processes , mathematical modeling of physiological systems , nonlinear dynamics , neuroscience , and biomathematics . Research : She develops statistical methods for diffusion processes, hidden Markov models, and stochastic differential equations, with applications in biomedical data and marine mammal behavior. Teaching : Covers basic statistics, probability, stochastic processes, regression, and generalized linear models. Publications highlight her work on climate tipping points (2023, Nature Communications ), nonlinear neuronal systems (2017), and statistical ecology (2020). Her collaborations span Denmark, France, and international institutions.

Rasmus WaagepetersenView profile

Professor

• Spatial Statistics
• Quantitative Genetics
• Markov Chain Monte Carlo Methods
• +3 more

Rasmus Waagepetersen is a Professor in the Department of Mathematical Sciences at Aalborg University, affiliated with The Faculty of Engineering and Science. His research focuses on spatial statistics, quantitative genetics, and statistical methodology for spatial point processes. He leads and participates in interdisciplinary projects such as urbanLab (spatial data analysis for urban planning) and studies on microbiome interactions in agricultural systems. Key research areas include spatial point processes, Markov chain Monte Carlo methods, and statistical inference for complex ecological and biomedical data. His work frequently involves collaborations with environmental and biological scientists, as seen in projects analyzing root microbiota assemblies in legumes and climate data for building simulations. Waagepetersen has contributed to methodological advancements in spatial statistics, including goodness-of-fit tests, likelihood-based inference for log Gaussian Cox processes, and quasi-likelihood approaches for case-control point pattern data. His research has been supported by grants from institutions like the Villum Foundation. Key Projects: urbanLab, Klimadata til fugtsimuleringer, Nod factor signaling in plant microbiota. Grants: Multiple projects funded by the Villum Foundation and Danish research councils. His recent publications address topics such as space-time point processes, microbiome data analysis, and statistical modeling in education. Waagepetersen maintains an active research group and collaborates internationally on both theoretical and applied statistical problems.

• Biostatistics
• Item Response Theory (IRT) models
• Scale validation
• +5 more

Karl Bang Christensen is a Professor at the Department of Public Health, Section of Biostatistics, within the Faculty of Health and Medical Sciences at the University of Copenhagen. His primary research areas include Biostatistics, Item Response Theory (IRT) models, scale validation, patient-reported outcomes (PRO), and multi-state models for sickness absence analysis. Research interests: Rasch models and latent variable models for health outcomes Statistical methods for evaluating PRO instruments Exercise interventions in cancer rehabilitation Multi-state modeling of administrative register data (sickness absence, unemployment, disability pension) Article trends: His publications focus on Rasch models, IRT, survival analysis, clinical trials, and health education. Recent work addresses preventive health interventions in dermatology, while earlier studies emphasize cognitive dysfunction, migraine treatment, and social determinants of sickness absence. Teaching: He teaches statistics at the Master of Health Sciences and PhD levels.

• Functional data analysis
• Statistical inference for dependent data
• Statistical inference for stochastic processes
• +3 more

Helle Sørensen is a Professor at the Department of Mathematical Sciences, University of Copenhagen. Her work bridges theoretical and applied statistics with interdisciplinary applications in biological and environmental sciences. Education : BSc (1993), MSc (1997), PhD (2000) in Statistics from University of Copenhagen. Employment : Professor (2018–present), Head of Data Science Lab (2018–2021), Professor MSO and head of Laboratory for Applied Statistics (2013–2018), Associate/Assistant Professor across multiple departments (2000–2013). Research Interests focus on: Functional data analysis Statistical inference for dependent data and stochastic processes Applications in biology, agriculture, and food science Her recent publications highlight statistical methodologies applied to: Enzymatic degradation of plant material Multivariate analysis in metabolic studies Random forest efficiency in metric spaces Quantile regression for longitudinal data Child food texture preferences and insect acceptance Teaching includes courses in basic probability, statistical theory, and applied statistics for bio/life sciences students. She supervises BSc, MSc, and PhD students in Statistics with co-supervision roles in interdisciplinary fields.

• Population Genetics
• Bioinformatics
• Genomic Data Analysis
• +6 more

Anders Albrechtsen is a Professor at the Bioinformatics Centre, Department of Biology, University of Copenhagen, specializing in computational and RNA biology. He leads research in statistical and computational methods for genomic data analysis with a focus on population genetics, particularly in isolated populations like the Greenlandic Inuit. Education: Natural Science Basic Education, Roskilde University Centre, Denmark (2000-2002) BSc in Molecular Biology, Roskilde University Centre, Denmark (2003) Mathematics, Roskilde University, Denmark (2002-2004) MSc in Bioinformatics, Copenhagen University, Denmark (2006) PhD from the Department of Biostatistics, Copenhagen University, Denmark (2009) Albrechtsen's research focuses on developing statistical and computational methods for genomic data analysis, with particular emphasis on multi-loci association studies, population structure analysis, and next-generation sequencing data. His work bridges computational methods development with applied population genetics, contributing significantly to understanding human and wildlife genomics. His research group develops open-source software available at www.popgen.dk/software. His recent publications demonstrate expertise across population genetics, genomic methods development, and medical applications, with numerous high-impact papers in journals like Nature, Cell, and Nature Communications. His work often involves large-scale genomic studies of human populations (particularly Greenlandic Inuit) and wildlife species, addressing questions related to population history, adaptation, and disease genetics. Scientific Recognition: Lundbeck Fellow (10M DKK, 2016-2021) Novo Ascending Investigator (10M DKK, 2021-) Villum Young Investigator Programme (2.3M DKK, 2011-2015) Albrechtsen actively supervises students and researchers, currently serving as main supervisor for 6 PhD students (with 8 completed), 2 postdocs, and 1 master's student (with 25 completed). He has secured significant research funding as PI and co-PI, including large collaborative grants like LuCamp (60M DKK) and the UCPH Excellence Programme (36M DKK). His research group maintains strong international collaborations, particularly with institutions in the United States. He serves as a journal reviewer for prestigious publications including Nature Genetics, Genome Research, and American Journal of Human Genetics, contributing to the scientific community through peer review and mentorship.

• Biostatistics
• Causal Inference
• Machine Learning
• +3 more

Thomas Alexander Gerds is a Professor in the Department of Public Health, Section of Biostatistics, at the University of Copenhagen's Faculty of Health and Medical Sciences. His research focuses on the development and application of statistical methods for analyzing binary, longitudinal, and time-to-event data, with a particular emphasis on causal inference and machine learning in the context of medical and public health studies. Gerds' primary research areas include causal inference, machine learning for pharmacoepidemiology, and statistical methodology for survival analysis. He collaborates with the Danish Heart Foundation on registry data studies, aiming to improve study design and causal conclusions in observational research. His work spans prediction modelling strategies, competing risk models, and the development of statistical software for applications in cardiology and public health. His recent publications (2024-2025) demonstrate a strong focus on applying advanced biostatistical methods to diverse medical fields. Key trends include the development of risk prediction models for conditions like kidney failure and cardiovascular disease, causal inference in pharmacoepidemiology (e.g., studying cholesterol-lowering drugs), and longitudinal mediation analysis. His work often involves registry-based cohort studies and systematic reviews, with applications in dentistry, neurology (cerebral palsy), diabetes, and emergency medicine.

Marie-Pier Bergeron BoucherView profile

Associate Professor

• Demography
• Mortality Forecasting
• Health Inequalities in Ageing
• +4 more

Marie-Pier Bergeron Boucher is an Associate Professor at the Interdisciplinary Centre on Population Dynamics (CPop) within the Faculty of Business and Social Sciences at the University of Southern Denmark. Her research focuses on mortality forecasting, lifespan differentials, and the development of demographic methods to analyze health and mortality trends in industrialized societies. Key themes include mortality decomposition, cause-of-death analysis, and healthy life expectancy projections. Her work spans international comparisons of longevity, socioeconomic disparities in survival rates, and the application of advanced statistical techniques like compositional data analysis. Notable projects include the ERC-funded 'Unequal Lifespans' initiative and the AXA Chair in Longevity Research. She collaborates widely with institutions globally and contributes to policy-relevant topics such as pension age indexation and retirement age survival forecasts. Dr. Bergeron Boucher holds a Ph.D. in Demography and has taught courses on R programming for demographic analysis, introducing students to modern computational tools in population studies. She actively participates in academic conferences and has authored over 40 peer-reviewed publications, reflecting her expertise in formal demography and mortality modeling.

• Epidemiological methods
• Network science
• Global Health
• +7 more

Dr. Diego Bassani is an Associate Professor of Epidemiology at the Dalla Lana School of Public Health and the Department of Pediatrics at the University of Toronto. He holds concurrent appointments as a Senior Scientist at The Hospital for Sick Children and Director of the International Program Evaluation Unit at the Centre for Global Child Health. His interdisciplinary work bridges epidemiology and network science to advance population health measurement. M.Sc., Ph.D. (Epidemiology) His research emphasizes large-scale epidemiological studies, network science applications, and methodological innovations in maternal and child health. Current projects include reconstructing population networks from national survey data, developing novel sampling designs, and enhancing timeliness in public health surveillance. Recent work explores allometric scaling, microbiota associations, and neonatal probiotic interventions. Key trends in his recent publications include network-based population health modeling (SEEDNet), microbiota analysis in Bangladeshi infants, and methodological advancements in cross-country health data synthesis. These studies span epidemiology, microbiology, and computational approaches. Dr. Bassani leads projects funded by the New Frontiers in Research Fund, NSERC, CIHR, Bill & Melinda Gates Foundation, and Global Affairs Canada. His methodological focus on network science aims to revolutionize health data collection and disease pattern detection. He collaborates with the ISI Foundation and contributes to open-source data infrastructure through initiatives like SEEDNet, supporting global health research and policy formulation.

Mette SørensenView profile

Associate Professor

• Genetic Epidemiology
• Aging Research
• Longevity Studies
• +5 more

Mette Sørensen is an Associate Professor at the Institute for Health Services Research within the Faculty of Health Sciences at the University of Southern Denmark. She leads research in genetic epidemiology, aging, longevity and functional genomics. With a Master of Science and PhD, her academic career has focused on understanding the molecular mechanisms of aging through twin studies and multi-omics approaches. Her research interests center on genetic and epigenetic factors influencing aging processes, with specific expertise in DNA methylation, epigenetics, and twin study methodologies. Sørensen's work examines how genetic and molecular biological factors affect aging trajectories, longevity, and age-related diseases. She applies multi-omics approaches including epigenomics, proteomics, and metabolomics to identify biomarkers of aging and longevity. Dr. Sørensen's recent publications demonstrate a strong focus on epigenetic clocks, DNA methylation patterns in aging, cardiovascular health in relation to molecular markers, and the use of twin studies to disentangle genetic and environmental influences on aging. Her work spans from basic molecular mechanisms to clinical applications in gerontology. Her scientific achievements have been recognized with prestigious awards including the Manufacturer Vilhelm Pedersen and Wife's Memorial Grant from the Novo Nordisk Foundation and The Danish Council for Independent Research Postdoctoral Fellowship. As an active researcher, Sørensen serves as a peer reviewer for journals including Scientific Reports and Aging Cell, participates in major conferences like The Gerontological Society of America Annual Scientific Meeting, and contributes to significant research projects such as LLFS: Længe Leve - et Familiestudie (Long Life Study). She also engages with the public through media interviews about DNA methylation age, aging, and longevity research.

Heidi Søgaard ChristensenView profile

Assistant Professor

• Clinical Data Science
• Inflammatory Bowel Disease
• Oncology
• +12 more

Heidi Søgaard Christensen is an Assistant Professor at the Department of Clinical Medicine, Faculty of Medicine, Aalborg University (AAU), Denmark. She is also affiliated with the Center for Clinical Data Science, reflecting her dual expertise in clinical research and data analytics. Her work integrates real-world evidence, population-based cohort studies, and advanced statistical methods to improve understanding and outcomes in complex diseases such as inflammatory bowel disease (IBD) and cancer. Her research interests are centered around clinical data science , inflammatory bowel disease , oncology , immunotherapy , pharmacoepidemiology , and biostatistical methodology . She leverages large Danish national registries to conduct high-impact studies on treatment patterns, drug safety, and disease progression. The 15 most recent publications highlight a strong trend toward real-world evidence generation, particularly in IBD and non-small cell lung cancer. Her work spans clinical outcomes, genetic risk prediction, imaging diagnostics, and methodological innovations such as extensions to Bland-Altman plots for multiple observers. These articles reflect interdisciplinary collaboration across gastroenterology, oncology, radiology, and statistics. PhD supervision: 1 student supervised Media coverage: 1 item, including social media mentions on X (formerly Twitter) Datasets contributed: 7, including those related to immune checkpoint inhibitors, abdominal aortic imaging, and statistical methods She has been actively publishing since 2016, with increasing output over time, demonstrating sustained research productivity. While no formal scientific awards are listed, her contributions to open science via figshare datasets and preprints in medRxiv underscore her commitment to transparency and reproducibility.

• Gene regulation
• Bioinformatics
• RNA Biology
• +6 more

Albin Gustav Sandelin is a Professor in the Department of Biology at the University of Copenhagen, specializing in bioinformatics and RNA biology. With a PhD in Functional Genomics from Karolinska Institute (2004) and an MSc in Molecular Biology from Stockholm University (2000), his career spans roles at institutions including RIKEN Yokohama Institute and Tokyo Medical and Dental University. His research focuses on Gene regulation mechanisms Transcription start site dynamics RNA sequencing methodologies Promoter architecture analysis Cancer microenvironment interactions . Recent publications highlight his work in pancreatic cancer adaptation to acidic environments (2024-2025), TLDR-seq for RNA analysis, and JASPAR database development. He supervises PhD students including Eivind Valen and Eric Man-Hung, with a history of teaching bioinformatics courses at Karolinska Institute and Copenhagen University. Key collaborations involve institutions in Japan, Canada, and Sweden, with ongoing contributions to open-access genomic resources like JASPAR.

Peter DalgaardView profile

Professor

• Biostatistics
• Statistical Computing
• Medical Research
• +3 more

Peter Dalgaard is a Professor at the Center for Statistics, affiliated with the Department of Finance at Copenhagen Business School (CBS). He holds editorial roles, including co-editor of the Scandinavian Journal of Statistics (2015–2018) and membership in the editorial board of the R Journal. His research focuses on statistical computing, biostatistics, medical data analysis, and R programming. Notable contributions include developing the R package 'pwr' for power analysis and co-authoring textbooks on statistical methods in healthcare and R programming. His publications span medical research, statistical methodology, software development, and econometrics. He has collaborated on studies involving chemotherapy side effects, migraine mechanisms, diabetes complications, and financial modeling. His work emphasizes rigorous statistical techniques and open-source tools for reproducible research. Professional activities include serving on academic assessment committees, such as for an associate professor position at Syddansk Universitet (2018–2019). His contributions to the R ecosystem highlight his role in bridging statistical theory with practical applications.