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Michael SørensenView profile

Professor

• Statistical Inference for Stochastic Processes
• Stochastic Differential Equations
• Financial Mathematics
• +3 more

Michael Sørensen is a Professor at the Department of Mathematical Sciences, University of Copenhagen. His primary research focuses on statistical inference for stochastic processes, particularly stochastic differential equations and jump processes, with applications in finance, physics (e.g., wind-blown sand dynamics), and biology. He has authored/co-authored influential books such as Exponential Families of Stochastic Processes and edited volumes on empirical process techniques and statistical methods for stochastic differential equations. His work bridges theoretical statistics with applied problems in natural sciences and finance. Research interests include modeling turbulence, sand transport dynamics, and protein structure evolution. Collaborations with earth scientists like Keld Rømer Rasmussen have advanced understanding of aeolian processes. His methodologies emphasize likelihood-based inference and estimating functions, with contributions to high-frequency data analysis and diffusion bridge simulations. A comprehensive CV and full publication list are available on his profile. Key contributions span stochastic modeling in physics (e.g., sand dune dynamics), financial econometrics, and computational statistics. He has pioneered techniques for analyzing multi-modal diffusions and developed frameworks for mixed-effects stochastic differential equations. His work is widely cited in both theoretical and applied statistical literature.

Johan BraekenView profile

Professor

• Psychometrics
• Item Response Theory (IRT)
• Computerized Adaptive Testing (CAT)
• +3 more

Johan Braeken is a Professor at the University of Oslo's Centre for Educational Measurement (CEMO). He holds expertise in psychometric modeling, particularly in modern test design, including computerized adaptive testing (CAT) and item response theory (IRT). His research focuses on improving assessment methodologies in education and large-scale evaluations. Education: PhD in Psychology (Psychometrics) from K.U.Leuven, Belgium (2008). Previous roles include Associate Professor (2014–2017) and Assistant Professor positions at Wageningen University and Tilburg University in the Netherlands. He has also worked as a psychometrician at CITO (2008–2009). Research Interests: Development and application of latent variable models, CAT optimization, and evaluation of international educational assessments. He explores statistical methods for improving measurement precision and addressing model violations. Software Contributions: Creator of the 'Empirical Kaiser Criterion' app for factor analysis, 'Fixed-precision MCAT selection rules' for R's mirtCAT package, and an Item Characteristic Curve visualization tool. Labs/Groups: Active in the CREATE and FREMO research groups, focusing on educational measurement and frontier research in psychometrics.

Pauliina IlmonenView profile

Associate Professor

• Mathematical Statistics
• Probability Theory
• Data Science
• +3 more

Pauliina Ilmonen is an Associate Professor and Vice Dean in the Department of Mathematics and Systems Analysis at Aalto University, within the School of Science. Her research focuses on mathematical statistics, probability theory, and data science, with applications in healthcare and engineering. She holds academic positions in both the Department of Mathematics and Systems Analysis and Statistics and Mathematical Data Science. Her work spans statistical methodology, stochastic processes, and interdisciplinary collaborations in biomedicine. Notable research areas include extreme value analysis, functional data analysis, and the modeling of dependent data. She has contributed to studies on HIV transmission dynamics, prostate cancer genomics, and the statistical analysis of infectious diseases. Dr. Ilmonen’s recent publications (2020–2025) emphasize methodological advancements in statistical inference, computational statistics, and applications in healthcare. She leads projects on predictive modeling, cost-effectiveness analysis in cancer screening, and network traffic prediction. Her findings bridge theoretical statistics with practical challenges in medicine and technology. She advises 8 theses and collaborates on grants exploring mathematical data science, biostatistics, and stochastic systems. Active in academic service, she contributes to curriculum development and promotes ethical use of statistics in research.

Magda Cepeda-ZorrillaView profile

Research Fellow

• Sustainable Transport
• Travel Behavior
• Modal Choice
• +6 more

Dr. Magda Cepeda-Zorrilla is a Research Fellow in the Department of Strategy and International Business at the University of Birmingham's Birmingham Business School, where she is affiliated with City-REDI. She joined the institution in February 2019. Education: PhD in Transport, University of Leeds, 2017 MSc in Transport (Sustainability), University of Leeds, 2013 BSc (Hons) in International Relations, National Autonomous University of Mexico, 2011 Her primary research focuses on the factors influencing individuals' travel choices, with a strong emphasis on strategies to promote sustainable travel. Her expertise includes the psychosocial aspects of modal choice, the application of social marketing techniques for tailoring transport interventions, and the analysis of transport infrastructure's impact on economic growth and productivity. She has extensive experience with both qualitative and quantitative research methods, including surveys, interviews, focus groups, and multivariate statistical analysis. Her recent publications show a consistent trend in understanding human behavior within the transport sector, particularly focusing on psychological and social determinants of sustainable travel adoption, such as cycling. Her work bridges the gap between transport planning, behavioral psychology, and policy development. Scientific Awards: No awards listed in the provided text. Dr. Cepeda-Zorrilla has contributed to research projects as a Research Assistant at the University of Leeds, including work on positive incentives for behavior change, and as a Graduate Consultant for a transport consultancy, where she analyzed traffic impacts for major projects like HS2. She has not supervised any students mentioned in the text. She is a key researcher within the City-REDI team at the Birmingham Business School, contributing to research on regional economic development and transport.

Mousumi BanerjeeView profile

Research Professor

• Biostatistics
• Cancer Research
• Health Services Research
• +4 more

Mousumi Banerjee is the Anant M. Kshirsagar Collegiate Research Professor in the Department of Biostatistics at the University of Michigan School of Public Health. She also holds the position of Research Professor in Global Public Health and serves as Director of Biostatistics for the Pediatric Cardiac Critical Care Consortium (PC4) Analytic Center and Director of Global StatCore. Her affiliations include the Rogel Cancer Center, Institute for Healthcare Policy and Innovation, Center for Global Health Equity, and Michigan Institute for Data Science (MIDAS). Bachelor's & Master's in Statistics from Indian Statistical Institute, Kolkata PhD in Statistics from University of Wisconsin-Madison (1994) Dr. Banerjee develops advanced statistical methodologies for biomedical applications, particularly in cancer and pediatric heart disease. Her research includes predictive modeling, machine learning, causal inference, survival analysis, and correlated data techniques. She focuses on health disparities and equitable care delivery, collaborating across disciplines including neurology, surgery, and social determinants of health. Recent publications demonstrate her expertise in statistical algorithm development for clinical quality assessment, disease classification, and healthcare outcomes. Her work spans applications in bladder cancer detection, thyroid cancer follow-up imaging, HPV-related oropharyngeal carcinoma analysis, and cardiac arrest prevention in pediatric critical care settings. Scientific Awards Fellow of the American Statistical Association Elected member of the International Statistical Institute As Director of Global StatCore, Banerjee enhances biostatistical support for global public health initiatives. She leads major methodological projects for the Pediatric Cardiac Critical Care Consortium (PC4) and works with national datasets like SEER, NCDB, and Medicare claims to analyze healthcare disparities and quality improvement metrics.

• Psychometrics
• Educational Measurement
• Statistical Modeling
• +3 more

Prof. Dr. Steffi Pohl is a Professor of Methods and Evaluation/Quality Assurance at the Department of Methods and Evaluation/Quality Assurance, Faculty of Education and Psychology, Freie Universität Berlin. She holds editorial roles in prominent journals like Psychometrika and Journal of Educational and Behavioral Statistics . Her research focuses on psychometrics, log data analysis, missing data mechanisms, and causal inference in educational assessments. Steffi Pohl's academic journey includes a Diplom in Psychology from Freie Universität Berlin (1998–2004) and a Ph.D. in Psychometrics (2005–2010) from Friedrich-Schiller-Universität Jena. She has held various research positions, including at the National Educational Panel Study (NEPS) and the University of Hertfordshire, UK. Her work emphasizes methodological advancements in testing, missing data, and measurement invariance across populations. Her research interests span psychometric modeling, log data analysis, and addressing challenges in large-scale educational assessments. Key contributions include innovations in response time analysis, disentangling engaged/disengaged test behaviors, and improving cross-cultural comparisons in educational rankings. She has been recognized with the 2020 Early Career Award from the Psychometric Society and the 2011 Gustav A. Lienert Dissertation Prize. In addition to research, Pohl teaches courses on empirical social research methods and multivariate analysis techniques. She actively contributes to university governance as a member of the Academic Senate at Freie Universität Berlin and serves as a trusted advisor for the German National Academic Foundation.

Shuchismita SarkarView profile

Assistant Professor

• Model-Based Clustering
• Finite Mixture Modeling
• Hidden Markov Models
• +4 more

Shuchismita Sarkar is an Assistant Professor in the Department of Applied Statistics and Operations Research at Bowling Green State University (BGSU), housed within the Allen W. and Carol M. Schmidthorst College of Business. Her research primarily focuses on model-based clustering methodologies, including finite mixture models, hidden Markov models, and change point estimation. Prior to academia, she worked in credit risk analytics. Education: Ph.D. in Applied Statistics, University of Alabama, 2019 M.Sc. in Applied Statistics, Western Michigan University, 2008 M.Sc. in Applied Statistics and Informatics, Indian Institute of Technology Bombay, 2002 B.Sc. in Statistics, University of Calcutta, 2000 Research Interests: Her work spans computational statistics, cluster analysis, finite mixture modeling, hidden Markov models, and change point estimation. These techniques are applied to diverse fields such as network analysis, epidemiology, and financial risk assessment. She has developed the R package netClust for network data clustering. Teaching: She teaches graduate and undergraduate courses in Data Mining and Regression Analysis, employing both face-to-face and online modalities. Her teaching excellence was recognized by the Jeff Kurkjian Teaching Award (2018). Awards & Grants: 2020: Classification Society Distinguished Dissertation Award (Honourable Mention) 2018: Summer in Excellence Research Grant ($5,000) 2018: Jeff Kurkjian Teaching Award Software Contributions: Authored the netClust R package for model-based clustering of network data.

• Statistics
• Spatial Statistics
• Spatio-Temporal Modeling
• +7 more

Donato Posa is a Full Professor in Statistics at the Department of Economic Sciences, University of Salento. He holds the academic position of Professor Ordinario (Full Professor) in the field of Statistics (SECS-S/01) and is actively engaged in research and academic leadership. His work bridges economics, environmental science, and advanced statistical modeling. University: University of Salento Department: Department of Economic Sciences Academic Rank: Professor Email: donato.posa@unisalento.it Office: Centro Ecotekne Pal. C, S.P. 6, Lecce - Monteroni, LECCE (LE) Phone: +39 0832 29 8737 Donato Posa earned his degree in Physics, cum laude, from the University of Bari with a thesis conducted at CERN, Geneva, and completed a specialization in Physics. His international academic experience includes extended research stays at Stanford University (USA), the University of Arizona, and the University of North Carolina. His research focuses on spatial and spatio-temporal statistics, with major contributions in geostatistics, multivariate geostatistics, stochastic simulation, and time series analysis. He has developed theoretical and applied models for environmental monitoring, pollution assessment, and socioeconomic data analysis. His work has been applied in risk mapping, environmental policy, and urban planning. The 15 most recent articles reflect a consistent trend in spatio-temporal modeling and geostatistical innovation. They span theoretical developments in covariance modeling and variogram analysis to practical applications in environmental monitoring, pollution dispersion, and ecosystem well-being. The research demonstrates a strong interdisciplinary focus, integrating statistical theory with environmental, economic, and computational sciences. His scientific recognition includes multiple CNR and NATO research grants, CERN awards, and an International Diploma of Honour from the American Biographical Institute for contributions to geostatistics. He has served on editorial boards, chaired international conferences (e.g., GeoEnv 2012), and participated in national scientific qualification committees. Posa has supervised numerous research projects funded by CNR, MIUR, Fondazione Caripuglia, and EU programs. He has acted as a scientific referee for leading journals such as Stochastic Environmental Research and Risk Assessment and Computational Statistics and Data Analysis . He has also led educational initiatives in statistical methods and GIS for environmental and cultural heritage applications. He has been actively involved in academic governance, serving as President of the Research Observatory at the University of Salento (2013–2017) and as a member of national evaluation committees. He has chaired international conferences and contributed to major scientific associations including the Bernoulli Society, the International Association for Statistical Computing, and the American Statistical Association.

Paulo M. M. RodriguesView profile

Professor

• Time-series econometrics
• Financial econometrics
• Empirical macroeconomics
• +7 more

Paulo M. M. Rodrigues is a Full Professor at the Nova School of Business and Economics, Universidade Nova de Lisboa , and a senior research economist at the Department of Economic Studies, Bank of Portugal , where he has been employed since 2008. He previously served as Associate Professor and held leadership roles including vice-dean and dean at the Faculty of Economics, University of Algarve. Education Agregação, University of Algarve (2015) PhD in Econometrics, University of Manchester (1998) Masters in Economics and Econometrics, University of Manchester (1995) Degree in Business Management, University of Algarve (1993) His primary research interests lie in time-series econometrics, financial econometrics, and empirical macroeconomics and finance . His work emphasizes methodological innovation in nonstationary and seasonal time series, long memory processes, predictive regression, and quantile-based modeling. He has made significant contributions to the development and application of unit root tests, cointegration analysis, and forecasting techniques under structural breaks and heteroskedasticity. The recent trends in his publications show a strong focus on advanced econometric methods, including IVX and residual-augmented approaches for predictive regression, fractional integration in multivariate settings, tail risk modeling in financial markets, and applications in tourism and labor economics. His work frequently appears in top journals such as the Journal of Econometrics , Econometric Theory , and Review of Economics and Statistics . Editorial and Professional Service Serves on the editorial board of several scientific journals. Advising and Grants While specific details on PhD students or grant funding are not provided in the text, his extensive collaborative research—particularly with scholars like Matei Demetrescu, João Nicolau, and A.M. Robert Taylor—indicates a strong record of academic mentorship and collaborative research leadership. His position at the Bank of Portugal also suggests involvement in policy-relevant research projects and potential funding from central bank or national research agencies. Laboratories and Research Teams He is affiliated with the Economics and Research Department at the Bank of Portugal, a leading institution for economic research in Portugal. This affiliation provides a collaborative environment for empirical macroeconomic and financial research with policy implications.

• Geophysical Engineering
• Applied Geophysics
• Electro Magnetic and Electrical Methods
• +11 more

Özgür Aktürk is an Assistant Professor in the Department of Geological Engineering at Akdeniz University, Faculty of Engineering, where he has been serving since 2011. His academic journey began at Ankara University, continued with a master's and doctorate at Middle East Technical University, and includes research experience at the University of Tennessee. He is actively involved in teaching and research in geotechnical and geophysical engineering, with strong industry collaboration through his R&D company. Doctorate: Middle East Technical University, 2010 Undergraduate: Ankara University, 2001 His research interests span Applied Geophysics , Engineering Geology , Electrical Resistivity Imaging , Soil and Rock Mechanics , Seismic Hazard Assessment , and Numerical Modeling . He applies these to practical problems such as tunnel stability, dam safety, karst investigations, and urban infrastructure. His work integrates field geophysics with computational models to assess geotechnical risks. The recent articles reflect a consistent focus on geophysical subsurface characterization, particularly using electrical resistivity methods, and geotechnical stability analysis. Key themes include urban geophysics for subway systems , karst cavity detection , soil liquefaction , and statistical analysis of geological materials . His collaborations with researchers like V. Doyuran, K. Kayabalı, and F. Uçar highlight interdisciplinary and applied research trends. He has supervised multiple master's students on topics related to tunnel deformation, landslide hazards, and geophysical site assessment. Although no formal scientific awards are listed, his extensive publication record and participation in funded projects indicate active research engagement. He is a member of the Engineering Geology Association and the Chamber of Geological Engineers, and has served on thesis juries. Özgür Aktürk has founded JeoTasarım Proje ve Mühendislik under Akdeniz University TEKNOKENT, demonstrating a commitment to applied research and technology transfer. His work bridges academic research and practical engineering solutions, particularly in water resources and geohazard mitigation projects.

• Compositional Data Analysis
• Multivariate Statistical Analysis
• Data Fusion Methods
• +5 more

Daunis i Estadella, Pepus is an Associate Professor in the Department of Computer Science, Applied Mathematics and Statistics at the University of Girona, where he is also the Vice-Rector for Quality and Transparency since December 2017. He is a core member of the recognized research group GR-EADC (Research Group in Statistics and Compositional Data Analysis), supported by the Catalan government. His research interests include: Compositional Data Analysis Data Fusion Methods Multivariate Statistical Analysis Applications in Medical Imaging, Radiology, and Public Health Statistical Methodology in Geology and Archaeology The recent articles reflect a strong trend in applying advanced statistical techniques—particularly compositional data analysis and data fusion—to interdisciplinary domains such as healthcare, consumer behavior, geosciences, and archaeology. His work emphasizes methodological innovation and real-world application, especially in integrating heterogeneous data sources and improving multivariate analysis in medical and social contexts. Scientific contributions and recognitions include: Active publication in high-impact journals like Computational Statistics & Data Analysis and American Journal of Neuroradiology ORCID: 0000-0001-6134-9255 Researcher ID: B-9082-2011 Scopus Author ID: 14041287900 He has supervised various research projects and played key administrative roles, including former Coordinator of University Access Exams (PAU) and departmental secretary. He has contributed significantly to academic governance and statistical education. His work bridges theoretical statistics with practical applications across health, engineering, and social sciences. He is affiliated with the Grup de Recerca en Estadística i Anàlisi de Dades Composicionals (GR-EADC), a consolidated research team focused on advancing statistical methods for compositional and multivariate data.

• Macroeconomics
• Economic Surveys
• Time Series Economics
• +7 more

Dr. Klaus Wohlrabe is a Scientific Assistant and Deputy Director of the ifo Center for Macroeconomics and Surveys at the ifo Institute for Economic Research, where he also serves as Head of Surveys. His work focuses on the methodology and evaluation of the ifo business surveys, economic analysis, bibliometrics, efficiency measurement, and time series economics. He has been actively involved with the ifo Institute since 2000, initially as a tutor in macroeconomics and economics before transitioning into his current research and leadership roles. His research interests span a wide range of topics in applied economics, with a strong emphasis on survey methodology, business cycle analysis, and economic forecasting. He has made significant contributions to understanding the mechanics of the ifo Business Climate Index, the representativeness of business surveys, and the impact of external shocks such as the Covid-19 pandemic and the war in Ukraine on firm behavior. His work in bibliometrics includes studies on journal rankings, citation patterns, co-authorship norms, and the efficiency of academic institutions. His recent publications, from 2020 to 2025, demonstrate a consistent and prolific output. The articles reveal a strong trend towards empirical analysis of survey data, particularly from the ifo Institute, to understand current economic conditions in Germany and globally. Key themes include business sentiment, labor markets, AI adoption, material shortages, and the economic implications of major events. His work often involves sophisticated statistical and econometric methods, including archetypoid analysis and efficiency measurement. Dr. Wohlrabe has collaborated with numerous researchers, including Lutz Bornmann, Robert Lehmann, and Stefan Sauer, on a wide array of projects. He has contributed to major policy reports, such as those on the economic costs of the Coronavirus shutdown and the competitiveness of German industry. He is a key figure in the development and dissemination of the ifo Institute's survey tools and findings, having co-edited the 'Handbook of ifo Surveys' and authored numerous sections on the ifo Business Climate Index, the ifo Employment Barometer, and other survey instruments. His work is instrumental in providing timely and reliable economic insights to policymakers, businesses, and the academic community.

Frédéric GuillaumeView profile

Professor

• Evolutionary Biology
• Population Genetics
• Quantitative Genetics
• +4 more

Frédéric Guillaume is a Professor in the Organismal and Evolutionary Biology Research Programme at the University of Helsinki 's Faculty of Biological and Environmental Sciences. His work integrates computational and empirical approaches to study evolutionary processes under environmental change. Education: PhD in Evolutionary Biology (2005) and BSc in Biological Sciences (2001) from Université de Lausanne His research focuses on: Genetic architecture of complex traits Eco-evolutionary responses to climate change Genotype-phenotype mapping and adaptive constraints Forward-time simulation modeling using Nemo software Experimental evolution with Tribolium castaneum Recent publications (2021-2024) span: Quantitative trait analysis through identity-by-descent methods Gene expression evolution under novel environmental pressures Trade-offs between environmental robustness and evolvability Climate change impacts on alpine plant genetics Pleiotropy versus linkage in genetic correlation detection Active in academic service through: Supervision of Master's theses International research visits (ICTS 2024, UCSB 2022) Collaborative projects like WildAP (2023-2025) and MSCA SalmonScales (2023) He maintains the open science Nemo software ecosystem and contributes to initiatives like Peer Community Journal . His work combines theoretical modeling with experimental validation to predict species persistence under global change scenarios.

Abhisekh Ghosh MoulickView profile

Assistant Professor

• Entrepreneurship
• Strategy
• Entrepreneurial Strategy
• +3 more

Abhisekh Ghosh Moulick is an active Assistant Professor in the Lawrence N. Field Department of Entrepreneurship and Innovation at the Zicklin School of Business, City University of New York (CUNY), with contact email Abhisekh.GhoshMoulick@baruch.cuny.edu and phone (646) 312-3635. His academic qualifications are: PhD from Texas A&M University BSc from University of London Research expertise centers on entrepreneurship and strategic management, with specialized focus on: Entrepreneurial Strategy Social Innovation and Entrepreneurship Nonmarket Strategy Strategic Human Capital United Way systems analysis Cross-cultural entrepreneurial experiences His work addresses institutional gaps in emerging economies and compensation dynamics in mission-driven organizations. Publication trends (2014-2023) reveal concentrated scholarship in causal complexity within entrepreneurship research, fiscal management in public schools, and United Way grant allocation systems. Key patterns include quantitative analysis of entrepreneurial phenomena, strategic compensation in nonprofits, and the impact of weak institutions on entrepreneurial catalysis. No scientific awards or honors were documented in the provided text. Student advising and grant activities are unreported; the text contains no references to doctoral students, master's candidates, or funded research projects. Institutional affiliations and research teams remain unspecified beyond his departmental appointment.

Hammou ElbarmiView profile

Professor

• Order Restricted Inference
• Survival Analysis
• Categorical Data Analysis
• +3 more

Hammou Elbarmi is a Professor at the Paul H. Chook Department of Information Systems and Statistics within the Zicklin School of Business at Baruch College, CUNY. His academic journey includes a PhD in Statistics from the University of Iowa (1993), an MS in Statistics (1989), a DEA in Applied Mathematics from University Mohamed V, Morocco, and a BS in Applied Mathematics from the same institution. PhD, Statistics, University of Iowa (1993) MS, Statistics, University of Iowa (1989) DEA, Applied Mathematics, University Mohamed V, Morocco BS, Applied Mathematics, University Mohamed V, Morocco Elbarmi specializes in Order Restricted Inference , Survival Analysis , and Categorical Data Analysis . His research focuses on statistical methods for comparing survival and cumulative incidence functions under stochastic ordering constraints, with applications to competing risks and biased sampling. He has developed novel nonparametric estimation techniques for distributions with type I/II bias and pioneered empirical likelihood approaches for hypothesis testing under inequality constraints. His work spans over two decades of funded research projects from PSC-CUNY , including grants for "Nonparametric estimation under stochastic precedence" (2020-2022) and "Consistent estimation of survival functions under uniform stochastic ordering" (2023-2024). He has delivered over 30 presentations at institutions like Rice University, University of Iowa, and Joint Statistical Meetings. Elbarmi has received the Faculty Scholarship and Creative Achievement Award at Baruch College annually from 2003-2011 and served as a Co-Chair for the Seminar Series in Statistics & Operations Research. His editorial and peer-review roles include associate editorships for journals like Statistica Sinica and Journal of Nonparametric Statistics .