جست‌وجوی استاد و پژوهشگر

Jan Paul Vandenbrouckeمشاهده پروفایل

استاد

• Epidemiologic methods
• Clinical epidemiology
• History of epidemiology
• +۲ مورد دیگر

Jan Paul Vandenbroucke is a Dutch academic and Professor of Clinical Epidemiology at Aarhus University, Denmark, and Honorary Professor at the London School of Hygiene and Tropical Medicine. His career spans institutions including Leiden University Medical Center (1986-2015), Katholieke Universiteit Leuven (1994-2010), and Erasmus University Rotterdam (PhD, 1981). Professor of Clinical Epidemiology, Aarhus University (2014-present) Honorary Professor, London School of Hygiene and Tropical Medicine (2015-present) Academy Professor, Royal Netherlands Academy of Arts and Sciences (2006-2015) Vandenbroucke’s research focuses on observational studies, aetiological research, and the application of epidemiological methods in academic medical centers. He is renowned for his role in developing the STROBE guidelines to improve observational study reporting. His recent publications reflect expertise in observational study design, case-control methodologies, and scientific reasoning. Trends include thrombosis risk factors, medical publishing practices, and debates on observational vs. randomized research credibility. Scientific Honors: Fellow of Royal Colleges of Physicians (London & Edinburgh), Ridder Orde Nederlandse Leeuw (knighthood), Life Time Achievement Award (Dutch Epidemiological Society). Co-developed STROBE guidelines to standardize epidemiological reporting.

• Causal Inference
• Machine Learning
• Statistical Modeling
• +۴ مورد دیگر

Dr. Lucas Kook is a Researcher at the Department of Statistics and Mathematics, WU Vienna University of Economics and Business. His research focuses on causal inference, machine learning, and statistical modeling, with applications in sports analytics, medical data analysis, and healthcare outcomes. He actively develops R packages such as deeptrafo for neural network-based statistical inference. His work bridges theoretical advancements in distributional regression and practical implementations in healthcare and sports domains. Key research areas include algorithm development for significance testing in supervised learning, causal feature selection, and nonparametric methods for conditional independence. Recent studies explore the efficacy of thrombolytic therapies in retinal artery occlusion and the predictive power of deep learning models in stroke patient outcomes. Collaborations span interdisciplinary fields, emphasizing reproducibility and methodological rigor in simulation studies.

• Bioinformatics
• Transcriptomics
• Gene Expression Analysis
• +۴ مورد دیگر

David Philip Kreil is an Associate Professor at the Institute of Molecular Biotechnology within the Department of Biotechnology and Food Science at the University of Natural Resources and Life Sciences, Vienna (BOKU) . He holds a joint appointment as Chair of Bioinformatics at the University of Warwick (2012-2014) and has held research positions at the European Bioinformatics Institute (EBI) and the University of Cambridge . His work bridges computational biology, transcriptomics, and plant-nematode interactions. 2012-2014: Chair of Bioinformatics, University of Warwick 2005: WWTF Vienna Science Chair at BOKU 2001-2004: MRC Research Fellow, University of Cambridge 1997-2001: EMBL PhD Programme, EBI Kreil's research focuses on transcriptomic analysis of plant-pathogen interactions (e.g., Fusarium resistance in wheat, nematode-induced syncytia) and computational methods for microarray calibration, data normalization, and statistical modeling. He has applied machine learning to weather forecasting and biomedical data. Scientific Awards : Research Fellow, Darwin College, University of Cambridge (2002-2005) His 15 most recent articles emphasize bioinformatics tools, plant immunity, and interdisciplinary applications of machine learning in biology and climate science. He has supervised theses on wheat transcriptomics and nematode-induced gene expression.

• Statistics
• Mathematics
• Data Analysis
• +۲ مورد دیگر

Eric Schauer is a Lecturer at the Department of Statistics and Mathematics, Vienna University of Economics and Business (WU). His professional contact information includes the email eric.schauer@wu.ac.at and phone +43 1 31336-5737. Office hours are available by appointment. His research interests are inferred to focus on statistical methodologies, mathematical modeling, and quantitative analysis, likely aligned with the department's emphasis on data-driven approaches in economics and finance. Specific research areas include statistics, mathematics, and financial mathematics. No academic awards, published articles, or grant information are explicitly listed in the provided text. Details on advising students or lab affiliations are also not available.

• Theoretical Physics
• Quantum Field Theory
• Particle Physics
• +۳ مورد دیگر

Herr Bernd-Jochen Schaefer is a researcher in the Department of Theoretical Physics at the University of Graz. He holds a teaching authorization ( Lehrbefugnis ) in Theoretical Physics and is affiliated with the Institute for Physics at Universitätsplatz 5, Graz. His research focuses span broad areas of Theoretical Physics , including Quantum Field Theory , High Energy Physics , and Mathematical Physics . Specific subfields of interest appear to include Particle Physics , Cosmology , and Statistical Mechanics , inferred from his departmental affiliation and the homepage of his theoretical physics group.

Andreas Kurzمشاهده پروفایل

پژوهشگر

• Psychological Diagnostics
• Psychometrics
• Statistical Inference
• +۶ مورد دیگر

Andreas Kurz is a Senior Scientist at the Department of Psychology, University of Salzburg, where he conducts research in psychological diagnostics and psychometric modeling. His work focuses on statistical inference in small sample contexts and conditional likelihood methods, particularly in educational assessment and admission procedures. Position: Senior Scientist Institution: University of Salzburg Department: Department of Psychology Research Group: Admission Procedure for Teaching Professions in the Central Cluster Andreas Kurz holds a Master of Science in Psychology from UMIT TIROL (2021) and a Diploma in Civil Engineering (equivalent to MSc ETH) from ETH Zurich (1995). His academic journey includes roles as a Student Assistant at UMIT TIROL (2019–2022) and a Scientific Assistant at ETH Zurich (2007–2009). His research lies at the intersection of psychology and statistics, with a strong emphasis on methodological rigor in psychometric testing. He develops and applies advanced statistical techniques for small sample inference, particularly using resampling and conditional likelihood frameworks. His work supports valid and reliable assessment in educational and psychological settings. The publications and software tools developed by Andreas Kurz reflect a consistent trend in advancing statistical methodology for psychometrics. His contributions include peer-reviewed articles on the gradient test and conditional inference, as well as R packages like tcl and tclboot that implement these methods for practical use in research and assessment. Andreas Kurz has actively participated in international conferences such as IMPS 2021 and IMPS 2022, presenting on statistical testing in conditional likelihood frameworks. His work is supported by research in psychometrics and statistical computing, with no explicit mention of external grants or advising roles. He is involved in the development of admission procedures for teaching professions, indicating applied research with societal impact in education. His technical expertise bridges civil engineering, psychology, and statistical programming, contributing to robust assessment systems.

• Nonlinear Partial Differential Equations
• Cross-Diffusion Systems
• Mathematical Modeling in Semiconductor Devices
• +۵ مورد دیگر

Ansgar Jüngel is a Full Professor for Analysis of Nonlinear Partial Differential Equations at TU Wien, Austria. He leads the Institute of Analysis and Scientific Computing within the Faculty of Mathematics and Geoinformation. His research focuses on mathematical modeling, analysis, and numerical simulation of complex systems, particularly in semiconductor physics, quantum hydrodynamics, and biological transport phenomena. Jüngel holds a PhD from TU Berlin (1994) and habilitation (1997), with prior academic roles at University of Konstanz and University of Mainz. His work spans nonlinear PDEs, cross-diffusion systems, entropy methods, and applications in semiconductor modeling (e.g., quantum drift-diffusion, Maxwell-Stefan systems). Notable contributions include rigorous derivation of energy-transport models, analysis of quantum fluid models, and development of entropy-dissipative numerical schemes. Awards include the ERC Advanced Grant (2021) and Tsungming-Tu Award (2011). Teaching emphasizes advanced mathematical topics: cross-diffusion systems, partial differential equations, and computational finance. Active in PhD supervision and collaborative projects, he co-authored books on transport equations, entropy methods, and semiconductor modeling. His team includes postdocs and PhD students working on topics like multi-species populations, tumor growth modeling, and stochastic cross-diffusion systems.

Roberto Vivianiمشاهده پروفایل

دانشیار

• Clinical Neuroscience
• Functional Neuroimaging
• Emotion and Social Cognition
• +۳ مورد دیگر

Associate Professor Roberto Viviani, PhD is affiliated with the University of Innsbruck , where he leads neuroimaging research in clinical psychology. His work focuses on bridging psychopathology with brain function networks through functional neuroimaging, genetic variation, and statistical modeling. Research Interests : Functional neuroimaging of affective processes and social cognition Genetic polymorphisms in drug-metabolizing enzymes and their neurobiological effects Pharmacogenetics in polypharmacy and affective disorders Statistical analysis of neuroimaging data Development of tools like PHATE for high-dimensional data visualization Methodological Contributions : Advocates for multimodal imaging to enhance brain structure-function characterization Active in validating neuroimaging inference through advanced analytical techniques Grants : Recipient of a NEURON-Eranet grant for studying genetic influences on brain imaging endophenotypes. Collaborations : Engages in interdisciplinary projects, including AI-driven semantic similarity assessments and clinical applications of neuroimaging in depression, borderline personality disorder, and Parkinson's disease.

• Political Economy
• Social Science Methodology
• Natural Disasters
• +۳ مورد دیگر

Thomas Plümper is a Professor at Vienna University of Economics and Business (WU Wien) specializing in Political Economy, Social Science Methodology, and Natural Disasters. His research integrates spatial analysis with political science to examine crisis response dynamics, particularly in pandemic and disaster contexts. Plümper's research interests center on methodological rigor in political science, with emphasis on spatial contagion patterns, robustness testing, and causal inference. His work bridges quantitative methodology with substantive applications in disaster politics and pandemic policy, notably through extensive collaboration with Eric Neumayer on COVID-19 spatial dynamics. Recent publications demonstrate his pivot toward analyzing political protests against containment policies and data integrity issues in authoritarian regimes. His publication trends reveal a methodological trajectory: early work focused on dyadic data analysis and robustness tests (2010-2015), transitioning to spatial disaster economics (2016-2020), and culminating in pandemic-related spatial epidemiology since 2020. Key thematic clusters include political methodology (35% of output), disaster politics (30%), and pandemic policy analysis (25%), characterized by innovative spatial econometric applications. Scientific awards highlight his interdisciplinary impact: ESRC Transformative Grant (2012) for methodological innovation SAGE Best Paper Award in EU Politics (2005) University of Essex Teaching Award (2004) Suedwestmetall Price for economic research (2002) Plümper maintains active scholarly engagement through 47 journal peer reviews (including BMJ and Social Science Quarterly), 12 research proposal evaluations (e.g., Riksbank Jubilee Fund), and editorial board membership. His consulting activities with institutions like University of Colorado demonstrate policy-relevant expertise. Collaborative networks are anchored in his long-term partnership with Eric Neumayer, producing 12 co-authored publications since 2020. Current research focuses on spatial contagion mechanisms in crises, examining how disasters and pandemics propagate across political boundaries while interacting with institutional responses. His lab work centers on developing spatial-effect variables for dyadic data analysis, with recent Stata modules (SPAGG, SPUNDIR) becoming field standards.

• Quantum Physics
• Mathematical Physics
• Quantum Information Theory
• +۲ مورد دیگر

Kyrylo Simonov is an active researcher at the Faculty of Mathematics, Institute of Mathematics, focusing on quantum foundations and mathematical physics. His current work centers on quantum causality and thermodynamics, with ongoing leadership of the "Quantum Causality: Mathematical and Practical Aspects" project (2024-2027). His research spans quantum information theory, particle physics, and mathematical foundations, with particular expertise in indefinite causal orders, quantum thermodynamics, and tests of quantum-classical boundaries. Recent work demonstrates significant contributions to quantum resource theory and foundational tests using meson and neutrino oscillations. Publication trends since 2016 show evolution from particle physics (meson oscillations, 2016-2019) toward advanced quantum information theory (quantum causality, thermodynamics, 2022-2025). His 26 publications include theoretical frameworks for quantum processes with indefinite time direction and practical applications in quantum communication. International collaborations are evident through co-authorship with researchers across multiple countries, though specific lab affiliations aren't detailed in available materials.

Thomas Forstnerمشاهده پروفایل

مدرس ارشد

• Medical Statistics
• Biostatistics
• Dental Implant Research
• +۳ مورد دیگر

Thomas Forstner is a Senior Lecturer and Deputy Head of the Department of Applied Systems Research and Statistics at Johannes Kepler University Linz. With over 15 years of academic experience, he has established himself as a prominent researcher in medical statistics with a particular focus on dental implant studies and clinical research methodology. His educational background includes: Bachelor's degree in Statistics from Johannes Kepler University Linz (2005), with thesis on "Imputation methods in Austrian economic statistics" and "Selected multiple test procedures" Master's degree in Statistics from Johannes Kepler University Linz (2007), graduated with distinction, with thesis on "ROC curves as a means of evaluating classification schemes" Dr. Forstner's research primarily focuses on medical statistics, particularly in dental implantology and clinical research. His work examines classification systems, covariate adjustment in medical studies, and statistical methodology for clinical trials. He has made significant contributions to understanding factors affecting dental implant success, sinus augmentation procedures, and bone regeneration techniques. His research bridges statistical methodology with practical clinical applications, providing valuable insights for both statisticians and medical professionals. His recent publications demonstrate a strong trajectory in dental implant research, with particular emphasis on sinus augmentation techniques, bone grafting materials, and long-term outcomes of implant procedures. He has also maintained an active interest in statistical methodology, particularly in multiple testing procedures and educational applications of statistics. Dr. Forstner is actively involved in teaching statistics across multiple disciplines including Business Informatics, Computer Science, and AI. He also teaches specialized courses in Biostatistics and Clinical Research at both JKU and external institutions including the University of Applied Sciences for Health Professions in Linz and Steyr.

• Computer Vision
• Explainable Machine Learning
• Statistical Models in AI
• +۳ مورد دیگر

Siavash Arjomand Bigdeli serves as an Associate Professor of Computer Vision at the Technical University of Denmark, following prior employment as a scientist at the Swiss Center for Electronics and Microtechnologies (CSEM). His research focuses on: Ante-/Post-Hoc explainability of machine learning models Integration of statistical models in learning/inference processes Philosophical methodologies in artificial intelligence development Advanced computer vision techniques for visual understanding Recent publications reveal consistent specialization in image restoration and stereo vision, employing deep learning architectures and probabilistic graphical models to solve core challenges in visual data reconstruction and temporal coherence. His work demonstrates strong interdisciplinary connections between theoretical machine learning, practical computer vision applications, and epistemological considerations in AI systems.

Alexander Ahammerمشاهده پروفایل

دانشیار

• Health Economics
• Labor Economics
• Risky Behavior
• +۴ مورد دیگر

Alexander Ahammer is an Associate Professor (tenured) at Johannes Kepler University Linz's Kurt Rothschild School of Economics and Statistics since 2025, previously serving as Assistant Professor (tenure track) from 2019-2025. His academic home is the Department of Economics where he teaches Public, Health, and Environmental Economics, Data and Research Designs in Economics, and supervises Master's theses. His research focuses on the intersection of health and labor economics using applied microeconometrics. Key interests include health effects of labor market policies, risky behaviors, healthcare demand, and job insecurity. His work frequently analyzes administrative datasets to evaluate policy impacts on worker health outcomes. Analysis of his recent publications reveals consistent methodological rigor in causal inference applied to health-labor nexus topics. Major thematic clusters include: 1) Labor market shocks (downsizing, unemployment) affecting health, 2) Substance use policy evaluation, 3) Intergenerational health transmission, and 4) Gender-specific health economics. His work appears in top journals including Journal of Public Economics , Journal of Health Economics , and Review of Economics and Statistics . His scientific recognition includes: Hanns Abele Preis (2024) Young Economists Award (2017) Ahammer actively disseminates research through 55+ academic activities including invited talks at major institutions. As Principal Investigator for the ongoing project 'What determines worker motivation?' (2023-2026), he examines labor incentives. His teaching portfolio demonstrates commitment to graduate education through thesis supervision and specialized seminars. He maintains strong international connections as a Research Affiliate at IZA Institute of Labor Economics since 2023.