Copula Models Professors and Supervisors | ApplySharif

جست‌وجوی استاد و پژوهشگر

استاد راهنما، استاد دانشگاه یا پژوهشگر مناسب برای مسیر پژوهشی‌تان را پیدا کنید و با او ارتباط بگیرید.

نمایش ۱۶-۳۰ از ۷۳۷ استاد راهنما

اطلاعات این پروفایل‌ها از صفحات عمومی دانشگاه‌ها جمع‌آوری شده و ممکن است به‌روز نباشد.

Sandra Paterliniمشاهده پروفایل

استاد

University of TrentoItaly

Sandra Paterlini is a Full Professor in the Department of Economics and Management at the University of Trento, Italy. She holds academic roles including Co-Chair of the ERCIM Working Group on Optimization Heuristics and Vice-Chair of the IEEE Task Force on Portfolio Optimization. Her career includes visiting positions at institutions such as the University of Minnesota and Ludwig-Maximilians-Universität München. She earned a PhD in Computational Methods for Financial and Economic Decisions from the University of Bergamo, an MSc in Financial Mathematics from the University of Warwick, and a Laurea in Economics from the University of Modena and Reggio E. Her research focuses on quantitative finance, risk management, portfolio optimization, and network analysis, with applications to ESG, systemic risk, and financial stability. Key research contributions include methodologies for sparse graphical modeling, systemic risk analysis, and ESG scoring frameworks. She has received multiple awards for research excellence and serves on editorial boards of journals like Computational Statistics & Data Analysis and Frontiers in Applied Mathematics and Statistics . Her work bridges academia and policy, with contributions to the European Central Bank’s Financial Stability Directorate and involvement in global conferences on computational finance and econometrics.

پروفایل رسمی دانشگاه

Radu Craiuمشاهده پروفایل

استاد

University of TorontoCanada

Radu Craiu is a Professor in the Department of Statistical Sciences at the University of Toronto. Born in Bucharest, Romania, he earned his PhD in Statistics from the University of Chicago in 2001 under the supervision of Xiao-Li Meng. He joined the University of Toronto as an Assistant Professor, was promoted to Associate Professor in 2006, and to Full Professor in 2013. He served as Department Chair from 2018–2022 and 2023–2024. Education: PhD in Statistics (2001), University of Chicago MS in Mathematics (1996), University of Bucharest BS in Mathematics (1995), University of Bucharest His research focuses on computational methods in statistics, particularly Markov chain Monte Carlo (MCMC) algorithms, Bayesian inference, copula models, model selection, and statistical genetics. He has collaborated on interdisciplinary projects in genetics, ecology, astronomy, and demography, emphasizing flexible statistical modeling and efficient computational techniques. Radu Craiu has received prestigious awards, including the CRM-SSC Prize (2016), CJS Best Paper Award (2019), and fellowships from the American Statistical Association (2022), Institute of Mathematical Statistics (2020), and International Statistical Institute (2015). He actively contributes to editorial roles for journals like the IMS Bulletin and Harvard Data Science Review .

پروفایل رسمی دانشگاه

Valentyn Panchenkoمشاهده پروفایل

استاد

University of New South WalesAustralia

Professor Valentyn Panchenko is a leading academic in Economics at the UNSW Business School, specializing in advanced econometric methodologies and financial modeling. Holding a PhD from the University of Amsterdam and an MPhil from the Tinbergen Institute, his research bridges theoretical econometrics with real-world financial applications, emphasizing big data analysis, network structures, and dependence modeling in economic systems. His expertise spans financial econometrics, time series analysis, non-parametric statistics, and agent-based economic simulations. He focuses on Granger causality, model evaluation, structural economic modeling, and bounded rationality with heterogeneous agents. His work has secured significant grants including ARC Discovery Projects and DECRA fellowships, enabling cutting-edge research on market dynamics and economic interactions. Professor Panchenko's publications appear in top-tier journals like the Journal of Econometric Theory, AEJ: Micro, Journal of Economic Dynamics & Control, and Journal of Banking & Finance. His methodological contributions include novel approaches to copula-based forecasting, nonlinear causality testing, and evolutionary learning models in strategic economic environments. While specific student advising details aren't provided, his research leadership demonstrates sustained impact across econometric theory, financial markets, and experimental economics.

پروفایل رسمی دانشگاه

Sakari Kuikkaمشاهده پروفایل

استاد

University of HelsinkiFinland

Sakari Kuikka is a Professor at the University of Helsinki, affiliated with the Faculty of Biological and Environmental Sciences and the Ecosystems and Environment Research Programme. He is a core member of the Helsinki Institute of Sustainability Science (HELSUS) and leads the Fisheries and Environmental Management Group. His contact details include the email sakari.kuikka@helsinki.fi and the address P.O. Box 65 (Viikinkaari 1), 00014 University of Helsinki, Finland. His research focuses on environmental sciences , particularly fisheries management , marine policy , and Bayesian risk assessment . He has pioneered the use of Bayesian networks in environmental decision-making, including oil spill risk management and seabed mining impact assessments. His work bridges ecological modeling and policy analysis , with applications to high-latitude ecosystems and sustainability governance. Recent publications highlight his expertise in toxicology data standardization for oil spill impacts on fish, economic integration in fisheries science , and Arctic shipping safety . He actively supervises doctoral students in Wildlife Biology and Interdisciplinary Environmental Sciences. Current projects (2023–2027) include WATERWAYS (marine sustainability) and GYROSCOPE (digital marine logistics).

پروفایل رسمی دانشگاه

Mohamad Khaledمشاهده پروفایل

مدرس ارشد

University of QueenslandAustralia

Dr. Mohamad Khaled is a Senior Lecturer in the School of Economics at The University of Queensland (UQ), affiliated with the Centre for Efficiency and Productivity Analysis within the Faculty of Business, Economics and Law. His research focuses on Applied Health Economics , Health Econometrics , and broader Econometrics methodologies. He specializes in analyzing health inequality, socioeconomic determinants of health, and statistical modeling techniques for economic data. His work addresses critical issues such as child malnutrition, health concentration curves, and income-related health disparities. Dr. Khaled has contributed to peer-reviewed journals including European Journal of Health Economics , Journal of Business and Economic Statistics , and Health Economics . His methodologies often involve advanced econometric frameworks and Bayesian approaches. He holds an academic position in a leading economics department and collaborates with institutions like Edward Elgar Publishing. His research emphasizes bridging theoretical econometric models with real-world health policy applications.

پروفایل رسمی دانشگاه

Volker J Schmidمشاهده پروفایل

استاد

Ludwig Maximilian University of MunichGermany

Volker J Schmid is a Professor of Bayesian Imaging and Spatial Statistics at the Department of Statistics, Ludwig Maximilian University of Munich. He leads the Bayesian Imaging and Spatial Statistics group and contributes to interdisciplinary initiatives like the Munich Center of Machine Learning. His work bridges statistical theory with applications in medical imaging and biology. PhD in Statistics (2004), LMU Munich Diploma in Statistics (2000), LMU Munich Abitur, Joseph-von-Fraunhofer-Gymnasium Cham (1993) His research focuses on Bayesian computational methods for high-dimensional data, particularly in medical imaging (MRI, DCE-MRI) and biological microscopy (e.g., 3D nuclear architecture analysis via super-resolution microscopy). Key applications include disease mapping , image segmentation , and spatio-temporal modeling . His software tools (e.g., nucim , bioimagetools , BAMP ) enable quantitative analysis in nuclear imaging and age-period-cohort modeling. His 15 most recent publications span Bayesian modeling for medical imaging , spatio-temporal epidemiology , and computational biology . Topics include co-localization metrics in fluorescence microscopy, nuclear architecture analysis, and dynamic Bayesian frameworks for MRI data. Collaborations extend to neuroimaging, oncology, and nuclear biology.

پروفایل رسمی دانشگاه

Navid Izadyمشاهده پروفایل

مدرس ارشد

City, University of LondonUnited Kingdom

Dr. Navid Izady is a Reader in Operations & Supply Chain at Bayes Business School, part of City St George's, University of London. His academic career includes a PhD from Lancaster University Management School (2010), and prior roles at the University of Southampton. He specializes in stochastic modelling for healthcare and manufacturing operations, collaborating with hospitals and healthcare organizations on sponsored research and consultancy projects. Dr. Izady holds qualifications in Industrial Engineering from Sharif University of Technology (BSc and MSc) and a PhD in Management Science. He teaches operations management, stochastic modelling, healthcare modelling, and decision analysis across BSc, MSc, and MBA programs. His research focuses on optimizing healthcare logistics, patient flow management, and resource allocation in hospitals. He has developed frameworks for managing pandemic and non-pandemic demand, reconfiguring inpatient services, and optimizing staffing and patient admission/discharge processes. His work bridges theoretical stochastic models with practical healthcare challenges, emphasizing operational efficiency and resilience. Notable contributions include studies on inpatient bed pressure reduction, sample pooling techniques for pandemic testing, and queueing theory applications in emergency departments and specialty clinics. His publications highlight innovations in healthcare operations management and simulation methods. Dr. Izady's expertise includes operations research, simulation, statistics, and stochastic processes. He supports industry partnerships and has supervised numerous research students, contributing to both academic and applied knowledge in healthcare and manufacturing systems.

پروفایل رسمی دانشگاه

Karen Bandeen-Rocheمشاهده پروفایل

استاد

Johns Hopkins UniversityUnited States

Biostatistics
Gerontology
Aging
+۱۴ مورد دیگر

Karen Bandeen-Roche is a Professor and the Hurley-Dorrier Professor and Chair of the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health, with joint affiliations in the School of Medicine and the School of Nursing. She is a leading expert in biostatistical methodology, particularly in latent variable models, longitudinal analysis, and multivariate survival methods applied to aging and gerontology. Her research focuses on developing statistical models for unobservable processes such as frailty, resilience, and functional status in older adults. She has made significant contributions to the measurement of aging-related constructs and has extensive collaborative work in ophthalmology and neurology. Her methodological work includes mixture models, measurement error correction, and latent class modeling. The recent publications highlight a strong trend in gerontological biostatistics, with a focus on frailty, dementia risk, resilience, and multisystem physiological responses in aging. Her work integrates complex data from observational cohorts and clinical studies, often employing innovative latent variable frameworks to address measurement challenges in health outcomes. Scientific Awards and Honors: Marvin Zelen Leadership Award in Statistical Science (2016) Fellow of the American Statistical Association (2001) Brookdale National Fellow (1997) Golden Apple Award for Excellence in Teaching (2010) Garland Clay Award (1999) Chair, NIH BMRD Study Section (2006–2008) President, Eastern North American Region, International Biometric Society (2011–2013) Executive Board, International Biometric Society (2015–2022) Board of Directors, National Institute of Statistical Sciences (2020–2023) Karen Bandeen-Roche has been deeply involved in advising and training the next generation of researchers. She co-directs a training program in Biostatistics and Epidemiology of Aging and has received multiple teaching and mentoring awards. She has served on numerous academic committees, including appointments and promotions, faculty senate, and ethics committees at Johns Hopkins. Her grants and collaborative research span aging, dementia, ophthalmology, and cardiovascular health, often supported by NIH and other federal agencies. She leads the Center on Aging and Health and is actively involved in interdisciplinary research initiatives that bridge biostatistics, medicine, and public health. Her lab and research team focus on developing and applying advanced statistical methods to understand the biological and social determinants of healthy aging.

پروفایل رسمی دانشگاه

Natalia Noldeمشاهده پروفایل

استاد

University of British ColumbiaCanada

Natalia Nolde is a Professor in the Department of Statistics at the University of British Columbia, Faculty of Science. Her research focuses on multivariate extreme value theory , probabilistic modeling , and applications in quantitative risk management across finance, insurance, hydrology, and geosciences. Her work explores non-classical approaches to multivariate extremes, particularly through limit set geometry and asymptotic dependence structures , offering novel insights into tail dependence and risk assessment. Recent publications highlight her expertise in copula-based risk modeling , financial stress testing , and geohazard prediction . Current students include: Daniel Hadley Jonathan O.K. Agyeman

پروفایل رسمی دانشگاه

Melanie Schienleمشاهده پروفایل

استاد

Karlsruhe Institute of TechnologyGermany

Prof. Melanie Schienle is a Professor and Chair of Statistical Methods and Econometrics at the Department of Economics and Management, Karlsruhe Institute of Technology (KIT). She also holds a professorship in the Department of Mathematics at KIT since 2021. Her expertise spans statistical methods, econometrics, financial risk analysis, and forecasting. She leads the HKMetrics Network and the RespiNow Hub for respiratory disease forecasting. She serves as a Senior Fellow at the Rimini Center for Economic Analysis (RCEA), a steering committee member of the German Economic Association, and a member of the University Research Council at KIT. Education: Ph.D. (Dr. rer. pol.) in Economics from Mannheim University (2008), summa cum laude; Diploma in Mathematics (University of Karlsruhe, 2003) with a minor in theoretical physics. She has held academic positions at Leibniz University Hannover (2012–2015) and Humboldt University of Berlin (2008–2012). Research interests focus on financial networks, systemic risk, time series analysis, and machine learning applications in economics. She co-leads projects on nowcasting and forecasting, including collaborative efforts during the pandemic to predict hospitalizations. Her work integrates advanced statistical techniques with real-world policy implications. Prof. Schienle is an Associate Editor for the International Journal of Forecasting and Journal of Time Series Analysis . She has authored over 50 peer-reviewed publications and contributed to high-impact journals like Nature Communications and Journal of Business & Economic Statistics . She leads the Institute of Statistics at KIT and chairs the MathSEE initiative for interdisciplinary mathematical applications.

پروفایل رسمی دانشگاه

Chen Zhouمشاهده پروفایل

استاد

Erasmus University RotterdamNetherlands

Chen Zhou is a Full Professor of Mathematical Statistics and Risk Management at the Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam. He is a member of the Research Advisory Committee of Erasmus School of Economics and actively contributes to academic leadership and research governance. His research focuses on extreme value statistics and financial risk management , with significant contributions to the theoretical and applied understanding of extreme events in financial and statistical contexts. His work bridges mathematical rigor with practical applications in finance and econometrics. The recent publications highlight a strong trend in advancing methodologies for extreme value estimation, including bootstrapping techniques, tail copula modeling, dimension reduction for extremes, and semi-supervised frameworks. These works are published in high-impact journals such as the Journal of the American Statistical Association , Bernoulli , and the Journal of Finance , indicating broad disciplinary relevance across statistics, econometrics, and finance. Editorial work: Editor, Extremes (since 2015) He teaches in the Bachelor program of Econometrics and Management Science and the MSc program in Quantitative Finance, and is affiliated with the Tinbergen Institute. He has supervised multiple doctoral students, reflecting his active role in academic mentorship and research training. Chen Zhou leads a research network focused on extreme value theory, systemic risk, and statistical inference, collaborating with leading scholars in the field. His work continues to shape methodological developments in the analysis of rare and high-impact events.

پروفایل رسمی دانشگاه

Mawuli Kouami Segnonمشاهده پروفایل

پژوهشگر

University of MünsterGermany

Dr. Mawuli Kouami Segnon is a researcher at the Chair of Empirical Economics, School of Business and Economics, University of Münster. His work focuses on econometric modeling, financial time series analysis, and volatility forecasting across various domains including cryptocurrencies, energy markets, and macroeconomic indicators. Research interests include: Development of advanced volatility models (GARCH, multifractal, regime-switching) Applications to financial markets, energy economics, and macroeconomic policy High-frequency data analysis and mixed-frequency forecasting Count data modeling with conditional heteroscedasticity Portfolio risk management using copula and multifractal approaches Recent publications demonstrate expertise in: Geopolitical risk impacts on stock volatility Comparative analysis of realized variance measures Inflation uncertainty modeling in G7 countries Electricity price volatility in Australian markets Bitcoin market forecasting Historical economic data analysis Current projects (since 2020) involve: Innovative economic/financial time series forecasting Financial market volatility modeling Applications of multifractal structures in econometrics

پروفایل رسمی دانشگاه

Ruben Loaiza Mayaمشاهده پروفایل

دانشیار

Monash UniversityAustralia

Ruben Loaiza-Maya is an Associate Professor (Research) in the Department of Econometrics and Business Statistics at Monash University. He holds a PhD in Econometrics from the University of Melbourne and an undergraduate degree in Economics from Universidad Nacional de Colombia (Medellin). His research focuses on Copula Modelling, Bayesian Estimation Methods, Time Series Analysis, and Macroeconomic/Financial Forecasting. Key contributions include advancements in variational inference, state space models, and robust forecasting techniques under model misspecification. He leads the active project 'Variational Inference for Intractable and Misspecified State Space Models' (2023–2026), funded as a Primary Chief Investigator. His work contributes to UN Sustainable Development Goals through methodological advancements in economic and financial analysis. Recent research emphasizes scalable Bayesian methods, hybrid variational approaches, and efficient computational techniques for high-dimensional models. Publications span prestigious journals like the International Journal of Forecasting, Journal of Econometrics, and Journal of Business and Economic Statistics. Notable collaborations include studies on copula-based time series forecasting and robust approximate Bayesian computation. His work bridges theoretical econometrics with practical applications in risk management and macroeconomic policy.

پروفایل رسمی دانشگاه

Arno Onkenمشاهده پروفایل

استادیار

University of EdinburghUnited Kingdom

Dr. Arno Onken is a Lecturer (Assistant Professor) in Data Science for Life Sciences at the School of Informatics, University of Edinburgh, where he is also affiliated with the Institute for Adaptive and Neural Computation. He leads a research group focused on developing machine learning and statistical methods for modeling neural activity and analyzing large-scale neuroscience data. His work bridges artificial intelligence and computational neuroscience. His research interests lie at the intersection of machine learning, statistics, and neuroscience. He develops flexible probabilistic models such as copulas and Gaussian processes, deep learning architectures like Vision Transformers for brain activity prediction, and matrix/tensor factorization techniques for dimensionality reduction in neural datasets. His group aims to uncover interpretable structure in complex neural recordings and understand how behavior and cognition are encoded in population activity. The recent publications reflect a strong trend in combining modern deep learning with classical statistical modeling to analyze large-scale neural recordings. His work spans from foundational methods in copula modeling and information theory to applications in predicting visual cortex responses and modeling brainstem-hippocampus interactions across sleep states. The research has been published in top venues including NeurIPS, CVPR, eLife, and PLoS Computational Biology. Dr. Onken actively supervises PhD students and has developed several open-source scientific software packages, including the Mixed Vine Toolbox and Population Spike Train Factorization Toolbox. He teaches core courses in Machine Learning and Pattern Recognition and Data Mining and Exploration at the University of Edinburgh.

پروفایل رسمی دانشگاه

Alicia Rambaldiمشاهده پروفایل

استاد

University of QueenslandAustralia

Professor Alicia Rambaldi is Director of Research at the School of Economics, Faculty of Business, Economics and Law at the University of Queensland. She is also an Affiliate of the Centre for Efficiency and Productivity Analysis. Her academic career spans decades of research in econometric methodologies with applications to real-world economic problems. Professor Rambaldi's research interests focus on applied econometrics, time series econometrics, state-space models, and spatial time series models. She has made significant contributions to economic measurement, particularly in developing methodologies for computation of price indices for land and property, estimation with linked administrative data, and smoothing methodologies combining spatial and temporal information. Her work bridges theoretical econometrics with practical applications in housing markets, climate adaptation, and international economic comparisons. Her recent publications demonstrate a consistent focus on housing economics, with numerous papers on hedonic pricing models, property valuation, and the impact of environmental factors on real estate markets. She has also maintained a strong research program in international comparisons, purchasing power parity, and productivity analysis, often collaborating with leading researchers in these fields. Professor Rambaldi is actively involved in research supervision, currently advising on topics including language barriers faced by immigrants, distributive politics, and copula models. Her completed supervision includes significant work on purchasing power parities, development indexes, trade studies, and spatial analysis of tourism employment. Her current research projects include spatial time series models with applications to housing and land prices, transport demand modeling, and international comparisons. She has secured substantial funding from diverse sources including the Australian Research Council, Natural Hazards Research Australia, and government departments, demonstrating the applied relevance of her work. Professor Rambaldi leads an active research group within the Centre for Efficiency and Productivity Analysis, focusing on developing and applying advanced econometric techniques to address pressing economic measurement challenges. Her work often involves interdisciplinary collaboration with researchers in environmental science, urban planning, and transportation studies.

پروفایل رسمی دانشگاه