Bayesian Spatial Modeling Professors and Supervisors in Canada

James Danckertمشاهده پروفایل

استاد

University of WaterlooCanada

James Danckert is a Professor in the Department of Psychology at the University of Waterloo, where he also serves as the Cognitive Neuroscience Area Head. He is cross-appointed to the Research Institute in Aging and leads the Danckert Attention and Action Group (Danckert Lab). His research spans cognitive neuroscience with particular focus on understanding the mechanisms and brain states that give rise to boredom and mental model updating. Dr. Danckert earned his BA from Melbourne University (Australia), followed by his MA and PhD from La Trobe University (Australia). His academic journey has positioned him as a leading expert in cognitive neuroscience with a specific emphasis on boredom psychology and attention mechanisms. His primary research interests include the cognitive and neural mechanisms of boredom, particularly in individuals with traumatic brain injuries, and mental model updating in relation to neglect syndrome. Danckert's work explores boredom through behavioral tasks like foraging, sustained attention tasks, and executive control tasks, utilizing neuroimaging techniques such as fMRI and tDCS. His mental model updating research involves working with stroke patients (with access to a database of over 800 patients), fMRI, and computational modeling. Analysis of Dr. Danckert's most recent publications reveals a continued focus on boredom and mental model updating, with increasing interdisciplinary approaches incorporating computational modeling, AI, and genetic perspectives. His work bridges cognitive psychology, neuroscience, and clinical applications, with particular emphasis on how boredom relates to attention, agency, and decision-making processes. Dr. Danckert has received significant recognition for his work, including: Former Canada Research Chair (Tier II) in Cognitive Neuroscience Recipient of the 40 Under 40 Award from the Region of Waterloo As a mentor, Dr. Danckert supervises graduate students in the Psychology Department at Waterloo, teaching advanced courses such as Psych 783: Neuroimaging and Cognition. His research is supported by prestigious funding sources including the Natural Sciences and Engineering Research Council (NSERC) and the Canada Foundation for Innovation (CFI). The Danckert Lab maintains a comprehensive research program with two main streams: boredom research and mental model updating. The lab utilizes diverse methodologies including behavioral testing, neuroimaging, computational modeling, and collaborations with experts in evolutionary genetics. The lab's work has significant implications for understanding cognitive processes in both healthy individuals and those with neurological conditions.

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Paul Marriottمشاهده پروفایل

استاد

University of WaterlooCanada

Paul Marriott is a Professor in the Department of Statistics and Actuarial Science at the University of Waterloo. His research focuses on integrating geometric principles, particularly differential and convex geometry, into statistical methodologies, with a recent emphasis on mixture models and information geometry. He has published extensively across diverse journals such as Biometrika, Annals of Statistics, and Psychological Medicine, bridging theoretical and applied statistics. Education: PhD, University of Warwick (1989) MA, University of Oxford (1984) Research Trends: His work explores geometric frameworks for statistical inference, mixture model parameterization, and robustness analysis. Recent publications highlight causal modeling, neural spike train analysis, and high-dimensional data applications. Contact: Office: Mathematics & Computer Building (M3) 4204, Phone: 519-888-4911 x35545, Email: pmarriot@math.uwaterloo.ca

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Rui Huمشاهده پروفایل

دانشیار

MacEwan UniversityCanada

Rui Hu is an Associate Professor at the Department of Mathematics and Statistics within MacEwan University's Faculty of Arts and Science. Their expertise lies in Experimental Design , Robustness in Statistics , and Spatial Statistics , with a strong focus on mathematical analysis and modeling. Education: PhD in Statistics (2016), with a thesis on Robust Designs for Model Discrimination and Prediction of Threshold Probability. Rui's research bridges fractional calculus, functional analysis, and epidemiological modeling, particularly through applications of partial differential equations and Sobolev/Besov space inequalities. Their recent work explores nonlocal operators and extensions via the Caffarelli–Silvestre framework. Rui has published extensively on topics including metapopulation disease models , robust experimental design , and mathematical biology , with a chronological focus from 2011 to 2025. Key trends include stability analysis in population dynamics and innovative applications of probability density functions in sound detection.

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Ying Zhangمشاهده پروفایل

استاد

Acadia UniversityCanada

Ying Zhang is a Professor in the Department of Mathematics and Statistics at Acadia University, maintaining an office in Huggins Science Hall, Room 151. She earned her BSc from Shandong Normal University and advanced degrees (MA, MSc, PhD) from Western University, complemented by P.Stat. certification (Certificate #78) from the Statistical Society of Canada. Her educational background includes: BSc from Shandong Normal University MA, MSc, PhD from Western University Professor Zhang's research centers on Time Series Analysis and Applied Statistics , extending to Statistical Computing, Symbolic Algebra Computing, and Statistical Consulting in Biostatistics, Survey Design, and Research Methodology. Her work demonstrates significant applications in environmental science (water resources trend analysis), health sciences (drug safety and utilization studies), and ecological modeling (wildlife population dynamics), with methodological innovations in nonparametric testing and hierarchical modeling. Analysis of her 2013-2018 publications reveals a dominant focus on developing novel time series methodologies for environmental and health contexts, particularly seasonal trend detection, medication utilization patterns, and ecological data analysis. Her work consistently bridges theoretical statistics with practical applications across disciplines. She actively contributes through the Statistical Consulting Centre and the CANSSI Maritime Statistical and Health Sciences Collaborating Centre , holding P.Stat. designation from the Statistical Society of Canada. While her collaborative publications indicate interdisciplinary engagement, specific details of grant funding and student advising are not documented in available sources.

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Stephanie Clelandمشاهده پروفایل

استادیار

University of British ColumbiaCanada

Stephanie Cleland is an Assistant Professor and Legacy for Airway Health Chair in Promotion of Lung Health at Simon Fraser University's Faculty of Health Sciences . She also serves as a Research Scientist at the Vancouver Coastal Health Research Institute and an Affiliate Investigator with Environmental Health Services at BC Centre for Disease Control (BCCDC) . PhD and MSPH in Environmental Sciences and Engineering from University of North Carolina at Chapel Hill BS in Computer Science and Community Health from Tufts University Former Oak Ridge Institute for Science and Education (ORISE) research fellow at US EPA Her research integrates environmental epidemiology , exposure assessment , and health impact assessment to analyze climate change-related health risks including wildfire smoke and extreme heat . She employs advanced statistical methods and novel datasets to: Identify harmful exposure levels/durations Determine at-risk population characteristics Evaluate mitigation strategies Develop spatiotemporal exposure models Quantify community resilience factors Assess cognitive and cardiovascular impacts Current research emphasizes machine learning applications for exposure assessment and environmental health communication strategies. Her work has been published in leading environmental health journals focusing on: PM2.5 and ozone health effects Climate change health modeling Wildfire smoke epidemiology Heat-related health impacts Indoor air quality interventions Geospatial exposure analysis

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Guillaume de Lafontaineمشاهده پروفایل

استاد

University of Quebec in Abitibi-TémiscamingueCanada

Guillaume de Lafontaine is a Professor at the University of Quebec in Rimouski (UQAR) and holds the Canada Research Chair in Integrative Biology of Northern Flora. His work focuses on the ecological, biogeographical, and evolutionary responses of arcto-boreal flora to historical and contemporary climate change. He is affiliated with the Department of Biology, Chemistry and Geography at UQAR and is a regular member of the Centre d'Étude de la Forêt (CEF), Collaborating member of the Centre for Nordic Studies (CEN), Associate member of the Quebec Biodiversity Science Center (CSBQ), Member of the BORÉAS northern environments research group, and Member of the Quebec Biodiversity Institute (IQBIO). De Lafontaine's research employs an integrative biology approach combining field ecology, population genetics/genomics, modeling, and paleoecology to assess ecosystem responses to climate change and disturbances. His work primarily targets Quebec/Canadian biogeographic models but also extends to Alaska, Europe, Asia, and cold climates of tropical latitudes through collaborations. His research program is structured around two main axes: threats of extinction at the warm margin and expansion capacity at the northern limit of boreal species. Analysis of his recent publications reveals a strong focus on climate change impacts on boreal ecosystems, with particular attention to species responses at range margins, historical biogeography through paleoecological reconstructions, and genetic adaptation to changing environments. His work spans multiple spatial and temporal scales, from contemporary ecological dynamics to Quaternary climate change impacts. As an academic mentor, Professor de Lafontaine has supervised numerous doctoral and master's students, postdoctoral researchers, and interns, contributing significantly to the training of the next generation of forest scientists. His research has been published extensively in high-impact journals across ecology, evolution, biogeography, and paleoecology.

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