جست‌وجوی استاد و پژوهشگر

Jason Rightsمشاهده پروفایل

دانشیار

• Quantitative Methods
• Multilevel/Hierarchical Data Analysis
• Statistical Methods
• +۴ مورد دیگر

Dr. Jason Rights is an Associate Professor in the Department of Psychology within the Faculty of Arts at the University of British Columbia. His office is located in Kenny Room 2017 at 2136 West Mall, Vancouver, BC. He leads The Rights Lab, a quantitative methods research group dedicated to improving statistical practice in scientific research. His educational background includes: B.S. in Psychology and Mathematics from the University of North Carolina at Chapel Hill (2011) M.S. in Psychology (Quantitative Methods) from Vanderbilt University (2015) Ph.D. in Psychology (Quantitative Methods) from Vanderbilt University (2019) Dr. Rights' research focuses on addressing methodological complexities in multilevel/hierarchical data contexts where observations are nested (e.g., patients within clinicians, students within schools). His work spans several interconnected programs including developing R-squared measures for multilevel models, addressing issues with level-specific effects, exploring connections between multilevel and mixture models, and advancing latent variable model selection techniques. Analysis of his publication record reveals a consistent focus on methodological innovations in quantitative psychology, with particular emphasis on improving statistical techniques for hierarchical data structures. His work bridges theoretical statistical development with practical applications across psychology and related fields. Dr. Rights actively develops open-source software in R to implement his methodological contributions, making advanced statistical techniques accessible to researchers. The Rights Lab serves as the hub for his ongoing research program in quantitative methods development.

Philippe Campeauمشاهده پروفایل

دانشیار بالینی

• Medical Genetics
• Bone Dysplasias
• Skeletal Dysplasias
• +۱۲ مورد دیگر

Dr. Philippe Campeau is an Associate Clinical Professor in the Department of Pediatrics at the Faculty of Medicine, Université de Montréal. He is affiliated with CHU Sainte-Justine, a major pediatric hospital in Montreal, Quebec, where he works in the Medical Genetics Service. His clinical and research work focuses on genetic disorders affecting children, particularly in the areas of skeletal development and neurogenetics. Dr. Campeau obtained his Doctorate in Medicine from Laval University in Quebec (1998-2003) followed by specialty training in medical genetics at McGill University (2003-2008). He completed postdoctoral training at Baylor College of Medicine (2008-2013), which further developed his expertise in genetic research methodologies. His primary research interests include bone dysplasias , skeletal dysplasias , epilepsy , and epigenetic diseases . Dr. Campeau's laboratory identifies disease-causing genes, deciphers disease pathophysiology, and works to improve the management of children affected by these conditions. His work encompasses exome analysis , functional studies with cell lines and mouse models , and investigations into urea cycle abnormalities . He has made significant contributions to understanding genetic causes of conditions such as Genitopatellar syndrome (KAT6B), osteopetrosis, dysosteosclerosis (SLC29A3), osteogenesis imperfecta, early-onset osteoporosis (WNT1), Yunis-Varón syndrome (FIG4), and DOORS syndrome (TBC1D24). Dr. Campeau's publication record demonstrates a strong trajectory in medical genetics research, with numerous high-impact publications spanning from fundamental genetic discovery to translational research. His work spans skeletal disorders, neurodevelopmental conditions, and epigenetic mechanisms. Recent publications indicate an expanding focus on chromatin modifiers, DNA methylation patterns, and spliceosome function in neurodevelopmental conditions, reflecting the evolution of his research interests toward more complex molecular mechanisms. Dr. Campeau has received several research grants in recent years (6 starting in 2014) from organizations including the Fonds de la recherche en santé du Québec, Canadian Institutes of Health Research, and Fondation Grand Défi Pierre Lavoie. While specific students are not mentioned in the available information, as a clinical professor, he mentors medical students, residents, and research trainees in the Department of Pediatrics. His research is conducted as part of the 'Musculoskeletal Diseases and Rehabilitation' axis at CHU Sainte-Justine Research Center, where he collaborates with international research teams to identify disease-causing genes and develop better management strategies for children with genetic disorders.

Raymond T. Ngمشاهده پروفایل

استاد

• Data Mining
• Text Mining
• Health Informatics
• +۵ مورد دیگر

Raymond T. Ng is a Professor of Computer Science at the University of British Columbia (UBC) and serves as Director of the Data Science Institute . In addition, he is the part-time Chief Informatics Officer at the PROOF Centre of Excellence for the Prevention of Organ Failures located at St Paul’s Hospital. Since 2016 he has held the prestigious Canada Research Chair in Data Science and Analytics. Education B.Sc. (Hons.) Computer Science, University of British Columbia, 1986 M.Math. Computer Science, University of Waterloo, 1988 Ph.D. Computer Science, University of Maryland, College Park, 1992 Research Interests Professor Ng’s research lies at the intersection of data mining , text mining , health informatics , sensor analytics , and databases . Over the past decade he has focused on two major domains: Genomics & Biomarker Discovery: Developing multi-omics biomarker panels for heart, lung and kidney transplant rejection and COPD exacerbations using transcriptomics, proteomics and metabolomics data. Natural Language Processing: Mining and summarizing conversational text such as emails, blogs and meeting transcripts to generate structured metadata and actionable insights. Scientific Awards Canada Research Chair in Data Science and Analytics (2016-2026) Best Paper Award, ACM SIGMOD 2004 Best Paper Award, ACM SIGKDD 2001 Selected among Best Papers of VLDB ’99 & ’98 Governor General’s Gold Medal, UBC (1986) Research Funding & Leadership Since joining UBC in 1992, Professor Ng has continuously secured major peer-reviewed funding from NSERC, CIHR, Genome Canada, CFI, MITACS and industry partners (Google, IBM, SAP). He leads or co-leads several large-scale initiatives: HEARTBiT multi-marker blood test for cardiac transplant rejection (CIHR 2018-2021) MERIDIAN ocean acoustic data infrastructure (CFI 2018-2021) Pan-Canadian Early Detection of Lung Cancer (Terry Fox 2018-2021) Business Intelligence Network (NSERC 2009-2014) Multiple Genome Canada programs on biomarker translation (2004-2018) Laboratories & Teams Professor Ng directs the Data Science Institute and works closely with the Natural Language Processing Research Group . At the PROOF Centre he heads a multidisciplinary team of statisticians, computer scientists and clinicians advancing computational biomarker pipelines from discovery to clinical implementation.

Yves Bourgaultمشاهده پروفایل

استاد

• Computational Fluid Dynamics
• Numerical Methods
• Finite Element Methods
• +۳ مورد دیگر

Yves Bourgault is a Full Professor in the Department of Mathematics and Statistics at the University of Ottawa. He holds a MSc and PhD from Laval University. His research focuses on computational fluid dynamics, numerical methods, finite element techniques, and continuum mechanics modeling, with applications in cardiac electrophysiology and ecological systems. Dr. Bourgault has supervised several graduate students, including Edward Boey (co-supervised), Sana Keita, Saint-Cyr Koyagurebo-Ime, and Kak Choon Loy. His work integrates advanced numerical techniques to address complex problems in biomedical engineering, environmental science, and mathematical physics. Key methodologies include finite element methods, deferred correction schemes, and anisotropic mesh adaptation. His research group is part of the Applied Mathematics division at the University of Ottawa, emphasizing interdisciplinary applications. Recent work explores climate change impacts on ecological systems, cardiac tissue modeling using high-resolution MRI data, and robust numerical methods for reaction-diffusion equations. Publications span topics such as bidomain models for cardiac electrophysiology, fluid-structure interaction in heart mechanics, and mathematical modeling of fuel cells. His contributions bridge theoretical numerical analysis with real-world biomedical and environmental challenges.

Rasul Shafikovمشاهده پروفایل

استاد

• Several Complex Variables
• Complex Geometry
• Polynomial Convexity
• +۵ مورد دیگر

Rasul Shafikov is a Professor in the Department of Mathematics at Western University's Faculty of Science. He has maintained an active research program in complex analysis and geometry while teaching a range of undergraduate and graduate mathematics courses including Calculus, Real Analysis, Complex Analysis, and Functional Analysis over multiple academic years. Dr. Shafikov's research focuses on several complex variables and complex geometry, with particular interest in polynomial and rational convexity of real submanifolds in complex spaces, geometric properties of holomorphic mappings and functions, and holomorphic foliations on Levi-flat hypersurfaces. His work represents significant contributions to understanding the boundary behavior of holomorphic functions, convexity properties in complex spaces, and the geometric structure of complex manifolds. An analysis of his recent publications reveals a consistent trajectory in advancing the theory of complex analysis in several variables, with increasing focus on the interplay between complex geometry, CR geometry, and convexity properties. His work often involves collaborations with researchers across international institutions, demonstrating the global relevance of his research in complex analysis. Dr. Shafikov has supervised multiple PhD students and postdoctoral researchers who have gone on to academic positions at institutions worldwide, including the University of Arkansas, Indian Institute of Science in Bangalore, Masaryk University in Czech Republic, and Central Michigan University. His mentorship has produced scholars who continue to contribute to the field of complex analysis. He has co-authored a book titled 'Geometry of Holomorphic Mappings' (Birkhäuser, 2023) with S. Pinchuk and A. Sukhov, which serves as a significant contribution to the literature in complex analysis. His teaching portfolio includes advanced graduate courses such as Complex Analysis, Functional Analysis, and Real Analysis, demonstrating his expertise across multiple mathematical disciplines.

• Gastroenterology
• Epidemiology
• Cardiovascular Health
• +۳ مورد دیگر

Shrikant Bangdiwala , Professor at McMaster University 's Faculty of Health Sciences in the Department of Health Research Methods, Evidence, and Impact , leads groundbreaking research in disorders of gut-brain interaction, cardiovascular epidemiology, and statistical methodology. 2025 Research Focus: Gut-brain disorder subtyping, dietary pattern analysis, and machine learning applications in clinical trials 2024 Innovations: Development of GROOVE tool for symptom overlap visualization and exposome-DNA damage correlation studies Longitudinal Impact: 20+ years tracking GI comorbidities, cardiovascular outcomes, and educational interventions Research Clusters Gut-Brain Disorders: Prevalence modeling across 26+ countries, symptom stratification, and psychological comorbidities Cardiovascular: Mortality prediction models, antithrombotic risk assessment, and ACE-inhibitor effectiveness Epidemiological Innovation: Hybrid trial adjudication systems, statistical frameworks for complex interventions, and exposome analysis tools Methodological Expertise Specializes in biostatistical frameworks for cardiovascular trials, machine learning detection of trial irregularities, and epidemiological modeling of gut-brain disorders through the Rome Foundation Global Epidemiology Study.

Archer Yangمشاهده پروفایل

دانشیار

• Statistical machine learning
• High-dimensional statistics
• Computational statistics
• +۸ مورد دیگر

Archer Yang is an Associate Professor in the Department of Mathematics and Statistics at McGill University, with additional affiliations as an Associate Academic Member of Mila - Quebec AI Institute, Associate Member of the School of Computer Science, and Member of the Quantitative Life Science Program. His academic journey began with a PhD from the University of Minnesota under the supervision of Hui Zou, establishing his foundation in statistical methodology and machine learning. Dr. Yang's research spans three interconnected themes: statistical machine learning, applications in drug discovery, and computational genomics and healthcare. In statistical machine learning, he focuses on developing dimensionality reduction, probabilistic models, and causality-inspired methods to address complex high-dimensional data challenges. His work in drug discovery involves creating machine learning models to accelerate drug candidate identification and enhance understanding of drug efficacy and safety. In computational genomics and healthcare, he develops techniques to analyze genomic data, identify biomarkers, and explore the genetic basis of diseases, with the goal of improving precision medicine and predicting patient outcomes. His overarching objective is to bridge advanced data-driven methodologies with impactful applications in pharmacology, genomics, and healthcare. His recent publications reveal a strong trend toward applying machine learning to healthcare challenges, particularly in congenital heart disease analysis, mortality prediction, and drug discovery. His work demonstrates expertise in developing interpretable models that can handle complex, high-dimensional biomedical data while maintaining statistical rigor. The integration of causal inference methods with machine learning appears to be a growing focus in his research trajectory. ICML Spotlight Paper (top 2.6%, 313/12,107) Dr. Yang actively supervises a large research group including multiple postdoctoral fellows, PhD students, and Master's students. His lab has developed several notable software tools, including ml-mr for machine learning in Mendelian randomization. His supervision extends across statistics, computer science, and biomedical applications, reflecting the interdisciplinary nature of his work. He appears to maintain strong collaborative relationships with researchers in healthcare and genomics fields. His laboratory, the Archer Yang Lab, maintains active GitHub repositories focused on machine learning applications in healthcare and drug discovery, with particular emphasis on interpretable models and statistical methodology development. The lab appears to work at the intersection of theoretical statistics and practical biomedical applications, with projects spanning from algorithm development to clinical implementation.

Yuejian Chenمشاهده پروفایل

استادیار

• Dynamic Modelling
• Vibration Signal Processing
• Artificial Intelligence
• +۵ مورد دیگر

Dr. Yuejian Chen is an Assistant Professor in the Department of Mechanical Engineering at the University of Manitoba's Price Faculty of Engineering. His research focuses on dynamic modelling, vibration signal processing, artificial intelligence, and prognosis/health management for complex systems like railway vehicles, wind turbines, and steam turbines. He holds a PhD from the University of Alberta (2020) and was a postdoctoral fellow there until 2021. Prior to joining the University of Manitoba in 2024, he served as an Assistant Professor at Tongji University's Institute of Rail Transit in China from 2021 to 2024. His research integrates digital twins and advanced health management methodologies to ensure safe and cost-effective operation of mechanical systems. Key areas include non-stationary vibration analysis, fault detection via AI (e.g., LSTM networks), and physics-informed machine learning. He has authored/co-authored over 60 publications and serves on editorial boards for journals such as IEEE Sensors Journal , IEEE Transactions on Instrumentation and Measurement , and Smart and Resilient Transportation . Dr. Chen's work bridges theoretical advancements with practical applications, emphasizing railway transportation and energy systems. His recent publications (2021–2025) highlight contributions to gearbox fault detection under variable speed conditions, multi-camera metro monitoring systems, and data-driven load identification strategies. His research trends emphasize fusion of physical principles with AI for robust diagnostics and health management across mechanical systems. He is actively recruiting graduate students interested in dynamic systems, signal processing, and AI applications in mechanical engineering. His research group collaborates with industry partners to address real-world challenges in machinery safety and efficiency.

Najat Bhiryمشاهده پروفایل

استاد

• Quaternary Geology
• Geomorphology
• Natural Hazards
• +۶ مورد دیگر

Najat Bhiry is a Full Professor in the Department of Geography within the Faculty of Forestry, Geography and Geomatics at Université Laval. She maintains her office at the Abitibi-Price Pavilion (office 3115) and serves as President of the Student Affairs Commission. Her research is closely affiliated with the Centre for Nordic Studies (CEN), where she is a regular member, and she actively participates in multiple research initiatives focusing on northern environments and Indigenous communities. Dr. Bhiry's educational background includes a PhD in Quaternary Geology from Pierre and Marie Curie University in Paris, a Master's degree in Quaternary Geology, and a Bachelor's degree in Geology and Biology. Her academic journey has positioned her at the intersection of earth sciences, environmental studies, and archaeology. Her research interests span Quaternary geology and geomorphology (including stratigraphy, sedimentology, and micromorphology), natural hazards and risks, plant paleoecology, geoarchaeology, and paleoenvironments. She applies these interests to understanding Arctic and subarctic landscapes, with particular attention to the impacts of climate change on northern ecosystems and Indigenous cultural heritage. Her work often integrates geological, archaeological, and environmental perspectives to reconstruct past landscapes and human-environment interactions. Dr. Bhiry's recent publications reveal a strong focus on Arctic and subarctic research, with particular emphasis on permafrost dynamics, geoarchaeology, climate change impacts, and Indigenous knowledge systems. Her work frequently involves international collaborations and addresses critical questions about northern landscape evolution, cultural heritage preservation, and environmental change. She demonstrates expertise in both field-based methodologies and advanced analytical techniques including remote sensing and micromorphological analysis. Dr. Bhiry serves on several important committees and editorial boards: Member of the First Peoples Committee of the Nordic Institute of Quebec Member of the Editorial Board of the Nordicana D platform Member of the Steering Committee of the Ecoscience journal Member of the Steering Committee of the journal Études Inuit Studies Dr. Bhiry currently supervises multiple graduate students including Rachid Addou (postdoctoral fellow), Sabrina Bujold, Laura Brassard, Vincent Filion, Danielle Chiasson, and Laurence Côté (all master's students with thesis). In the past five years, she has successfully guided Josuah Tremblay, Guillaume Pouliot, Jérémy Grenier, Rachel Labrie, Frédéric Mansau, and Sarah Robert to completion of their degrees. Her research is supported by numerous grants from organizations including Fonds de recherche du Québec, Ressources naturelles Canada, CNRS (France), MITACS Inc., and the Natural Sciences and Engineering Research Council of Canada. Her laboratory work primarily occurs through the Centre for Nordic Studies (CEN), where she collaborates with interdisciplinary teams studying northern environments. Her research often involves fieldwork in Arctic regions including Nunavik (northern Quebec), Nunatsiavut (Labrador), and international sites in Morocco and Iceland. These teams integrate geological, archaeological, and environmental science perspectives to address complex questions about landscape evolution and human adaptation in northern environments.

• Combinatorial Optimization
• Transportation
• Vehicle Routing
• +۷ مورد دیگر

Jean-Yves Potvin is a Full Professor in the Department of Computer Science and Operations Research at the Faculty of Arts and Sciences, Université de Montréal. He focuses on integrating operations research and artificial intelligence techniques to solve complex transportation and telecommunications problems. Role: Full Professor Affiliation: Université de Montréal, CIRRELT, OPTIM Contact: jean-yves.potvin@umontreal.ca , potvin@iro.umontreal.ca , Jean-Yves.Potvin@cirrelt.ca Research Interests: Potvin specializes in combinatorial optimization and vehicle routing with time-dependent constraints. He develops metaheuristics like tabu search and genetic algorithms for real-time applications, particularly in dynamic vehicle dispatching and network design. Article Trends: Recent publications focus on time-dependent vehicle routing, technician scheduling with multiple constraints, and parallel implementations for efficiency. Key areas include workload equity, stochastic item routing, and real-time adjustments using machine learning. Grants and Projects: He has been involved in several funded projects related to vehicle routing, network design, and telecommunications expansion, supported by organizations like NSERC and FRQNT. Labs and Teams: Potvin is affiliated with CIRRELT (Interuniversity Research Centre on Enterprise Networks, Logistics, and Transport) and OPTIM (Optimization Simulation Laboratory).

Aseem Raj Sharmaمشاهده پروفایل

استاد مدعو

• Climate Change
• Hydro-climatology
• Extreme Weather Events
• +۷ مورد دیگر

Dr. Aseem Raj Sharma is an Adjunct Faculty member in the Department of Geography, Earth, and Environmental Sciences at the University of Northern British Columbia (UNBC). He is also a Research Climatologist with the B.C. Ministry of Forests, where he specializes in hydro-climatology, focusing on extreme climate events and climate change impacts. Education: PhD, University of Northern British Columbia Research Focus: Dr. Sharma's research is centered on understanding the dynamics and impacts of extreme climate events. He investigates how large-scale climate variability influences phenomena such as atmospheric rivers and heatwaves, which significantly contribute to flooding and wildfires. His work delves into the underlying mechanisms driving the frequency, intensity, and spatial patterns of these extremes, with a particular emphasis on their interconnected nature and potential for compound impacts. His expertise spans several key areas including: Hydro-climatology Climate change impacts Atmospheric rivers and their role in extreme precipitation Heatwaves and associated wildfire risks Geospatial data analysis using R, RShiny, and QGIS Publications Overview: Dr. Sharma has an extensive publication record, with his work appearing in high-impact journals. His research covers a broad range of topics, from analyzing historical trends in temperature and precipitation extremes in regions like the Koshi River Basin and British Columbia, to linking atmospheric phenomena like atmospheric rivers and blocking patterns to hydrological extremes and wildfire risks. His 2024 publications focus on the efficacy of climate datasets and the 2021 heat dome's role in record-breaking fire weather, highlighting his ongoing contribution to understanding recent extreme events. Current Status: He is currently not accepting graduate students, as stated in his profile. He is available to be contacted by the media as a subject matter expert in his fields of expertise.

Mustapha Yagoubمشاهده پروفایل

استاد

• RF/microwave CAD
• RFID design
• Neural networks
• +۴ مورد دیگر

Professor Mustapha Yagoub is a distinguished faculty member in the School of Electrical Engineering and Computer Science at the University of Ottawa, where he has been serving since 2001. With over 300 publications to his name, he specializes in RF/microwave engineering, neural networks applications, and RFID systems. His research bridges theoretical advances with practical industrial applications in wireless communications and microwave circuit design. Education: Dipl.-Ing. in Electronics, École Nationale Polytechnique, Algiers, Algeria (1979) Magister in Telecommunications, École Nationale Polytechnique, Algiers, Algeria (1987) Ph.D., Institut National Polytechnique, Toulouse, France (1994) Professor Yagoub's research spans several interconnected domains within electrical engineering, with particular emphasis on microwave circuit design and wireless communication systems. His work integrates neural network techniques with traditional microwave engineering approaches, creating innovative solutions for complex RF problems. He has made significant contributions to RFID technology, particularly for specialized applications like underground mining environments. His expertise in applied electromagnetics has led to numerous advances in antenna design and microwave component modeling. Analysis of Professor Yagoub's recent publications reveals a strong focus on practical microwave circuit design, with particular attention to low-noise amplifiers, RF parameter extraction techniques, and efficient circuit implementations for wireless communications. His work demonstrates consistent integration of electromagnetic theory with circuit design principles, often applying novel computational approaches to solve challenging problems in microwave engineering. Many publications address specific industry needs in wireless communications, RFID systems, and energy-efficient circuit design. Professional Affiliations: Senior Member, IEEE Microwave Theory and Techniques Society Professional Engineer, Ontario, Canada Member, Ordre des ingénieurs du Québec, Canada Professor Yagoub has supervised numerous graduate students through their research in microwave engineering and wireless communications. His extensive publication record suggests substantial research funding throughout his career, supporting work in microwave circuit design, neural network applications in RF systems, and RFID technology development. His collaborations with researchers across multiple institutions and countries have contributed to the international recognition of his work in microwave engineering. While specific laboratory details aren't provided in the available information, Professor Yagoub's research focus suggests he leads or has led laboratory facilities for microwave circuit design, RF measurement, and wireless communication systems testing. His work on neural network applications in microwave engineering indicates a computational research component alongside experimental work.

Christopher Blier-Wongمشاهده پروفایل

استادیار

• Actuarial Science
• Machine Learning
• Statistics
• +۴ مورد دیگر

Christopher Blier-Wong is an Assistant Professor in the Department of Statistical Sciences within the Faculty of Arts and Science at the University of Toronto, where he joined in 2024 after completing a postdoctoral fellowship at the University of Waterloo. He holds a PhD in Actuarial Science from Université Laval (2023), along with multiple graduate degrees in Computer Science (AI specialization) and Actuarial Science from the same institution. His research lies at the intersection of actuarial science, machine learning, and statistics, with a particular focus on dependence modelling and e-variables. His work explores non-life insurance, risk theory, risk-sharing mechanisms, and the application of machine learning techniques to actuarial problems. Recent publications demonstrate his expertise in constructing high-dimensional copulas, developing efficient risk allocation methods, and pioneering the use of image data in insurance pricing. His research portfolio shows a strong trend toward developing computationally efficient methods for complex actuarial problems, particularly those involving dependence structures. He has made significant contributions to the understanding of Farlie-Gumbel-Morgenstern (FGM) copulas and their generalizations, creating methods that scale effectively to high dimensions while maintaining computational tractability. Scientific Awards and Recognition: NSERC Postdoctoral Fellowship (2023-2025) ARC Graduate Student Presentation Award from Society of Actuaries (2022) Canada Graduate Scholarships Michael Smith Foreign Study Supplements (2022) Multiple research grants from NSERC, Université Laval, and industry partners Honor Roll for Academic Excellence at Université Laval (2018, 2020) Blier-Wong currently leads research funded by a major sponsored research agreement titled 'Dependence, inference and unstructured data in actuarial science' (2025-2030). He has supervised graduate students through teaching courses such as 'STA 2536 Data Science for Risk Modelling' at the University of Toronto and previously taught 'ACT-1003 Complements in Mathematics' at Université Laval. His research group focuses on developing novel statistical methodologies with practical applications in insurance and risk management.

• Respiratory Diseases
• Infectious Diseases
• Molecular Biology
• +۶ مورد دیگر

Simon Rousseau is an Associate Professor at the Faculty of Medicine and Health Sciences , McGill University , and a Scientist at the RI-MUHC (Glen site) within the Translational Research in Respiratory Diseases Program and Centre for Translational Biology . His research spans Respiratory Diseases , Infectious Diseases , and Inflammation , with a focus on Cystic Fibrosis and COVID-19 . Key Research Areas: Molecular mechanisms of host-pathogen interactions Signal transduction in airway infections Systems biology of respiratory diseases Biobanking and AI integration in clinical research His recent work highlights trends in SARS-CoV-2 response diversity, Pseudomonas aeruginosa pathogenesis, and AI-driven clinical network modeling (RAMEN). Dr. Rousseau contributes to major initiatives like the Biobanque québécoise de la COVID-19 (BQC19) and Canadian Respiratory Research Network (CRRN) , emphasizing translational applications.

• Complex Analysis
• Potential Theory
• Approximation Theory
• +۳ مورد دیگر

Paul M Gauthier is an Associate Professor at the University of Montreal's Department of Mathematics and Statistics, affiliated with the Faculty of Arts and Science. His research focuses on complex analysis and potential theory, particularly approximation by holomorphic or harmonic functions, with recent emphasis on exploring the Riemann Hypothesis through complex approximation methods. He has supervised multiple Master's students, including Leila Ezeddin, Richard Piché, Alain Rémillard, Jean-Philippe Samson, and Sébastien Manka. Gauthier is a member of the prestigious Centre de recherches mathématiques (CRM), leading and co-researching in strategic initiatives like the 'Complex approximation on Riemann surfaces and in infinite dimensions' project funded by NSERC and FRQNT. His work bridges theoretical mathematics with applications in number theory and geometry. Key research projects include multi-year grants exploring analytic approximation and Riemann surface applications. His affiliations also extend to collaborations with institutions like the CRM, emphasizing interdisciplinary and foundational mathematical research. Gauthier’s contributions are evident in over 50 publications, showcasing expertise in approximation theory, harmonic functions, and zeta function analysis.