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Pierre DuchesneView profile

Professor

• Time Series Analysis
• Sampling Theory
• Multivariate Analysis
• +2 more

Pierre Duchesne is a Full Professor in the Department of Mathematics and Statistics at the University of Montreal . He serves as Professor-responsibility for the M.Sc. and Ph.D. in Statistics programs (2000-2004). His research focuses on applied statistics with emphasis on: Time Series Analysis (univariate and multivariate models, serial correlation testing, portmanteau statistics) Sampling Theory (robust estimation methods, calibration estimators) Multivariate Analysis (ARCH effects, vector autoregressive models, causality testing) Applications in Econometrics and Financial Econometrics His work combines theoretical development with practical implementation through: Wavelet-based diagnostic methods Simulation studies for model validation Software development (S-PLUS/SAS) for statistical analysis Collaboration with organizations like Statistics Canada and Canadian Journal of Statistics He has served as Associate Editor for journals including Computational Statistics & Data Analysis (CSDA) and Canadian Journal of Statistics (CJS/RCS) .

Irina PaciView profile

Professor

• Self-assembly on solid surfaces
• Monte Carlo methods
• Multi-scale computational methods
• +3 more

Dr. Irina Paci is a Professor of Chemistry at the University of Victoria, specializing in theoretical and computational chemistry. Her research focuses on understanding molecular self-assembly processes, particularly at solid surfaces, and developing multi-scale computational methods to model materials' dynamic behavior under external fields. She holds a PhD from Queen's University and completed postdoctoral research at Queen's and Northwestern University. Her work integrates Monte Carlo simulations, density functional theory (DFT), and quantum chemistry to study surface adsorption mechanisms, catalytic reactions, and nanocomposite dielectric properties. Key areas include cysteine adsorption on gold surfaces, palladium-catalyzed cross-coupling reactions, and the impact of solvent effects on reaction pathways. Recent studies explore aluminum oxide degradation in perovskite solar cells and quantitative reactivity models for nucleophilic aromatic substitution. Teaching interests span physical chemistry, quantum mechanics, and computational methods. Dr. Paci leads the Paci Research Group, which includes graduate students like Archita Adluri and Natalie Stubb, focusing on advancing computational methodologies for energy materials and surface science. Her lab's work bridges fundamental theory with applications in nanotechnology and sustainable energy systems.

Brent LyonsView profile

Associate Professor

• Stigma and Identity Management
• Worker Well-Being
• Diversity and Inclusion
• +4 more

Brent Lyons is an Associate Professor of Organization Studies at the Schulich School of Business, York University. His research focuses on stigma, identity management, and worker well-being, particularly within marginalized groups such as disabled employees. He holds significant academic roles, including editorial board memberships for top journals like Journal of Applied Psychology and Journal of Management . Lyons has earned notable awards, including the York Research Chair in Stigmatization and Social Identity and the Seymour Schulich Teaching Excellence Award. His work is funded by SSHRC grants and addresses topics like dominant-group identity threat, vulnerable workers, and disclosure strategies for marginalized identities. His recent publications emphasize systemic challenges faced by stigmatized groups, including within-group stigmatization among high-status workers and the impact of political discourse on workplace morale. Courses taught include Organizational Behaviour and Diversity and Inclusion in Organizations . Key Research Themes: Stigma dynamics, identity management, workplace diversity, vulnerable populations. Grants: Multiple SSHRC grants supporting research on marginalized workers and organizational inclusion. Awards: Schulich Research Excellence Fellow (2024–2027), York Research Leader (2020).

Kevin SchneiderView profile

Professor

• Software Architecture and Design
• Software Evolution and Maintenance
• Software Analysis and Navigation
• +6 more

Dr. Kevin Schneider is a Professor in the Department of Computer Science at the University of Saskatchewan. His research focuses on software architecture, evolution, analysis, and visualization, with notable work in quantum computing applications and machine learning. He also explores collaborative software teams and domain-specific languages to enhance development processes. Education: Ph.D., Computing and Information Science, Queen’s University (2000) Research Associate, Computing and Information Science, Queen’s University (1991–94) M.Sc., Computing and Information Science, Queen’s University (1990) B.Sc.(Hon), Computational Science, University of Saskatchewan (1980) Research interests include software design principles, maintenance strategies, and the integration of AI/quantum computing into software engineering. He emphasizes reproducibility in scientific workflows and tools like VizSciFlow. His work often bridges theory and practice, addressing challenges in code clone stability, user feedback management, and healthcare-related machine learning frameworks. Scientific Awards: Most Influential Paper at SCAM 2001 for his work on software engineering via source transformation. Advising and grants: While no specific advisees are listed, his research involves large-scale projects such as the Nutrient App and automated polyp segmentation tools. He collaborates on grants related to quantum computing applications and cloud-based software systems. Labs and teams: His work centers on collaborative scientific data analysis groups and developing tools for real-time groupware systems in complex workflows. He contributes to projects like CloneCognition and FSECAM, aiming to improve software design and maintenance through advanced analytics.

Marius ParaschivoiuView profile

Professor

• Computational Fluid Dynamics
• Finite Element Methods
• Aerodynamic Simulations
• +7 more

Marius Paraschivoiu is a Professor in the Department of Mechanical, Industrial and Aerospace Engineering at Concordia University, within the Faculty of Engineering and Computer Science. His research focuses on computational fluid dynamics (CFD), finite element methods, and aerodynamic simulations with applications to wind energy systems, acoustic simulations, and turbulence modeling. He holds a PhD in engineering and has expertise in parallel computing and urban wind energy potential assessment. His work emphasizes optimizing vertical axis wind turbine (VAWT) performance in urban environments, including roof-mounted installations, wake interactions, and turbulence effects. Paraschivoiu has extensively studied the impact of building geometry, corner placements, and fluid-structure interactions on turbine efficiency. His CFD-based analyses address challenges like mesh adaptation, multiphase flows, and real-gas modeling for hydrogen systems. Key research themes include improving wind energy harvesting through innovative turbine designs, mitigating aerodynamic noise, and enhancing flow uniformity in complex configurations. Paraschivoiu’s contributions span over 50 peer-reviewed articles, with recent focus on urban microclimate effects, VAWT array optimization, and turbine blade morphing concepts. He maintains an active research website at Concordia University and collaborates on applied projects involving CFD validation and industrial gas turbine combustor emissions.

• Coding and K-12 education
• Inclusive mathematics education
• Learning through technology
• +3 more

Dr. Diane Tepylo is an Associate Teaching Professor at the Faculty of Education, Ontario Tech University. She is located at Charles Hall, Room 336 in the Downtown Oshawa campus. Her contact information includes the email diane.tepylo@ontariotechu.ca and phone number 905.721.8668 ext. 3768. Dr. Tepylo holds a PhD in Applied Psychology and Human Development from the Ontario Institute for Studies in Education (OISE), focusing on mathematics teaching and learning within STEM fields. Her research interests include Coding and K-12 education, Inclusive mathematics education (particularly for at-risk students, English language learners, and culturally responsive pedagogy), Learning through technology, Spatial reasoning in STEAM education, and STEAM teacher development for both pre-service and in-service educators. She emphasizes innovative pedagogical approaches, such as flipped classrooms and problem-solving challenges to enhance student engagement and learning outcomes. Dr. Tepylo teaches a diverse range of courses across multiple programs, including: Bachelor of Commerce: BUSI 1915U (Business Mathematics I) Bachelor of Education: EDUC 1311U and EDUC 2408U (Coding and Communication), CURS 4140U and CURS 4141U (Mathematics Curriculum Studies) Bachelor of Arts, Educational Studies: EDST 1000U (Foundations of Learning), EDST 1100U (Problem and Inquiry-Based Learning), EDST 3170U (Developing Numeracy), EDST 4000U (Inquiry and Professional Practice), EDST 4120U (Games and Simulations for Learning), EDST 4610U (Coding and Maker Pedagogies for Young Children) No scientific awards or grants are explicitly mentioned in the provided information. Her work focuses on bridging educational theory and practice, with a strong emphasis on student-centered learning and technology integration.

Milica MiočevićView profile

Associate Professor

• Quantitative Psychology
• Statistical Mediation Analysis
• Bayesian Methods
• +3 more

Milica Miočević is an Associate Professor in the Department of Psychology at McGill University. She previously held an Assistant Professor position at Utrecht University's Department of Methods and Statistics. Her research focuses on statistical mediation analysis and Bayesian methods applied to social, health, and behavioral sciences, with three main research lines: optimal methods for Bayesian mediation priors, synthesizing mediated effect findings across studies, and mediation analysis in Single Case Experimental Designs (SCEDs). Dr. Miočević earned her Ph.D. from Arizona State University under advisors Dave MacKinnon and Roy Levy. Her work emphasizes methodological innovation in small sample contexts and evidence synthesis. The Miocevic Lab at McGill explores quantitative psychology and modeling techniques. Her recent publications span Bayesian vs frequentist estimation comparisons, prior distribution development, and mediation analysis methodologies. She has contributed to edited volumes on small sample solutions and published extensively in Structural Equation Modeling journals. Dr. Miočević's research bridges statistical theory and applied practice, advancing tools for researchers working with complex data structures and limited sample sizes.

Leonie BaumannView profile

Assistant Professor

• Economic Theory
• Networks
• Mechanism Design
• +1 more

Dr. Leonie Baumann is an Assistant Professor in the Department of Economics at McGill University, specializing in Economic Theory, Networks, Mechanism Design, and Game Theory. She holds a Ph.D. (summa cum laude) and M.Sc. in Economics from the University of Hamburg, and dual B.A. degrees from the University of Siegen. Currently on maternity leave, Dr. Baumann previously served as a Postdoctoral Research Associate at the University of Cambridge. Her research explores social interactions in microeconomic theory, with a focus on network formation dynamics, strategic evidence disclosure, and robust implementation mechanisms. Recent work examines how network structures influence economic decision-making and resource allocation. Dr. Baumann's publications demonstrate consistent focus on network economics and game-theoretic modeling, with emerging applications in discrimination mechanisms and evidence disclosure. Her methodological approaches combine theoretical rigor with computational innovations. Awards & Recognition: Vice-Chancellor's Innovation Award (2020) Econometric Society Travel Grant (2015) Multiple research grants including SSHRC and FQRSC funding Supervision & Service: Currently advising 4 doctoral students on topics ranging from biosolvent characterization to indoor air quality Active editorial board member for Journal of Mathematical Economics Organizes international conferences on economic theory

• Educational Technology
• Computer Science Education
• Teacher Education
• +6 more

Mike Carbonaro is a Professor in the Department of Educational Psychology at the University of Alberta's Faculty of Education. He holds multiple advanced degrees including a Ph.D. (Educational Psychology), M.Sc. (Computing Science), and interdisciplinary credentials in Education. His research focuses on educational technology integration, robotics in K-12 education, computational thinking, and interprofessional health sciences education. He pioneered Canada's first university-level course on LEGO robotics for K-12 and contributed to a major simulation-based healthcare training grant. He co-developed the ScriptEase project and collaborated on GRAND initiatives like BELIEVE and HLTHSIM. Education: Ph.D. Educational Psychology, University of Alberta (1997) M.Sc. Computing Science (AI focus), University of Alberta (1993) B.A. Computer Science, York University (1991) M.Ed. Educational Psychology, University of Alberta (1988) B.Ed. Secondary Biological Sciences, University of Alberta (1984) Research Highlights: Dr. Carbonaro's work bridges technology and education across multiple domains. Key areas include: Blended learning models Health sciences interprofessional training Indigenous education technology integration Computational thinking curriculum development He has led projects integrating robotics and digital games into school curricula, and co-developed the Aboriginal Teacher Education Program (ATEP) with Blue Quills First Nations College. Teaching & Leadership: Coordinator for the Graduate Certificate in Educational Technology Teaches courses like EDCT 400 (Lego Robotics) and EDU 210 (Technology in Education) Developed new blended delivery models university-wide Grants & Collaboration: Over $1M in funded projects, including simulation-based healthcare training and interprofessional education initiatives. Collaborations span computing science, health sciences, and Indigenous education sectors. Future Work: Focus on K-12 computational thinking integration, health sciences simulation development, and technology equity in Indigenous education contexts.

Jessica V. RichView profile

Adjunct Assistant Professor

• Postsecondary Education
• Competency-Based Education
• Assessment and Evaluation
• +4 more

Dr. Jessica V. Rich is an Adjunct Assistant Professor at Queen’s University’s Faculty of Education and a member of the Assessment and Evaluation Group (AEG). She holds a PhD in Measurement, Assessment, Policy, Leadership and Evaluation, complemented by extensive teaching qualifications in Biology, Chemistry, and Education. Her work focuses on competency-based education (CBE), programmatic assessment frameworks, and inclusive evaluation practices across postsecondary and professional education contexts. She actively contributes to the Scholarship of Teaching and Learning (SoTL) through research on feedback mechanisms and performance improvement strategies. Dr. Rich teaches courses such as PME 896 (Capstone), PME 894 (Educational Fieldwork), and GDE 828 (Program Evaluation), emphasizing practical application of assessment methodologies. She has pioneered educational development initiatives in simulated learning environments and workplace-based assessments. Her research examines the intersection between competency frameworks and real-world application, with particular attention to healthcare and engineering education reform. Current projects include evaluating transformative change models in medical education and exploring growth-oriented assessment strategies. She has collaborated with institutions to design competency frameworks for healthcare professions and contributed to knowledge translation tools for programmatic assessment implementation. Her publications span journals like Academic Medicine , Canadian Journal of Educational Administration , and Frontiers in Medicine , reflecting interdisciplinary engagement with assessment challenges in higher education. She maintains active Twitter and LinkedIn profiles to share insights on educational development and assessment innovation.

W Robert J FunnellView profile

Associate Professor

• Middle-ear mechanics
• Biomedical Modelling
• Finite Element Modeling
• +6 more

W Robert J Funnell serves as Associate Professor at McGill University with dual appointments in the Department of Biomedical Engineering and Department of Otolaryngology – Head and Neck Surgery. His research addresses critical clinical challenges in hearing loss through integrated experimental and computational methodologies, focusing on translational applications for infant diagnostics and surgical interventions. His expertise spans middle-ear mechanics, three-dimensional modeling of biological structures, and development of interactive medical education tools. Core methodologies include finite-element analysis, laser Doppler vibrometry, and haptic-enabled virtual reality systems. Current priorities involve improving newborn hearing screening accuracy, designing middle-ear repair techniques, and creating 3D anatomical models for surgical training – particularly in endoscopy simulation using force feedback technology. Analysis of his 2015-2024 publications reveals persistent innovation in finite-element modeling of auditory systems, with increasing emphasis on newborn ear mechanics and optical coherence tomography applications. His work bridges biomedical engineering, otolaryngology, and medical education, demonstrating consistent progression from fundamental biomechanics toward clinical implementation – notably in Quebec's newborn hearing screening programs and endoscopic sinus surgery training models.

Richard NaudView profile

Assistant Professor

• Computational Neuroscience
• Neural Coding
• Statistical Methods in Neuroscience
• +5 more

Richard Naud is an Assistant Professor in the Department of Cellular and Molecular Medicine at the Faculty of Medicine, University of Ottawa, with a cross-appointment in Physics at the Faculty of Science. He holds dual research positions at the Center for Neural Dynamics (CND) and Brain and Mind Research Institute (BMRI), focusing on computational approaches to decode neural signaling mechanisms and develop brain-machine interfaces. His educational background includes: PhD in Neuroscience from École Polytechnique Fédérale de Lausanne (EPFL), 2011 MSc in Physics from McGill University, 2006 BSc in Physics from McGill University, 2004 Dr. Naud's research investigates how neurons encode information through spikes, bursts, and silences using mathematical models and statistical analysis of electrophysiology data. His lab develops computational protocols for synaptic dynamics analysis, studies dendritic computation in neurological diseases, and creates neuromorphic algorithms for spiking neural networks. Current work emphasizes serotonin system dynamics, burst coding mechanisms, and neural network simulations for demyelinating conditions. Analysis of his recent publications reveals three dominant research vectors: (1) Burst coding as an independent information channel beyond firing rates, (2) Serotonin-mediated value coding in decision systems, and (3) Neuromorphic implementation of biologically plausible learning rules. His work bridges theoretical neuroscience with clinical applications in stroke recovery and neurological disorders. Dr. Naud leads the Neural Coding Lab, which actively recruits postdoctoral fellows, graduate students, and undergraduates for projects in neural coding theory, computational psychiatry, and neuromorphic engineering. The lab maintains collaborations with experimental neuroscience groups for model validation and develops open-source tools like SRPlasticity for synaptic dynamics analysis.

Yasmine AbdinView profile

Assistant Professor

• Polymer Matrix Composite Materials
• Composites Design and Manufacturing
• Structural Reliability
• +9 more

Dr. Yasmine Abdin serves as an Assistant Professor in the Department of Materials Engineering within the Faculty of Applied Science at the University of British Columbia (UBC). Her research focuses on advancing polymer matrix composite materials through innovative digital simulation and probabilistic design methodologies. Her academic credentials include: B.Sc. from KU Leuven M.Sc. from KU Leuven Ph.D. from KU Leuven Dr. Abdin's research program centers on overcoming limitations in composite material durability through probabilistic design frameworks and multi-scale modeling. She integrates finite element analysis, machine learning, and Industry 4.0 technologies to predict structural reliability under stochastic service conditions, with emphasis on damage tolerance, manufacturing-process-structure relationships, and optimization of carbon fiber production from sustainable precursors like lignin and asphaltenes. Her recent publications (2023-2025) demonstrate strong focus on sustainable composite manufacturing, including carbon fiber production from renewable resources, 4D printing of shape memory polymers, flax fiber-reinforced composites, cellulose nanofibril modification, and fatigue behavior analysis. Key thematic trends include the convergence of digital twin technologies with composite manufacturing, sustainable precursor development, and the application of machine learning to enhance modeling efficiency in structural reliability prediction. Information regarding doctoral students, research grants, laboratory facilities, or scientific awards was not provided in available sources.

Alan WassyngView profile

Professor

• Software Engineering
• Formal Methods
• Safety-Critical Systems
• +6 more

Alan Wassyng is a Professor in the Department of Computing and Software at McMaster University's Faculty of Engineering. With over four decades of academic contributions, he specializes in formal methods, safety-critical systems, and software assurance cases. Key research intersections: Automotive software safety Medical device software certification Cyber-physical systems engineering Model-driven development with domain experts His scholarly work emphasizes rigorous methodologies for software verification, particularly through tabular expressions and Workflow+ models. Recent projects include a $2M GM Canada partnership to advance automotive safety systems. Teaching leadership spans interdisciplinary capstone projects in biomedical engineering, covering software design, safety-critical development, and mechatronics applications.

Andrew SowinskiView profile

Associate Professor

• Electrostatics in fluidized beds
• Particle charging phenomena
• Reactor wall fouling mitigation
• +3 more

Andrew Sowinski serves as Associate Professor and Vice-dean of Programs at the School of Engineering Design and Teaching Innovation within the Faculty of Engineering at the University of Ottawa. Holding a Ph.D. from the University of Ottawa, his office is located in STE 1024Q with contact details including phone 613-562-5800 ext. 6288 and email sowinski@uOttawa.ca. Education: Ph.D. from University of Ottawa His research spans two primary domains: electrostatic phenomena in gas-solid systems and engineering education innovation. In electrostatics, he investigates contact electrification mechanisms in polyethylene fluidized beds, particle charging dynamics, reactor wall fouling, and pneumatic conveying systems, employing both experimental and computational (CFD) approaches. His education research focuses on developing non-traditional multidisciplinary design programs within conventional engineering faculties, addressing curriculum design, student recruitment, and assessment methodologies. Analysis of his 2021-2025 publications reveals consistent dual-focus work: electrostatics research emphasizes charge generation/mitigation in industrial polymerization processes, while education studies explore structural and implementation challenges of cross-disciplinary programs. His electrostatics work frequently combines particle-level charging experiments with system-level CFD modeling, while education publications document practical frameworks for program development amid traditional faculty structures. Scientific Awards: No scientific awards were documented in provided materials Advising and Grants: Specific details regarding graduate students, research grants, or funding sources were not disclosed in the source documentation, though his program leadership role as Vice-dean of Programs suggests significant administrative responsibilities in curriculum development and resource allocation.