جست‌وجوی استاد و پژوهشگر

• Inverse Problems
• Partial Differential Equations
• Mathematical Physics
• +۳ مورد دیگر

Ali Feizmohammadi is an Assistant Professor, Teaching Stream (LTA) in the Department of Mathematics at the University of Toronto Mississauga, affiliated with the Mathematical and Computational Sciences division. His research focuses on inverse problems, partial differential equations, and geometric analysis. He holds a position emphasizing teaching excellence within the university's framework. His work addresses advanced mathematical challenges such as coefficient identification in subdiffusion equations, fractional Laplacian problems on Riemannian manifolds, and nonlinear elliptic equations on manifolds. Recent articles highlight contributions to the Calderón problem in various contexts, wave equation control, and spacetime finite element methods. No scientific awards or grants are explicitly listed in the provided information. He has not yet listed advisees in the available data. His research trends emphasize rigorous mathematical analysis of inverse problems in both classical and fractional PDE frameworks, with applications to geometric and control-theoretic questions. Dr. Feizmohammadi's work spans theoretical advancements in inverse problems, numerical methods for control systems, and the interplay between differential geometry and PDEs. His contributions address both fundamental theory and applied methodologies in mathematical physics and engineering.

Joshua Brinkerhoffمشاهده پروفایل

دانشیار

• Computational Fluid Dynamics
• Turbomachinery
• Multiphase Turbulent Flows
• +۷ مورد دیگر

Dr. Joshua Brinkerhoff is an Associate Professor in Mechanical Engineering at the University of British Columbia Okanagan Campus. He serves as the Associate Director for Research & Industrial Partnerships in the School of Engineering and leads the UBC-Okanagan Computational Fluid Dynamics Laboratory. His research spans computational fluid dynamics, turbomachinery, multiphase flows, hydrogen safety, wind energy, and biofluid mechanics. He teaches courses in mechanics of materials, alternative energy systems, turbulence, computational fluid dynamics, and aircraft design. PhD, Aerospace Engineering (Carleton University, Ottawa, ON) BEng, Aerospace Engineering (Carleton University) Dr. Brinkerhoff’s research interests include: Computational Fluid Dynamics (CFD) for laminar-to-turbulent transition and instability analysis Wind energy systems and turbine aerodynamics Hydrogen storage and safety protocols for transportation Biofluid mechanics for respiratory diseases and aneurysm modeling Multiphase flows in industrial and environmental contexts His publications focus on CFD simulations for: Aerosol dispersion and mitigation in indoor environments Wind farm interactions and atmospheric gravity waves Cavitation and phase transitions in cryogenic and LNG systems Heat transfer optimization in industrial and thermal systems Instability dynamics in buoyancy-driven and swept flows Turbulent structures in fluidized beds and reactors Dr. Brinkerhoff has no listed scientific awards in the provided data but has extensive contributions to renewable energy, hydrogen safety, and medical fluid dynamics. His laboratory develops open-source tools like TOSCA for large-eddy simulations and investigates practical applications in urban air quality, dental aerosol control, and turbine wake modeling.

Alireza Yaseriمشاهده پروفایل

استادیار مدعو

• Geotechnical Engineering
• Geomechanics
• Earthquake Engineering
• +۴ مورد دیگر

Alireza Yaseri serves as an Adjunct Assistant Professor in the Department of Civil Engineering within Smith Engineering at Queen's University. He maintains a dual affiliation with the GeoEngineering Centre, a leading research institute at Queen's specializing in geotechnical and geoenvironmental challenges, where he contributes to advanced computational modeling initiatives. Education: PhD in Geotechnical Engineering, Université Laval (2021) MSc in Geotechnical Engineering, Shiraz University (2012) Dr. Yaseri's research program centers on computational geomechanics with emphases on seismic soil-structure interaction, railway-induced vibrations, and constitutive modeling of granular materials. His work bridges theoretical mechanics and practical infrastructure challenges through advanced numerical techniques, particularly hybrid FEM-SBFEM implementations for dynamic analysis of earth dams, canyon systems, and transportation corridors. He investigates nonlinear soil behavior under monotonic/cyclic loading and develops predictive models for vibration propagation in complex geological settings. Analysis of his publication trajectory (2014-2024) reveals consistent innovation in computational geotechnics, with recent work focusing on 2.5D/3D modeling of train-induced vibrations and sophisticated sand constitutive frameworks. His 2024 publications demonstrate dual expertise in railway vibration prediction methodologies and critical-state soil mechanics, while his earth dam-canyon system analyses from 2020-2022 established foundational approaches for seismic amplification in flexible geological formations. As an active member of Queen's GeoEngineering Centre, Dr. Yaseri collaborates on interdisciplinary projects addressing infrastructure resilience, with particular relevance to dam safety and transportation geotechnics in seismic zones. His technical leadership in scaled boundary methods contributes to the center's reputation for computational innovation in geomechanics.

• Mathematical Physiology
• Dynamical Systems
• Mathematical Modeling
• +۳ مورد دیگر

Gerda de Vries is a Professor in the Department of Mathematics & Statistical Sciences at the University of Alberta, Faculty of Science. Her research focuses on mathematical physiology, dynamical systems, and mathematical modeling, particularly in cellular biophysics, pattern formation, and systems biology. She has contributed extensively to understanding complex biological systems through interdisciplinary approaches combining mathematics and biology. Her work spans applications in radiation biology (e.g., cell cycle dynamics and low-dose radiation effects), biophysics (microtubule organization, motor proteins), ecology (predator-prey interactions, forest fire modeling), and education (adapting primary literature for STEM teaching). Recent research highlights include analyzing saddle-node bifurcations, bystander effects in radiation, and collective behavior in animal groups. De Vries has published over 50 peer-reviewed articles since 2000, with a focus on bridging abstract mathematical theory to concrete biological phenomena. Notable contributions include models of pancreatic β-cell dynamics, immune system versatility, and educational frameworks for mathematical biology. Her academic career includes leadership in curriculum development and interdisciplinary research, though no specific grants or awards are explicitly listed in the provided information.

Carl Tropperمشاهده پروفایل

استاد

• Parallel Simulation
• Distributed Systems
• VLSI Circuit Simulation
• +۲ مورد دیگر

Carl Tropper is Professor Emeritus of Computer Science at McGill University, specializing in parallel discrete-event simulation. His research develops synchronization algorithms for large-scale systems including VLSI circuits, gravitational N-body simulations, and neuronal reaction-diffusion models. Education: BSc, McGill University PhD, Polytechnic Institute of New York Professional Experience: Former positions at Boeing, MITRE, and Caltech's Jet Propulsion Laboratory

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.

David Del Rey Fernándezمشاهده پروفایل

استادیار

• Numerical Simulation of PDEs
• Summation-by-Parts Methods
• Continuous and Discontinuous Galerkin Schemes
• +۲ مورد دیگر

David Del Rey Fernández is Assistant Professor and Pratt & Whitney Canada Chair in Industrial Artificial Intelligence in the Department of Applied Mathematics at University of Waterloo. His research develops efficient numerical algorithms for solving partial differential equations on high-performance systems. He holds a PhD from University of Toronto and previously worked at NASA Langley Research Center. Research focuses on robust numerical methods, mesh adaptation, and machine learning acceleration. His work includes entropy-stable schemes, summation-by-parts methods, and discretizations for compressible flows. Recent publications address Lyapunov-consistent discretizations and scalable reduced-order modeling.

David Lozinskiمشاهده پروفایل

دانشیار

• Combustion Science
• Fluid Dynamics
• Financial Mathematics
• +۳ مورد دیگر

David Lozinski is an Associate Professor in the Department of Mathematics and Statistics at McMaster University, Faculty of Science. His research spans combustion science, fluid dynamics, and financial mathematics. He has published extensively on topics like smoldering combustion, flame stability, and quantitative risk modeling. Teaching responsibilities include courses on risk management, actuarial mathematics, financial markets, and applied statistics. Research interests combine theoretical and applied mathematics with practical applications in combustion engineering and financial systems. Key contributions include studies on reverse smoldering mechanisms (1995), vapor diffusion flames (1995), and modern financial risk models (2024). Teaching spans undergraduate and graduate programs, covering mathematical finance, probability, and statistical inference. No scientific awards are listed in the profile. Active in curriculum development for financial mathematics programs, instructing courses like MFM 714 (Risk Management) since 2025 and STATS 3G03 (Actuarial Mathematics I) since 2024.

Jianbing (Jason) Liمشاهده پروفایل

استاد

• Environmental pollution control
• Petroleum waste management
• Soil and groundwater remediation
• +۳ مورد دیگر

Dr. Jianbing Li is a Professor and Professional Engineer (P.Eng.) in the Environmental Engineering Program at the University of Northern British Columbia (UNBC), holding prestigious fellowships from CSCE, CSSE, EIC, and Engineers Canada. His research program addresses critical environmental challenges with significant real-world impact, particularly in northern and remote communities of British Columbia. Education: PhD in Environmental Systems Engineering, University of Regina Research Focus: Dr. Li's work centers on environmental pollution control , petroleum waste management , soil and groundwater remediation , environmental modeling , risk assessment , and oil spill response . His innovative approaches integrate machine learning, advanced materials, and sustainable engineering principles to develop practical solutions for complex environmental problems, with particular emphasis on resource recovery from waste streams. Publication Trends: Analysis of his 15 most recent publications (2023-2025) reveals a strategic focus on oil spill response technologies, wastewater treatment innovations, and waste valorization. Key advancements include nano/micro bubble flotation systems, chitosan-based adsorbents, and machine learning models for pyrolysis optimization, demonstrating his leadership in translating laboratory research to field applications. Scientific Recognition: 2024 Fellow of Engineers Canada and Engineering Institute of Canada 2023 CSCE Dr. Albert E. Berry Medal (Canada's top environmental engineering award) Multiple UNBC Research Excellence Awards (2010, 2014, 2019, 2023) 2013 Northern BC Business and Technology Award with Husky Energy Best paper awards from International Academy of Science and Environmental Geotechnology Society Research Leadership: Dr. Li has secured over $800,000 in 2023 and $1.9 million in 2020 for oil spill response research through NSERC, DFO, and NRCan. His current portfolio includes groundwater protection for Indigenous communities, next-generation decanting technologies, and water security for remote regions. He actively mentors PhD, MSc, and MASc students while serving on NSERC evaluation committees and co-directing the UNBC/UBC environmental engineering program (2013-2017). Collaborative Networks: Dr. Li leads multi-institutional partnerships with UBC, government agencies, industry (including Husky Energy), and Indigenous communities like Lheidli T'enneh First Nation. His work through the Multi-Partner Research Initiative addresses practical challenges in rural British Columbia while advancing fundamental knowledge in environmental systems engineering.

David Ardiaمشاهده پروفایل

استاد

• Quantitative risk management
• Quantitative Asset Management
• Sentometrics
• +۷ مورد دیگر

David Ardia is a Full Professor in the Department of Decision Sciences at HEC Montréal, promoted to this position on June 1, 2025. Previously, he served as an Associate Professor from June 2020 to May 2025. He holds the Research Professorship in Sentometry and is a member of the Study and Research Group on Decision Analysis (GERAD) and the International Statistical Institute. Ardia is also an elected member of the ISI Louis Bachelier Fellow and serves as Associate Editor for both the International Journal of Forecasting and the Journal of Statistical Software. His educational background includes a Ph.D. in Financial Econometrics from the University of Fribourg, a Master of Applied Sciences in Quantitative Finance from the Swiss Federal Institute of Technology Zurich and University of Zurich, and a Master of Science in Financial Engineering from the University of Neuchâtel. Ardia's research focuses on the intersection of quantitative finance, machine learning, and natural language processing, with particular emphasis on sentometrics (textual sentiment analysis in finance), risk management, and climate finance. His work spans financial econometrics, volatility modeling, and the application of advanced statistical methods to asset allocation and economic forecasting. He has pioneered methods for analyzing climate change concerns in financial markets and has made significant contributions to understanding green versus brown stock performance. His publication record shows a strong trajectory in high-impact finance and statistics journals, with recent work examining Robinhood trading patterns, cryptocurrency markets, climate finance, and innovative methodological approaches to financial time series analysis. His research demonstrates increasing focus on sustainability applications within quantitative finance. Prix de la qualité des données ouvertes 2024 (Canadian Open Data Community) Prix de recherche pour les professeures et professeurs agrégés (HEC Montréal, 2024) Prix pour l'excellence en pédagogie (HEC Montréal, 2022) Best Paper Award at the 38th International Conference of the French Finance Association Best Paper Award 2018-2019 from International Journal of Forecasting eRum 2020 COVID19 contest winner for the COVID-19 Data Hub Ardia actively supervises numerous graduate students, with over 70 mentorship activities documented in the past five years, spanning both thesis supervision and supervised projects. His research is supported by collaborations with institutions including IVADO, the R Consortium, and the University of Lugano. He co-created the influential COVID-19 Data Hub platform, which integrates epidemiological data with policy measures and spatial databases to analyze pandemic impacts. His research group focuses on developing computational tools for financial analysis, particularly through R packages like MSGARCH for Markov-switching GARCH models and sentometrics for textual sentiment analysis. This work bridges academic research with practical applications in financial institutions and policy analysis.

Bing Hanمشاهده پروفایل

استاد

• Asset Pricing
• Behavioral Finance
• Investments
• +۲ مورد دیگر

Bing Han is a Professor of Finance and the TMX Chair in Capital Markets at the Joseph L. Rotman School of Management, University of Toronto. He holds a PhD in Finance from UCLA and a PhD in Mathematics from the University of Chicago. Research Interests : Behavioral Finance, Asset Pricing, Investment Strategies, Risk Management, and Real Estate Finance. His work bridges mathematical rigor with empirical finance, focusing on market anomalies, investor sentiment, and liquidity dynamics. Publication Trends : His recent work explores option pricing discrepancies, social transmission of consumption beliefs, and cross-border information flows. Articles highlight applications of behavioral biases, volatility modeling, and macroeconomic forecasting using financial instruments. Scientific Awards & Honors : Lifetime Achievement Award (2021) Outstanding Paper Award (2018) Best Paper Award (2016) Outstanding Paper in Asset Pricing Research (2013) CBA Foundation Research Excellence Award (2010) Advising & Grants : Available for Masters/PhD supervision and industry projects. Secured sponsored research funding on Sentiment Risk and Hedge Fund Returns (2016-2017). Previously taught at University of Chicago, Ohio State, and University of Texas at Austin.

Brandon Karchewskiمشاهده پروفایل

استاد آموزشی

• Computational Geoscience
• Engineering Geology
• Natural Hazards
• +۲ مورد دیگر

Brandon Karchewski is an Associate Head (Undergraduate) and Teaching Professor in the Department of Earth, Energy and Environment at the University of Calgary. He earned his PhD in Civil Engineering from McMaster University and teaches courses including Engineering Geology, Computational Methods, and Natural Disasters. His research program focuses on: Computational methods in geophysics and geomechanics Geoscience education innovation Climate change impacts on frozen soils Inverse modeling applications Karchewski has pioneered virtual field experiences and developed open-source tools for modeling climate impacts on permafrost. His educational research examines metaphor use in geoscience communication and field pedagogy. Recent computational work includes Python-based permafrost modeling and stochastic inversion methods for biogeochemical transport. He leads the geophysics field school program emphasizing team-based learning. Award recognition includes: Geoscience Teaching Award (2019) Best Poster Award for teaching innovation research (2018) Team Teaching Excellence award (2016) Multiple teaching assistant awards

M Reza Kholghyمشاهده پروفایل

دانشیار

• Industrial Decarbonization
• Hydrogen Production
• Carbon Dioxide Conversion
• +۷ مورد دیگر

Dr. M Reza Kholghy is an Associate Professor and Canada Research Chair in Particle Technology and Combustion Engineering at Carleton University's Department of Mechanical and Aerospace Engineering. He directs the Energy and Particle Technology Laboratory (EPTL) where he focuses on sustainable industrial solutions. His academic credentials include a BASc in Aerospace Engineering from Sharif University of Technology, and MASc/PhD degrees in Mechanical Engineering from the University of Toronto, followed by postdoctoral work at ETH Zurich. Research interests center on: Industrial decarbonization through metal fuel combustion (aluminum/iron) and carbon management Hydrogen production via methane pyrolysis and metal-water reactions Advanced material synthesis including flame spray pyrolysis for catalytic films and alumina production Nanoparticle engineering with focus on soot formation dynamics and optical properties His publications predominantly explore nanoparticle synthesis mechanisms, soot formation modeling, and sustainable fuel technologies, with recent emphasis on hydrogen cogeneration and metal combustion. Experimental and computational approaches are equally represented across combustion diagnostics, reactor design, and molecular dynamics simulations. Major scientific recognitions include: Canada Research Chair (Tier 2) Vanier Canada Graduate Scholarship NSERC Postdoctoral Fellowship He leads the Energy and Particle Technology Laboratory with industry partnerships focused on sustainable technology development. The lab specializes in flame spray pyrolysis reactors, nanoparticle characterization (surface area, porosity, composition), and high-pressure reaction systems. Dr. Kholghy actively mentors students through capstone projects and research positions, though specific PhD/Master's advisees aren't named in available sources.

George Psofogiannakisمشاهده پروفایل

استادیار

• Fuel Cells
• Redox Flow Batteries
• Density Functional Theory
• +۳ مورد دیگر

George Psofogiannakis is an Assistant Professor in the Department of Chemical and Biological Engineering at the University of Ottawa's Faculty of Engineering. His research integrates computational modeling with energy storage and conversion systems, focusing on advanced materials for sustainable technologies. His academic credentials include: Ph.D. in Chemical Engineering, University of Ottawa (2007) M.A.Sc. in Chemical Engineering, University of Ottawa B.A.Sc. in Chemical Engineering, University of Toronto Professor Psofogiannakis' research spans computational materials science and chemical engineering , specializing in fuel cells , redox flow batteries , and gas storage materials . He employs advanced simulation techniques including Density Functional Theory (DFT) , Reactive Molecular Dynamics (ReaxFF) , and Computational Fluid Dynamics (CFD) to investigate reaction mechanisms and material properties at atomic scales. His work bridges theoretical modeling with practical energy applications, particularly in hydrogen storage and catalytic processes. Recent publications (2021-2024) reveal a dominant focus on two-dimensional carbon materials (carbophenes) for gas adsorption, with significant contributions to understanding functionalization effects, mechanical properties, and band-gap engineering. His research consistently applies DFTB and ReaxFF methodologies to solve complex problems in energy materials. Professional recognition includes: Marie-Curie Fellowship (2008-2013) He teaches core Chemical Engineering courses including Catalysis by Metals and Zeolites, Electrochemical Processes, and Computational Methods. His research group develops computational frameworks for next-generation energy materials, with ongoing projects in battery systems and catalytic converters. Future work emphasizes predictive modeling of material degradation and optimization of adsorption mechanisms for industrial-scale gas storage. Professor Psofogiannakis leads a computational laboratory focused on atomic-scale simulation of energy materials, collaborating with experimental groups to validate theoretical predictions and accelerate materials discovery.

Wang-Hung Tseمشاهده پروفایل

پژوهشگر

• Applied Mathematics
• Pattern Formation
• Computational Biology
• +۳ مورد دیگر

Dr. Wang-Hung Tse is a researcher and faculty member in the Department of Mathematics at Trinity Western University (TWU), affiliated with the Faculty of Natural & Applied Sciences. He holds a PhD from the University of British Columbia (2016) and an MPhil from The Chinese University of Hong Kong (2009). His primary research focuses on pattern formation in biological systems, nonlinear dynamics, and the integration of machine learning with experimental data analysis. He has contributed to studies on crime hotspot dynamics, biological morphogenesis, and satellite data assimilation. Dr. Tse has taught courses including Differential Equations (MATH 321), Calculus III (MATH 223), and Business Mathematics (MATH 101). His interdisciplinary research emphasizes reproducible outcomes and involves agent-based modeling, computational simulations, and mathematical analysis of complex systems. Recent work includes collaborations on sea surface temperature modeling and crime pattern stability. His research methodologies span applied mathematical analysis of singularly perturbed systems, numerical bifurcation methods, and high-performance computing for large-scale simulations. Key contributions include studies on localized stripe stability in reaction-diffusion systems and the interplay between Gaussian curvature and pattern formation on Riemannian manifolds.