جست‌وجوی استاد و پژوهشگر

Pierre Nonnonمشاهده پروفایل

استاد

• Science Education
• Technology Education
• Computer-Assisted Experimentation
• +۵ مورد دیگر

Pierre Nonnon is a Full Professor in the Department of Didactics at the Faculty of Education Sciences, University of Montreal, where he serves as head of the Educational Robotics Laboratory. His office is located at Marie-Victorin local F529, and he can be reached at pierre.nonnon@umontreal.ca or by phone at 514 343-7257. Professor Nonnon has pioneered research in Computer-Assisted Experimentation (ExAO) for over 30 years, developing foundational innovations including the 'appariteur-robot' (1973), 'cognitive lens' concept (1984), and 'Scientific Gymnasium in School' (1992). His work since 1995 focuses on reengineering science laboratories through microlaboratories implemented in secondary schools and colleges. His research spans science and technology didactics, educational robotics, experimental science instrumentation, and implementation of new science programs, emphasizing competency-based learning approaches in experimental sciences. Analysis of his 15 most recent publications (2004-2009) reveals consistent focus on portable microlaboratories, adaptive learning systems, and integration of computer-assisted experimentation in science education. His work demonstrates evolution from theoretical frameworks to practical implementations, with increasing emphasis on making science laboratories more accessible through portable, user-friendly technologies that support both teachers and students in experimental learning processes. Professor Nonnon has supervised 19 graduate students (16 Ph.D. and 3 Master's) from 1989-2016, contributing significantly to science education research. His teaching includes courses such as DID2215 Didactique de la technologie au secondaire, DID3371 Didactique des maths, des sciences et des technologies, and laboratory-focused courses in science-technology didactics. He has been instrumental in developing multiple educational programs including the Microprogramme de 1er cycle de qualification en enseignement, Baccalauréat in science and technology teaching, and Master's programs in education with options in secondary and higher education. His 2017-2020 research project 'Réalisation d'une nouvelle interface du MIcroLab ExAO' funded by Univalor demonstrates continued active research engagement.

• 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).

Ugo Piomelliمشاهده پروفایل

استاد

• Computational Fluid Dynamics
• Turbulence Modeling
• Large Eddy Simulation (LES)
• +۳ مورد دیگر

Ugo Piomelli is a Professor in the Department of Mechanical and Materials Engineering at Queen's University (since 2008). He holds the Tier I Canada Research Chair in Turbulence Simulation and Modelling (2008-2022) and previously held the HPCVL-Sun Microsystems Chair in Computational Science and Engineering (2008-2015). His academic career includes positions at the University of Maryland (Professor 2000-2008, Associate Professor 1993, Assistant Professor 1987-1993). He is a Fellow of multiple prestigious societies: Royal Society of Canada (2015), American Physical Society (2002), American Institute of Aeronautics and Astronautics (2004), American Society of Mechanical Engineers (2009), and Canadian Academy of Engineering (2021). PhD in Mechanical Engineering (Stanford University, 1988) MASc in Aerospace Engineering (University of Notre Dame, 1984) Dr. Ing. in Aerospace Engineering (Università degli Studi di Napoli, 1979) His research focuses on turbulence modeling, large eddy simulation (LES), geophysical flows, and computational fluid dynamics (CFD) with applications to rough-wall boundary layers, flow separation, and environmental/hydroelectric systems. Recent work explores resolvent-based wall models, scalar transport over rough surfaces, and unsteady boundary layer dynamics under variable freestream conditions. Scientific awards include: Fellow of the American Physical Society (2002), Associate Fellow of AIAA (2004), Fellow of ASME (2009), Fellow of the Royal Society of Canada (2015), and Fellow of the Canadian Academy of Engineering (2021). Key contributions include: 2023-2025 studies on LES wall models using resolvent analysis, roughness effects in boundary layers, and scalar transport dynamics. Earlier work (2013-2022) examines turbulence structures in dunes, rotating channel flows, and erosion-rate modeling for sediment transport. He operates the Turbulence Modelling and Simulation Laboratory, advancing numerical frameworks for complex flows and mentoring graduate students. His research has been supported by NATO-AVT349 for naval applications and collaborations in hydroelectric/hydraulic engineering.

Greg Lewisمشاهده پروفایل

استاد

• Applied Dynamical Systems
• Geophysical Fluid Dynamics
• Computational Science
• +۳ مورد دیگر

Greg Lewis is a Professor in the Faculty of Science at the University of Ontario Institute of Technology (UOIT), where he joined in 2003 as the institution's first Mathematics professor during its founding year. He led the development of UOIT's Applied Mathematics group and established the BSc program in Applied and Industrial Mathematics, alongside the MSc and PhD programs in Modelling and Computational Science. Education: PhD in Mathematics, Institute of Applied Mathematics, University of British Columbia (UBC), 2000 Postdoctoral Research, Fields Institute, Toronto His research specializes in Applied Dynamical Systems with direct applications to Geophysical Fluid Dynamics, integrating computational modeling of complex fluid phenomena in earth sciences. This work bridges theoretical dynamics with industrial mathematics through numerical simulation and real-world problem-solving frameworks. Professor Lewis has contributed significantly to academic service, including CAIMS Board of Directors (2013) and Doctoral Dissertation Award Committee (2014). He co-organized Industrial Problem Solving Workshops at the Fields Institute, fostering industry-academia collaboration in mathematical modeling.

Maral Aminpourمشاهده پروفایل

استادیار

• Computational Biology
• Drug Discovery
• Machine Learning Applications in Biomedical Engineering
• +۷ مورد دیگر

Dr. Maral Aminpour is an Assistant Professor in the Department of Biomedical Engineering at the University of Alberta , where she leads a computational lab focused on drug discovery and biological systems modeling. Her research integrates artificial intelligence and physics-based methods to study protein-protein interactions, with particular emphasis on repurposing drugs for COVID-19 and optimizing anti-tubulin cancer therapeutics . Her lab develops hybrid AI-physics software tools to advance rational drug design and has contributed to understanding ivermectin's multi-target effects, Omicron's neurovirulence, and microtubule-targeting cancer drugs. Current projects include computational approaches to PROTACs design and antiparasitic drug discovery . Teaches graduate courses in Rational Drug Design (BME 620) and Machine Learning for Biomedical Applications (BME 677) Lab website: Aminpour Lab Active research areas: Computational drug discovery , AI in biomedical engineering , Protein interaction modeling

Nasem Badreldinمشاهده پروفایل

استادیار

• Soil Science
• Remote Sensing
• Precision Agriculture
• +۵ مورد دیگر

Dr. Nasem Badreldin serves as an Assistant Professor in the Department of Soil Science within the Faculty of Agricultural and Food Sciences at the University of Manitoba. His research program develops computational technologies and data analytics to address agricultural and environmental challenges, delivering actionable insights for farmers, agribusiness, and policymakers across Canada and internationally. Education: PhD in Geography, Ghent University, Belgium MSc in Soil Science, Ghent University, Belgium BSc in Environmental Agricultural Sciences, Suez Canal University, Egypt Research Interests: Crop yield prediction using space-borne sensors Multi-scale data analysis in plant phenotyping Proximal soil sensing for conservation and crop production Landscape dynamics monitoring across spatiotemporal scales AI-driven modeling of soil physical/chemical properties Publication Trends: His 15 most recent publications (2022-2025) reveal a cohesive research trajectory centered on remote sensing and machine learning applications. Key contributions include soil organic carbon prediction using satellite fusion techniques, potato nitrogen management systems, grassland mapping in Canadian ecoregions, and erosion assessment models. His work consistently integrates multi-platform data (satellites, drones, ground sensors) to solve precision agriculture challenges with practical field applications. Scientific Awards: No awards documented in the provided text Advising and Grants: Details regarding graduate student supervision, research funding, or collaborative projects were not specified in the available documentation. Labs and Teams: No information about dedicated research laboratories, instrumentation facilities, or team structures was provided in the source materials.

Hugh Couchmanمشاهده پروفایل

استاد

• Astrophysics
• Cosmology
• Numerical Simulation
• +۳ مورد دیگر

Hugh Couchman is a Professor in the Department of Physics and Astronomy at McMaster University. A Fellow of the CIAR Cosmology Programme, his research focuses on cosmic structure formation from post-recombination era to the present, utilizing high-resolution numerical simulations across computational platforms ranging from workstations to supercomputers. Research spans scales from sub-galactic to superclusters Developed advanced numerical tools for cosmological simulations Key work on galaxy formation and early cosmic objects His computational methods research addresses the "Grand Challenges" of modeling 10 10 mass-scale differences in cosmic evolution, with particular emphasis on adaptive algorithms and parallel computing architectures. Current projects investigate the formation of the Milky Way and first-generation galaxies. Scientific Recognition CIAR Cosmology Programme Fellow

• Reinforcement Learning
• Machine Learning
• Multi-agent Systems
• +۴ مورد دیگر

Matthew Taylor is an Associate Professor of Computing Science at the University of Alberta's Faculty of Science. He directs the Intelligent Robot Learning Lab (irll.ca) and holds a Canada CIFAR AI Chair at Amii, the Alberta Machine Intelligence Institute. His research spans reinforcement learning, multi-agent systems, robotics, and human-AI interaction, with emphasis on translating academic AI into industry applications. Dr. Taylor earned his PhD in 2008 and has held roles across academia and industry. His work focuses on human-in-the-loop AI systems, reward design, and multi-agent coordination. Notable contributions include frameworks for automated warehouse layout generation, decentralized energy resource coordination, and bio-inspired prosthetic control systems. Awards include his Amii fellowship and CIFAR chair. His lab develops real-world applications in areas like flight training augmentation, smart home systems, and robotics education. Current projects emphasize robustness in noisy environments and transfer learning across domains. Key Research Areas: Reinforcement Learning, Human-AI Collaboration, Multi-Agent Systems Lab: Intelligent Robot Learning Lab Affiliations: Amii (Alberta Machine Intelligence Institute)

• Surgical Robotics
• Medical AI
• Medical Imaging
• +۳ مورد دیگر

Dr. Ali Nasseri is an Adjunct Professor in the Department of Biomedical Engineering at the University of Alberta's Faculty of Engineering. He also serves as the founding director of the Medical Autonomy and Precision Surgery (MAPS) Laboratory at the School of Medicine and Health of the Technical University of Munich. With over 15 years of experience in medical and surgical robotics, Dr. Nasseri leads research initiatives at TUM, Johns Hopkins University, and the University of Alberta, coordinating multiple large-scale collaborative projects funded by BMBF, BFS, and NIH. Dr. Nasseri's research focuses on surgical robotics, medical AI, medical imaging, medical XR, and medical autonomy. His multidisciplinary background in mechatronics, computer vision, machine intelligence, and medicine has led to a focused research program on surgical autonomy and intelligent robotic interventions. He is a pioneer in robotic eye surgery and has published more than 140 peer-reviewed articles in these fields. His recent work focuses on utilizing AI and real-time multimodal perception to implement surgical workflow autonomy—enabling robotic systems to adapt seamlessly to intraoperative complexity. His publications over the past few years demonstrate a strong trend toward increasing autonomy in ophthalmic surgery, with particular emphasis on AI-driven solutions, precision control systems, and real-time monitoring for safety. The research spans multiple subfields including retinal surgery, corneal procedures, surgical planning, and instrument tracking, with a consistent focus on improving surgical outcomes through technological innovation. best paper awards As co-founder of two medical robotics startups, Dr. Nasseri is actively engaged in translational research bridging laboratory innovation and clinical deployment. He directs the largest medical robotics project currently funded by the Bavarian Research Foundation and several industry-backed initiatives, demonstrating strong connections between academic research and industry applications. Dr. Nasseri leads the Medical Autonomy and Precision Surgery (MAPS) Laboratory at TUM, which focuses on developing intelligent robotic systems for surgical applications. The lab brings together experts from engineering, computer science, and medicine to tackle challenges in surgical robotics, with particular expertise in ophthalmic procedures.

Mostafa Nasriمشاهده پروفایل

مدرس

• Mathematical Analysis
• Operations Research
• Functional Analysis
• +۳ مورد دیگر

Mostafa Nasri serves as an Instructor in the Department of Mathematics and Statistics at the University of Winnipeg within the Mathematics and Statistics Faculty. Holding a Ph.D. from IMPA, he completed postdoctoral fellowships at Laval University, University of Montreal, and McGill University before joining his current institution. His academic credentials include: Ph.D. in Mathematics, IMPA- Instituto Nacional de Matemática Pura e Aplicada (2008) M.Sc. in Mathematics, Amirkabir University of Technology (2004) B.Sc. in Mathematics, Sharif University of Technology (2002) Dr. Nasri's research integrates Mathematical Analysis and Operations Research with specialized expertise in Functional Analysis, Optimization, and Applied Mathematics. His theoretical work examines Schauder bases, composition operators, and Dirichlet spaces, while his Optimization research develops augmented Lagrangian methods for equilibrium problems and variational inequalities. Applied contributions include contact dynamics modeling for multibody systems and HIV infection dynamics. Analysis of his 2023-2025 publications reveals intensified focus on Functional Analysis (particularly Dirichlet spaces and operator theory) alongside persistent development of optimization algorithms, with applied mechanics and mathematical biology research continuing at reduced frequency. No scientific awards are documented in available materials. Current information indicates no graduate student advising or active research grants at the University of Winnipeg. Prior industry collaboration with CM Labs Simulations Inc. and Canadian university departments demonstrates applied research experience, though no current laboratories or dedicated research teams are specified.

Bentley Oakesمشاهده پروفایل

استادیار

• Digital Twins
• Model Transformations
• Software Engineering
• +۶ مورد دیگر

Bentley Oakes is an Assistant Professor in the Department of Computer Engineering and Software Engineering at Polytechnique Montréal. He holds a Ph.D. (2018) and M.Sc. (2015) from McGill University, and a B.Sc. (2013) from the University of Manitoba. His research focuses on Digital Twins , Model Transformations , and Knowledge Representation for cyber-physical systems. Ph.D. in Computer Science, McGill University, Canada M.Sc. in Science, McGill University, Canada B.Sc. in Computer Science, University of Manitoba, Canada His work bridges Model-Driven Engineering and Artificial Intelligence to advance the rigorous development of digital twins. Key research areas include: Digital Twin Engineering : Frameworks for systematic development, reporting, and validation. Knowledge Representation : Ontologies and contracts for modeling domain expertise. Model Transformations : Symbolic execution and debugging of ATL/DSLTrans transformations. Verification : Formal methods for cyber-physical systems and co-simulations. Oakes has published extensively in MODELS , MSR , TOSEM , and SoSyM . His recent studies on rationale extraction in open-source software and DevOps approaches for built assets highlight interdisciplinary innovations. He has been recognized for Outstanding Reviewing Contributions , receiving multiple Best Reviewer Awards at leading software engineering venues. At Polytechnique Montréal, he teaches courses such as: INF6900AE : Scientific and Technical Communication I INF7900AE : Scientific and Technical Communication II LOG6953FE / LOG6310E : Digital Twin Engineering LOG8371E : Software Quality Engineering

M. Wrightمشاهده پروفایل

دانشیار

• typography
• publication design
• exhibition design
• +۸ مورد دیگر

M. Wright is an Associate Professor in Design and Computation Arts at Concordia University, specializing in typography, publication design, exhibition design, and feminist/queer histories. She co-founded the art and design collective AK/OK with Kate Jarboe, whose work has been exhibited globally and distributed by Printed Matter (NYC). Education : MFA in Visual Communication Design, School of the Art Institute of Chicago; AB in Comparative Literature, Princeton University. Her research explores intersections of design, archives, and participatory creation, with recognition from Type Directors Club, Print magazine, and AIGA 50 Books/50 Covers. Her book designs are held in permanent collections at the National Design Archives (US) and Columbia University’s Butler Library. Recent publications span diverse domains, including pediatric emergency care (neonatal resuscitation, ingested coins), trauma surgery (prehospital thoracotomy, surgical safety checklists), and developmental psychology (autism screening, theory of mind). These reflect interdisciplinary collaborations bridging design methodology with medical and social sciences. Scientific Awards : Type Directors Club recognition, Print magazine recognition, American Association of Museums recognition, New York Book Show recognition, AIGA 50 Books/50 Covers recognition. Teaching activities include graduate-level courses like DART 631/Special Topics in Visual Communication, emphasizing hands-on design thinking and social engagement. Her lab, AK/OK, focuses on archival practices and activist art through artists’ books and public interventions.

Sarah Adamowiczمشاهده پروفایل

استاد

• Biodiversity
• Evolutionary Biology
• Molecular Evolution
• +۴ مورد دیگر

Sarah Adamowicz is a Professor at the University of Guelph's Department of Integrative Biology within the College of Biological Science. Her research focuses on biodiversity, evolutionary biology, and molecular evolution, particularly in Arctic ecosystems and aquatic invertebrates. She leads initiatives in DNA barcoding, macroevolutionary studies, and ecological assessments using genomic tools. Her work integrates DNA sequence data, fossil records, and comparative analyses to explore species diversity patterns and evolutionary processes. Key projects include the Barcode of Life campaign, habitat restoration research, and developing bioinformatics tools like Debar and CanFlyet. Dr. Adamowicz’s publications span molecular evolution rates, phylogenetic reconstruction, and ecological impact studies in boreal and Arctic regions. She collaborates extensively on northern biodiversity projects, such as the Churchill Diptera barcode library and assessments of peat-based soil recovery in industrial sites. Her lab (SSC 2409/10) supports interdisciplinary research, combining fieldwork with computational methods. Current and future work emphasizes leveraging genomic data for conservation, understanding latitudinal biodiversity gradients, and advancing metagenomic techniques for ecological monitoring.

Mustapha CE Yagoubمشاهده پروفایل

استاد

• RF/Microwave CAD
• RFID Design
• Neural networks for high-frequency applications
• +۲ مورد دیگر

Mustapha CE Yagoub serves as a Professor in the School of Electrical Engineering and Computer Science at the University of Ottawa, where he has maintained an active academic position since joining in 2001. His professional background spans both industry and academia across three continents, with significant contributions to microwave engineering and RF circuit design. His research interests focus on RF/Microwave CAD, RFID Design, Neural networks for high-frequency applications, Planar antennas, and Applied electromagnetism. This specialization is reflected in his extensive publication record of over 300 journal and conference papers, along with two books including 'Conception de circuits linéaires et non linéaires micro-ondes' (2000) and 'Computer Manipulation and Stock Price Trend Analysis' (2005). His recent work demonstrates strong continuity in microwave circuit analysis, RFID applications, and neural network implementations for high-frequency systems, with particular emphasis on practical engineering solutions for wireless communications and sensor networks. As an educator, Professor Yagoub teaches undergraduate courses including Circuit Theory I (ELG 2538) and Electronics for Mechanical Engineers (ELG 3736), along with graduate-level Nonlinear Microwave Devices (ELG 6369). He actively supervises fourth-year undergraduate projects and graduate research in his specialty areas. Professor Yagoub maintains active professional standing as a Senior Member of the IEEE Microwave Theory and Techniques Society, a member of the Professional Engineers of Ontario (Canada), and a member of the Ordre des ingénieurs du Québec (Canada). His international academic journey began with engineering education at École nationale polytechnique in Algiers, continued with doctoral studies in Toulouse, France, and included academic positions at Houari Boumediene University of Science and Technology in Algiers before his current appointment at uOttawa.

Dirk Rodenburgمشاهده پروفایل

استادیار مدعو

• Human Computer Interaction
• Ethics in Technology
• Sensory Processes and Performance
• +۳ مورد دیگر

Dr. Dirk Rodenburg is an Adjunct Assistant Professor at Queen's University's Dan School of Drama and Music within the Faculty of Arts and Science. He holds cross appointments as an Educational Consultant in the Schools of Medicine and Rehabilitation Therapy (Faculty of Health Sciences) and as a Term Adjunct Professor in the Department of Chemical Engineering (Faculty of Engineering). His research focuses on human performance, real-time data analytics, ethics in technology, and wearable technology applications in healthcare and education. Education: B.A. Psychology, Queen's University M.A. Adult Education, University of British Columbia Ph.D. Faculty of Information, University of Toronto Research interests span human-computer interaction, cognitive load measurement, adaptive simulation systems, and neurotechnology ethics. He has pioneered work in wearable-based emotion recognition, stress detection using ECG, and ethical guidelines for brainwave technologies. Professional roles include Board Member of the Centre for Responsible Brainwave Technologies (CeReB), Associate Editor for International Journal of Sport and Society , and Section Editor for Technology Source . His work bridges academia and industry through 20+ years as a software entrepreneur in educational tech and biotechnology. Grants & Labs: His cross-disciplinary focus integrates engineering, medicine, and arts through collaborative research initiatives in adaptive training systems and ethics frameworks for emerging technologies.