جست‌وجوی استاد و پژوهشگر

Lyndia Wuمشاهده پروفایل

استادیار

• Biomechanical engineering
• Biomedical instrumentation
• Biomedical signal processing
• +۱۱ مورد دیگر

Lyndia Wu is an Assistant Professor in the Department of Mechanical Engineering at the University of British Columbia's Faculty of Applied Science, where she holds the prestigious Canada Research Chair in Wearable Brain Injury Sensing. She leads the SimPL (Sensing in Biomechanical Processes Lab) and maintains an active research program focused on biomechanics and medical device development. Her educational background includes: B.A.Sc. from the University of Toronto M.S. from Stanford University Ph.D. from Stanford University Postdoctoral Fellowship from Stanford University Dr. Wu's research program centers on developing novel sensing and data analytics technologies to study human biomechanics in health and disease states. Her primary research areas encompass brain injury or concussion biomechanics using advanced sensing, modeling, and machine learning approaches, as well as the development of innovative sensors and algorithms for studying sleep disorders like obstructive sleep apnea. She specializes in wearable sensors for brain health monitoring, traumatic brain injury mechanisms, and AI applications in healthcare settings. Analysis of her recent publications reveals a strong focus on sports-related head impacts (particularly in soccer), EEG monitoring following impacts, and sleep monitoring after concussions. Her work demonstrates interdisciplinary collaboration across biomechanical engineering, neuroscience, and clinical medicine, with publications spanning biomechanics, neurotrauma, biomedical instrumentation, and signal processing domains. Dr. Wu has received significant recognition for her work, including: Scholar Award from the Michael Smith Foundation for Health Research (2019) Junior Faculty Teaching Award from UBC Mechanical Engineering (2022) She actively supervises graduate students in Mechanical Engineering programs (MASc and PhD) and collaborates extensively across disciplines. Dr. Wu is affiliated with multiple research centers including the Institute for Computing, Information and Cognitive Systems (ICICS), Origins of Balance Deficits and Falls, and SmarT Innovations for Technology Connected Health (STITCH), reflecting her interdisciplinary approach to solving complex biomedical challenges. As director of the SimPL lab, she leads a research team developing cutting-edge sensing solutions for biomechanical processes with particular emphasis on brain injury prevention, monitoring, and recovery assessment through innovative engineering approaches.

Bern Kleinمشاهده پروفایل

استاد

• Mineral Processing
• Comminution
• Sensor-Based Ore Sorting
• +۳ مورد دیگر

Bern Klein is a Professor at the University of British Columbia's Faculty of Applied Science, specifically within the Norman B. Keevil Institute of Mining Engineering. His career spans over three decades, beginning with extensive industry experience from 1990 to 1998, followed by his academic role at UBC since 1997. He has held leadership positions including Graduate Advisor (1999-2008) and Department Head (2008-2014), and has been instrumental in establishing research centers like the Centre for Industrial Minerals Innovations and the Canadian International Resources and Development Institute. Education: PhD in Mineral Process Engineering, University of British Columbia (1992) BASc in Mining and Mineral Process Engineering, University of British Columbia (1985) Research Interests: Professor Klein's research is centered on mineral processing technologies , with a strong emphasis on energy efficiency and environmental sustainability in mining operations. His work encompasses: Comminution processes and energy optimization Rheology of mineral suspensions Sensor-based ore sorting technologies Water and energy conservation in mining Development of innovative mineral processing flowsheets His research has led to the creation of Mine Sense Technologies Ltd , a startup company that has developed novel sensor-based sorting systems for the mining industry. Scientific Awards: Institute of Mining and Metallurgy Transactions Best Paper Award (2008) Canadian Institute of Mining Distinguished Lecturer Award (2011) CEEC Medal for Best Paper (2013, 2016) CEEC Honorable Mention for Best Paper (2022) Mitacs Award for Exceptional Leadership for a Professor (2023) Teaching and Supervision: Professor Klein teaches courses including MINE 201 Mineral Resources Engineering II , MINE 434/524 Processing of Precious Metal Ores , MINE 508 Integrated Mining and Processing Systems , and MINE 579 Rheology of Mineral Suspensions . He has supervised numerous graduate students, with Uuganbadrakh Oyunkhishig being one of his Master's students. Research Teams and Labs: His research involves interdisciplinary collaboration, particularly through the Quantum Matter Institute and the Centre for Industrial Minerals Innovations. He is open to collaborations with undergraduate students and other researchers, fostering a collaborative research environment.

• Software Engineering
• Model-Driven Engineering
• Automotive Embedded Systems
• +۳ مورد دیگر

Vera Pantelic is an Adjunct Assistant Professor in the Department of Computing and Software at McMaster University. Her research focuses on software engineering practices for model-based development in automotive systems, particularly centralized Electrical/Electronic (E/E) architectures, Simulink modeling, and supervisory control of probabilistic discrete event systems. Education: Not explicitly mentioned in the text. Her scholarly activity includes extensive contributions to conferences and journals in automotive software engineering, model transformation, and real-time systems. Her work addresses challenges in modularity, documentation, and compliance within automotive embedded systems. Her recent publications emphasize advancements in centralized E/E architectures, model-driven testing, and assurance cases for automotive safety. She collaborates on topics integrating software engineering principles with automotive domain requirements. Scientific Awards: No specific awards mentioned in the text. She serves as an advisor in software engineering, though specific student names are not listed. Her projects involve simulation-based testing, model refactoring, and compliance frameworks, supported by industry partnerships and academic grants. Her work contributes to labs and teams focused on automotive software reliability and model-driven engineering. No explicit lab or team affiliations are detailed in the provided text.

Reza Samaviمشاهده پروفایل

دانشیار

• Information Security
• Machine Learning
• Trustworthy AI
• +۵ مورد دیگر

Dr. Reza Samavi is an Associate Professor at Toronto Metropolitan University's Department of Electrical, Computer, and Biomedical Engineering, Faculty of Engineering & Architectural Science. He is also a Faculty Affiliate with the Vector Institute for Artificial Intelligence and directs the Trustworthy AI Research Lab (TAILab). Previously, he served as Assistant Professor and eHealth Graduate Program Coordinator at McMaster University's Department of Computing and Software (2014-2020). Holding a PhD in Computer Science (University of Toronto, 2013), his academic journey bridges industry experience with rigorous scholarly contributions. His research lies at the critical intersection of Trustworthy AI , Machine Learning Security , and Medical Informatics . He investigates Safety & Security of ML Algorithms Privacy-Preserving AI Systems Transparency Frameworks for Medical AI Blockchain-enabled Privacy Auditing Game Theory for Model Robustness Optimization-based Anonymization Techniques The TAILab research group under his leadership has produced groundbreaking work in Uncertainty Quantification for Neural Networks Robustness Against Adversarial Attacks Medical Image Analysis Clinical Decision Support Systems Emergency Medicine Predictive Modeling His recent projects focus on enhancing migrant youth mental health through LLM-based conversation agents and developing certified robustness guarantees for ensemble networks. Dr. Samavi's scholarly excellence is recognized through Privacy Technologies Research Award (IBM) Privacy By Design Research Award (Ontario IPC) Bridging Divides Emerging Research Grant (TMU) NSERC PGS-D Recipient (Co-supervised student) SOSCIP Accelerator Grant He has secured major funding from NSERC , SOSCIP , MITACS , HHS , and IDEaS programs. As a dedicated educator, Dr. Samavi teaches graduate courses in Secure Machine Learning and Software Testing while mentoring 15+ graduate students across PhD , MASc , and MEng programs. His lab has presented at premier venues including AAAI , IJCAI , and IEEE Transactions while maintaining active collaborations with institutions like Harvard, ETH Zurich, and the University of Waterloo.

Tim J. Nyeمشاهده پروفایل

دانشیار

• Advanced Manufacturing
• Operations Research
• Process Modelling
• +۴ مورد دیگر

Tim J. Nye is an Associate Professor in the Department of Mechanical Engineering at McMaster University's Faculty of Engineering. He holds a Ph.D. in Mechanical Engineering (1997) from the University of Waterloo, following an M.Sc. (1989) at Ohio State and B.A.Sc. (1987) at Waterloo. His research focuses on applying operations research techniques to manufacturing systems, with specific expertise in optimization algorithms for sheet metal processes, hydroforming reliability, and adaptive control in forging. Education: Ph.D. Mechanical Engineering, University of Waterloo (1997) M.Sc. Mechanical Engineering, Ohio State (1989) B.A.Sc. Mechanical Engineering, University of Waterloo (1987) Research interests span multiple dimensions of advanced manufacturing: developing decision models for production investment, creating novel lot-sizing algorithms incorporating work-in-process costs, exact solutions for 2D nesting problems, and agent-based systems for reliability prediction using warranty data. His work bridges theoretical operations research with practical metal forming applications. Recent publications demonstrate consistent contributions to manufacturing optimization, with particular focus on stamping processes, sheet metal design, and hydroforming reliability. These align with McMaster's research clusters in Advanced Materials & Manufacturing and Infrastructure. Scientific awards include the 2002 CSME Best Student Paper competition win for machine vision research with S. Dworkin. He maintains active collaborations with industry partners, as evidenced by his research on industry-university R&D ventures. Current projects explore intelligent open die forging as a solid freeform fabrication method, demonstrating his commitment to both traditional manufacturing improvement and emerging rapid prototyping technologies.

Luis A. Ricardez-Sandovalمشاهده پروفایل

دانشیار

• Process Systems Engineering
• Multiscale Modelling
• Computer-aided Catalyst and Materials Design
• +۷ مورد دیگر

Luis A. Ricardez-Sandoval is an Associate Professor in the Department of Chemical Engineering at the University of Waterloo and holds a Tier II Canada Research Chair in Multiscale Modelling and Process Systems. His research group develops advanced computational tools for optimizing chemical processes across multiple scales. Doctorate: Chemical Engineering, University of Waterloo (2008) MASc: Chemical Engineering, Instituto Tecnologico de Celaya (2000) BASc: Chemical Engineering, Instituto Tecnologico de Orizaba (1997) The research group focuses on multiscale modelling and process systems engineering , particularly for CO2 capture , energy systems , and heterogeneous catalysis . Their work combines advanced mathematics, machine learning , and uncertainty analysis to optimize chemical processes before physical implementation. Recent publications emphasize dynamic system optimization under uncertainty, multiscale simulation , and CO2 conversion technologies . Key methodologies include probabilistic uncertainty quantification and economic predictive control . Scientific Awards : 1997: First Place, XII National Creativity Contest 1998: Best Student Award, Instituto Tecnologico de Orizaba 1999: Third Place, XIV National Creativity Contest 2000: J.M. Smith Award for Best MASc Student He has collaborated with international institutions like CONACyT-Mexico, China Scholarship Council, and Universidad de Los Andes. His teaching includes graduate courses in process control, optimization, and computer-aided design.

Elif Bilgicمشاهده پروفایل

استادیار

• Performance Assessment in Medical Education
• Simulation-Based Medical Education
• Artificial Intelligence in Health Sciences Education
• +۲ مورد دیگر

Elif Bilgic is an Assistant Professor and Education Scientist at McMaster University's Department of Pediatrics. Her research program focuses on performance assessment across medical specialties, with an emphasis on optimizing clinical and simulation-based evaluations through technological innovation, interdisciplinary collaboration, and competency-based frameworks. McMaster University, Department of Pediatrics (2025-present) McGill University, Department of Surgery (2018-2025) Research Interests span performance assessment in surgical and pediatric education, virtual reality simulations, and artificial intelligence applications in health sciences training. She investigates: Valid assessment tools for laparoscopic suturing and endoscopic procedures Extended reality (XR) adoption in Canadian medical simulation centers Emotional impacts of competency assessment mandates on trainees and faculty Interdisciplinary AI integration in surgical education Educational analytics for skill acquisition tracking Teaching includes modules like The Fundamentals of Skill Acquisition (HSEDUC 704) and Program Evaluation in Health Sciences Education (HSEDUC 710). Her 2025 publications highlight advancements in simulation platforms for pediatric acute care, AI implications in surgical training, and emotional analysis of assessment systems.

Shakhawat Hossainمشاهده پروفایل

استاد

• Statistical Methodology
• Longitudinal Data Analysis
• Survival Analysis
• +۴ مورد دیگر

Dr. Shakhawat Hossain is a Professor of Statistics at the University of Winnipeg, serving as Chair starting July 2025. He holds adjunct positions at the University of Manitoba and University of Regina. His academic journey includes a PhD from the University of Windsor (2008), postdoctoral training at the University of Alberta's School of Public Health (2008–2010), and prior faculty roles at Alabama A & M University. He specializes in advanced statistical methodologies with applications in health sciences and epidemiology. Dr. Hossain's education includes: Ph.D. in Statistics, University of Windsor M.Sc. in Statistics, University of Alberta M.Sc. in Mathematics, Jahangirnagar University, Bangladesh B.Sc. (Hons.) in Mathematics, Jahangirnagar University, Bangladesh His research focuses on shrinkage estimation techniques , longitudinal data analysis , survival analysis , and health services research . He actively applies these methods to study dengue transmission dynamics, neuroimaging correlates of developmental disorders, and clinical outcomes in pediatric populations. His work bridges theoretical statistical innovation with real-world public health challenges. Dr. Hossain currently holds an NSERC Discovery Grant supporting student research. His 2023-2024 publications emphasize spatial epidemiology, advanced survival models, and dengue fever dynamics. He serves as Associate Editor of the Journal of Statistical Computation and Simulation . His advisory and grant activities include mentoring students in statistical modeling and securing funding for interdisciplinary health projects. While specific lab affiliations are not explicitly stated, his collaborations span departments in statistics, public health, and biomedical sciences.

Nick Moseyمشاهده پروفایل

دانشیار

• Computational Chemistry
• Theoretical Chemistry
• Materials Science
• +۷ مورد دیگر

Nick Mosey is an Associate Professor in the Department of Chemistry and Associate Dean (Research) in the Faculty of Arts & Science at Queen’s University. He holds a PhD from the University of Western Ontario and completed postdoctoral research at Princeton University. His research focuses on computational and theoretical chemistry, particularly in developing simulation methods to study chemical reactions under mechanical stress and tribological conditions. Key areas include molecular dynamics, exact exchange calculations in periodic systems, and the design of electrocatalysts for fuel cells. His work integrates method development (e.g., contracted planewave basis functions, temporal QM/MM) with applied studies in tribology (e.g., friction modifiers, lubricants) and electrocatalysis (nickel-based materials for alkaline fuel cells). He has led interdisciplinary projects involving collaborations across chemistry, materials science, and engineering. Awards include the NSERC Doctoral Prize (2007), Early Researcher Award (2009-2014), and leadership in securing funding from NSERC and Ontario government programs. Mosey teaches courses in quantum mechanics and computational chemistry, with a focus on bridging theory and practical applications. His group has produced over 70 peer-reviewed publications and trained numerous graduate students and postdoctoral researchers. Current research emphasizes extending simulation time-scales for reactive systems and exploring novel materials for energy applications.

Ousmane Seidouمشاهده پروفایل

استاد

• Hydrological Modeling
• Climate Change Impacts
• Water Resources Management
• +۴ مورد دیگر

Dr. Ousmane Seidou is a Full Professor in the Department of Civil Engineering at the University of Ottawa, where he has served since 2007. He leads the Hydraulics Lab and holds affiliations with the Faculty of Engineering's Centre for Indigenous Community Infrastructure. His academic journey includes a PhD from École Polytechnique de Montréal (2002) and postdoctoral research at the Institut National de la Recherche Scientifique, Quebec. Dr. Seidou specializes in climate change impacts on water resources, hydrological modeling, and transboundary water management. Education: Ph.D. in Civil Engineering (Hydraulics), École Polytechnique de Montréal (2002) M.Sc. in Water Resources Engineering, École Polytechnique de Montréal (2002) Postgraduate Diploma in Hydroinformatics, École Inter-États des Ingénieurs de l'Équipement Rural (1998) Undergraduate Degree in Civil Engineering, École Mohammadia d'Ingénieurs (1996) Research Focus: Dr. Seidou’s work integrates hydrological modeling with climate adaptation strategies, emphasizing Africa’s water security. Key areas include: Climate change impacts on river basins (e.g., Niger, Congo) Development of flood early warning systems in West Africa Water-Energy-Food-Environment (WEFE) nexus frameworks Environmental flow estimation in wetland ecosystems He leads international projects involving multi-country collaborations and agencies like the United Nations Development Programme and the World Bank. Recent Projects: Principal Investigator for the Niger Basin Authority’s WEFE Nexus initiative Technical leadership in the Dutch-funded BAM-GIRE project (Mali/Guinea wetlands) Development of flood early warning systems for Niamey and Gaya (Niger) Teaching: Courses include Climate Change Impacts on Water Resources, Advanced Hydrological Modeling, and Water Resources Management. He mentors PhD students in hydrology and climate adaptation. Grants & Funding: Secured multi-million-dollar projects with organizations like Wetlands International and the UAE-BELEM Programme. Recent funding includes $135,000 for hydrological modeling tools in the Niger Basin. Labs/Teams: Director of the Hydraulics Lab at the University of Ottawa. Active in global initiatives like the Global Goal on Adaptation (GGA) indicator development under the Paris Agreement.

• Heuristic Search
• Combinatorial Search
• Artificial Intelligence
• +۲ مورد دیگر

Nathan Sturtevant is a Professor at the University of Alberta's Department of Computing Science, an Amii Fellow, and Canada CIFAR Chair. His research spans heuristic and combinatorial search problems, with applications in game AI and pathfinding algorithms. He collaborates with the games industry to implement his research in commercial products. Dr. Sturtevant's research explores search algorithms for single and multiple agents, covering areas such as bidirectional search, meta-learning for game theory, procedural content generation, and multi-agent pathfinding. His work integrates machine learning techniques with classical search algorithms to solve complex problems in game environments. Recent publications demonstrate innovations in search optimization, including novel frameworks for suboptimal bidirectional search, new puzzle difficulty metrics, and applications of transformer models to card game planning. His FarmQuest player telemetry dataset provides resources for studying player behavior in farming simulations.

Adrian Owenمشاهده پروفایل

استاد

• Cognitive Neuroscience
• Clinical Neuroscience
• Disorders of Consciousness
• +۴ مورد دیگر

Dr. Adrian Owen is a Professor of Cognitive Neuroscience & Imaging at Western University's Brain and Mind Institute, holding the Canada Excellence Research Chair. His work focuses on consciousness disorders, neurodegenerative diseases, and functional neuroimaging applications. He pioneered techniques like detecting residual cognition in vegetative patients using fMRI and fNIRS. Research Focus: Owen's research bridges cognitive neuroscience and clinical practice, emphasizing disorders of consciousness, Alzheimer's/Parkinson's mechanisms, and neurorehabilitation. He develops brain-computer interfaces for communication in non-responsive patients and investigates anesthesia effects on neural connectivity. Key Contributions: Pioneered covert cognition detection in vegetative patients, advanced fNIRS applications in ICU settings, and established international clinical cohorts for consciousness assessment. His work has appeared in Nature , Science , and The Lancet . Labs/Teams: Leads the Owen Lab at Western University, collaborating with clinicians, engineers, and neuroscientists to translate neuroimaging innovations into clinical tools. Grants/Industry Links: Receives funding for interdisciplinary projects linking brain imaging, neurology, and biomedical engineering, fostering industry partnerships for neurotech development.

Tao Liuمشاهده پروفایل

استادیار

• Computational biomechanics
• Footwear science
• Wearable technology
• +۳ مورد دیگر

Dr. Tao Liu is an Assistant Professor in the Department of Mechanical and Manufacturing Engineering at the University of Ontario Institute of Technology, Faculty of Engineering and Applied Science. His research focuses on computational biomechanics, footwear science, wearable technology, and assistive devices. He holds a Ph.D. in Biomechanics (University of Alberta), MSc (Northeastern University), and BSc (Northeastern University) in Mechanical Engineering. Education: Ph.D. (Biomechanics) - University of Alberta MSc (Mechanical Engineering) - Northeastern University BSc (Mechanical Engineering) - Northeastern University Research Interests: Dr. Liu's work integrates computational modeling, biomechanical analysis, and medical device design. Key areas include musculoskeletal modeling, finite element analysis of orthopedic implants, and optimizing wearable technologies for clinical applications. His research emphasizes translating biomechanical insights into practical solutions for rehabilitation and sports performance. Key Achievements: 2024 Editor’s Choice Award (Journal of Medical & Biological Engineering & Computing) 2022 Mitacs Accelerate Award (Canada) Shortlisted for REHAB Innovation to commercialization (2021) and Calgary Life Science Fellowship (2020) Recipient of 2013 UAV Innovation Grand Prix (national level) Research Contributions: His publications span musculoskeletal modeling validation, implant design optimization, and biomechanical analysis of footwear and spinal mechanics. Recent work emphasizes subject-specific modeling techniques and clinical validation of biomedical devices.

Fedor Dokshinمشاهده پروفایل

استادیار

• Computational and Quantitative Methods
• Environmental Sociology
• Political Sociology
• +۴ مورد دیگر

Fedor Dokshin is an Assistant Professor in the Department of Sociology at the University of Toronto, Downtown Toronto (St. George) campus. His research bridges computational social science with environmental and political sociology, focusing on energy transitions, partisan dynamics, and social network structures. Key research areas include racial and income disparities in solar photovoltaic adoption, policy feedback mechanisms in renewable energy programs, and partisan influences on environmental decision-making. Fields of Study: Computational and Quantitative Methods, Environmental Sociology, Political Sociology, Social Networks Areas of Interest: Computational social science, Energy and the environment, Political polarization Research Trends: Dokshin's publications reveal a focus on energy justice, behavioral diffusion models, and political polarization. His work combines computational methods with environmental policy analysis, examining how socioeconomic factors and partisan identities shape renewable energy adoption. Articles demonstrate geographic heterogeneity in opposition to extraction projects, digital discourse analysis techniques, and institutional dynamics affecting scholarly knowledge production. Methodological Emphasis: Utilizes large-scale data analysis, spatial modeling, and automated textual analysis to explore energy-environment-society intersections. Research highlights the tension between technical solutions and social equity in energy transitions, with recurring themes of policy design, public engagement, and networked political behavior.

Miroslava Kavgicمشاهده پروفایل

دانشیار

• Sustainable Building Engineering
• Carbon Capture Materials
• HVAC Systems Optimization
• +۶ مورد دیگر

Miroslava Kavgic is an Associate Professor in the Department of Civil Engineering at the University of Ottawa. She holds a Ph.D. (United Kingdom), M.Sc. (United Kingdom), and B.Sc. (Serbia), and is a Professional Engineer (P.Eng.). Her research focuses on sustainable building engineering, carbon-negative materials, and energy-efficient design for remote communities. She leads the Centre for Indigenous Community Infrastructure at uOttawa, emphasizing culturally appropriate solutions. Education: Ph.D. in Environmental Design and Engineering (University College London, 2013) M.Sc. in Environmental Design and Engineering (University College London, 2006) B.Sc. in Mechanical Engineering (Serbia) Research Interests: Carbon capture building materials (e.g., hempcrete composites) Bioclimatic design strategies for net-zero buildings Urban energy modeling to decarbonize cities Renewable energy systems integration Advanced HVAC controls and energy efficiency Her recent publications (2021–2025) emphasize: Phase change material applications in building envelopes Machine learning for energy demand prediction Optimization algorithms like MEVO for building performance Hybrid renewable energy systems Labs/Teams: Active in the Centre for Indigenous Community Infrastructure, focusing on Northern communities' sustainable infrastructure. Collaborates with industry on building design innovations.