جست‌وجوی استاد و پژوهشگر

Mostafa Naghizadehمشاهده پروفایل

پژوهشگر

• Seismic Data Processing
• Inverse Problems
• Mineral Exploration
• +۳ مورد دیگر

Mostafa Naghizadeh is a Researcher affiliated with the Metal Earth project at Laurentian University's Harquail School of Sustainable Mining. His expertise lies in seismic data processing, inverse problems, and mineral exploration geophysics. He holds a B.Sc. in Mining Engineering from Shahid Bahonar University of Kerman (Iran), an M.Sc. in Geophysics from the University of Tehran, and a Ph.D. in Geophysics from the University of Alberta. Dr. Naghizadeh's research focuses on advancing seismic imaging techniques, environmental sustainability in seismic surveys, and crustal architecture studies. His work integrates geophysical methods with machine learning to enhance mineral exploration efficiency. He has contributed to projects like the Metal Earth initiative, which maps mineral endowments in Canada's Archean terranes. Education: B.Sc. Mining Engineering, Shahid Bahonar University of Kerman M.Sc. Geophysics, University of Tehran Ph.D. Geophysics, University of Alberta His research interests emphasize seismic data optimization, inverse problem solutions, and environmental adaptations for geophysical surveys. Recent work includes developing EcoSeis—low-footprint acquisition methods—and analyzing fault systems in gold-endowed regions. He has received numerous awards, including the SEG Karcher Award (2011), CSPG Baillie Award (2009), and multiple scholarships for academic excellence. Professionally, he is a certified Geoscientist (APEGA) and holds editorial roles at SEG's Geophysics and CSPG's Recorder journals. Key contributions include advancing seismic design for sustainability, crustal-scale imaging, and mineral prospectivity mapping in the Abitibi and Wabigoon belts. His interdisciplinary approach bridges geophysics with environmental and computational sciences.

Shahrukh Atharمشاهده پروفایل

استادیار

• Image and Video Processing
• Perceptual Image Quality Assessment
• Digital Signal Processing
• +۳ مورد دیگر

Dr. Shahrukh Athar is an Assistant Professor in the Department of Electrical & Computer Engineering at McMaster University. His research focuses on perceptual image quality assessment (IQA), degraded-reference and multiply-distorted image analysis, and digital signal/video processing. He also emphasizes educational development, particularly active learning strategies and pedagogical training for colleagues and graduate students. He teaches courses such as COMPENG 2DX3 (Microprocessor Systems Project), COMPENG 2SH4 (Principles of Programming), ELECENG 2CI4 (Introduction to Electrical Engineering), and ELECENG 3CL4 (Introduction to Control Systems). His work bridges machine learning applications in IQA with practical educational methodologies. Dr. Athar's research includes developing robust no-reference IQA algorithms using deep learning and constructing large-scale datasets. He has published extensively on topics like image debanding, blind quality assessment, and FPGA-based signal processing implementations. His LinkedIn and other professional profiles highlight interdisciplinary contributions in both technical and educational domains.

Michael Noseworthyمشاهده پروفایل

استاد

• Medical imaging physics
• Magnetic resonance imaging
• Multinuclear spectroscopy
• +۷ مورد دیگر

Dr. Michael Noseworthy is a Professor in both the Electrical & Computer Engineering Department and the McMaster School of Biomedical Engineering at McMaster University. He serves as the Director of Medical Imaging Physics and Engineering at St. Joseph's Healthcare and holds a Special Professional Staff position in Radiology and Nuclear Medicine. Previously, he was Co-Director of the McMaster School of Biomedical Engineering from 2010 to 2020. Dr. Noseworthy's research focuses on medical imaging physics, particularly magnetic resonance imaging (MRI) and multinuclear spectroscopy (MNS), with applications in brain, muscle, and cancer research. His work involves developing comprehensive disease imaging protocols that evaluate anatomic, metabolic, and functional characteristics of healthy and abnormal tissues. He has increasingly focused on multimodal techniques that fuse MRI with EEG, EMG, ultrasound, and other imaging methods. His recent publications demonstrate expertise in accelerated MRI techniques, concussion research, tissue microstructure assessment, and machine learning applications in medical imaging. His work spans multiple disciplines including biomedical engineering, neuroscience, and computational imaging. President's Award for Excellence in Graduate Supervision (McMaster University, 2013) Distinguished Fellow Adjunct Professor, Institute of Applied Health Science, Mohawk College (2024) P.Eng. (L.E.L) professional engineering license Dr. Noseworthy teaches several courses including Medical Imaging Systems II (BIOMED 702, ECE 780, MED PHYS 702) and Advanced Medical Imaging (ELECENG 4BF4), focusing on MRI, NMR, ultrasound, and optical imaging methods. His research group develops innovative imaging protocols that integrate complex systems mathematics and machine learning for medical image analysis.

Sorina Dumitrescuمشاهده پروفایل

استاد

• Multimedia Computing
• Data Compression
• Signal Processing
• +۴ مورد دیگر

Dr. Sorina Dumitrescu is a Professor in the Department of Electrical & Computer Engineering at McMaster University, where she has held various academic and research roles since 2002. She earned her Ph.D. in Mathematics from the University of Bucharest (1997) and completed a postdoctoral fellowship at the University of Western Ontario (2000–2002). Her research focuses on multimedia coding, communications, and data compression, with particular emphasis on network-aware systems, signal quantization, and steganalysis. She has been recognized with the NSERC University Faculty Award (2007–2012). Her research interests include distributed quantization for machine learning, resource allocation in non-orthogonal multiple access systems, and robust image coding. She has authored numerous publications, including a notable book on network-aware source coding. Dr. Dumitrescu teaches courses such as COMPENG 3SM4 (Algorithm Design and Analysis) and ECE 726 (Machine Learning: An Introduction). Key achievements include pioneering work on multiple description source coding, distributed source coding, and steganalysis. Her articles span topics like optimal quantizer design, network resource allocation, and error-resilient coding strategies. Awards and grants highlight her contributions to advancing communication systems and information theory.

• Human Cognition
• Attention
• Memory
• +۵ مورد دیگر

Robert Bruce Milliken is a Professor at McMaster University in the Department of Psychology, Neuroscience & Behaviour . As an experimental psychologist, his work focuses on understanding fundamental processes in human cognition, including attention, memory, and cognitive control. His research explores the distinction between conscious and unconscious mental processes, the role of attention in learning and memory, the impact of visual imagery on perception, and how implicit learning shapes attentional control. Education : Ph.D., M.A., and B.A. from the University of Waterloo; Postdoctoral Researcher at McMaster University Research Trends : Analysis of his 15 most recent publications reveals consistent focus on visual attention mechanisms, cognitive control dynamics, and memory encoding processes. Key subfields include attentional blink paradigms, contextual cueing effects, imagery-perception interactions, and the role of perceptual difficulty in memory formation. Teaching Activities : He has taught advanced courses including Human Memory, Senior Honours Thesis, and Cognitive Psychology at McMaster University from 2017-2025, supervising numerous student research projects.

Jacques Royمشاهده پروفایل

استاد

• Transportation Management
• Supply Chain Management
• Transportation Network Optimization
• +۲ مورد دیگر

Jacques Roy is a full Professor in the Department of Logistics and Operations Management at HEC Montréal. He serves as Director of the CHAÎNE Research Group and Supervisor of the Supply Chain Forum (Carrefour Logistique). His expertise spans Transportation Management, Supply Chain Management, and Operations Research. He holds an MBA (Operational Research) and a Ph.D. (Operations Management – Economics minor) from HEC Montréal. Education: MBA in Operational Research, HEC Montréal Ph.D. in Operations Management (Economics minor), HEC Montréal Research Interests: His research focuses on enhancing supply chain resilience, healthcare logistics optimization, and sustainable packaging strategies. Notable projects include pandemic-related supply chain management, transportation network design, and business process improvement. Recent studies emphasize collaboration barriers in healthcare supply chains and pandemic-driven operational challenges. Publications & Awards: Recent works include a 2023 book on Quebec’s airports and a 2024 study on supplier contributions to PPE logistics resilience. He received the 2023 Impact Research Award for pandemic-related research and the 2020 Jean-Guertin Teaching Excellence Prize. Supervision & Grants: Advises over 40 graduate students on topics like decarbonization in road transport, hydrogen truck economics, and air freight pricing. Leads projects for organizations such as Keurig Dr Pepper, Pratt & Whitney Canada, and Shanghai ITPC. Labs & Teams: Leads the CHAÎNE Research Group and the Logistics Hub, fostering collaboration between academia and industry stakeholders.

Anastasis Kratsiosمشاهده پروفایل

استادیار

• Machine Learning
• Artificial Intelligence
• Statistical Learning
• +۵ مورد دیگر

Anastasis Kratsios is an Assistant Professor in the Department of Mathematics and Statistics at McMaster University. His research focuses on the analytic and statistical foundations of deep learning, particularly in encoding structures from natural and social sciences like stochastic processes, games, and PDEs. He teaches courses including Computational Finance, Mathematical Reasoning, and Calculus for Science. Research interests span machine learning theory, approximation methods, and their applications in finance and geometry. Notable work includes neural operator design for PDEs, causal deep learning models, and federated learning frameworks. He frequently publishes in top venues like NeurIPS, ICLR, and Journal of Machine Learning Research. Teaching responsibilities include MFM 713 (Computational Finance II), MATH 1C03 (Introduction to Mathematical Reasoning), and MATH 1A03 (Calculus for Science I). He has developed innovative curricula blending theoretical rigor with practical computational finance tools. Publications emphasize theoretical guarantees for neural networks, kernel methods, and geometric deep learning. Recent work explores universal approximation under constraints, adversarial learning in market models, and scalable graph representation techniques. His research bridges mathematical foundations with real-world applications in finance, physics, and engineering.

Steve Hansenمشاهده پروفایل

استاد

• Human Movement Behavior Analysis
• Motor Control
• Sensory-Motor Systems
• +۳ مورد دیگر

Dr. Steve Hansen is a Professor in the Department of Physical and Health Education at Nipissing University, serving as Graduate Program Coordinator and Chair within the Schulich School of Education. He holds a BKin (Honours), MSc, and PhD from McMaster University. His research focuses on visual control of upper limb movements, kinematic analyses of movement in both typically developing and special populations, and theoretical modeling of movement control and rehabilitation. Key themes include optimizing speed-accuracy trade-offs, sensory-motor integration, and movement variability quantification. Research interests span human movement behavior, sensory-motor systems, and movement control in clinical populations. His work examines how visual feedback and task constraints influence movement planning and execution, with applications to neurorehabilitation and motor learning. Recent trends in his publications emphasize hormonal effects on motor performance, robotics in pediatric therapy, and peer feedback dynamics in skill acquisition. No scientific awards are explicitly listed, but his extensive publication record reflects impactful contributions to motor control theory. As an academic leader, he oversees graduate training and curricular development in physical education. While no lab affiliations are noted, his research collaborations involve interdisciplinary teams studying biomechanics, neuroscience, and clinical applications.

Jim McAuliffeمشاهده پروفایل

استاد

• Visual Attention
• Motor Learning
• Neurocognitive Function
• +۳ مورد دیگر

Dr. Jim McAuliffe is a Full-Time Professor and Dean of Graduate Studies and Research at Nipissing University's Schulich School of Education. He holds a PhD in Physical Education and Sports Studies from the University of Alberta and has over two decades of academic leadership experience, including roles at Lakehead University and Nipissing. His research focuses on visual attention, motor learning, and neurocognitive function, particularly in the context of sports-related concussions and safe return-to-play protocols. He has secured grants from NSERC, the Ontario Neurotrauma Foundation, and Auto21 Network. Education: HBA & MA (University of Western Ontario), PhD (University of Alberta) Leadership Roles: Director of BPHE Program, Vice-Dean of Schulich School of Education Research interests include visual attention mechanisms, autonomic nervous system responses, and driving safety. He has contributed to over 25 peer-reviewed publications, emphasizing interdisciplinary approaches to human movement science and clinical neurology. Dr. McAuliffe also serves on national sports organizations like Squash Canada and the Canadian Olympic Committee. His academic work bridges theoretical research and practical applications, such as improving sports safety protocols and optimizing cognitive assessments for athletes. He actively collaborates with institutions to advance concussion management strategies and youth sports safety.

Asifa Aamirمشاهده پروفایل

عضو هیئت علمی

• Information Systems
• Business Processes and IT
• User Experience
• +۴ مورد دیگر

Asifa Aamir is an Associate Teaching Professor at Ontario Tech University's Faculty of Business and Information Technology. Her research focuses on information systems, instructional technologies, and hybrid learning models. She investigates strategies to bridge gender gaps in STEM through gamification and user-centric design. Her work also explores the strategic use of new technologies in academia and business environments. Education: SAP Certified Application Associate - Business Process Integration (SAP S/4HANA) Master of Business Administration (Technology Management), University of Duisburg-Essen Master of Philosophy (Information Systems Engineering), Ontario Tech University Master of Science (Computer Sciences), UMIST, Manchester Bachelor's, Quaid-e-Azam University, Pakistan Research Interests: Asifa's work spans information systems engineering, business-process optimization, and the integration of technology in education. She emphasizes user experience design, hybrid learning frameworks, and the impact of emerging technologies on academic and corporate landscapes. Her projects often address accessibility and equity in STEM through innovative instructional tools. Research Trends: Her publications highlight optimization methodologies (e.g., Benders decomposition) and risk management in supply chains, transportation systems, and environmental policy. Recent work emphasizes sustainable infrastructure (e.g., EV charging networks) and data-driven decision-making in logistics. Awards: None explicitly listed. Advising & Grants: While no student advisees are noted, her role emphasizes pedagogical innovation and curriculum development. She contributes to experiential learning initiatives within the Faculty of Business and IT. Labs/Teams: Collaborates with the Business Analytics & AI Research Group, focusing on data-driven solutions for business and academic challenges.

Louise Milletteمشاهده پروفایل

دانشیار

• Environmental Engineering
• Civil Engineering
• Geological Engineering
• +۵ مورد دیگر

Louise Millette is an Associate Professor at Polytechnique Montréal , where she teaches in the Department of Civil, Geological and Mining Engineering . She also serves as Director of the Office of Sustainable Development at Polytechnique Montréal, focusing on operationalizing sustainable practices in engineering education and business systems. Research Areas : Contaminated Site Management, Environmental Management Systems for Businesses, Sustainable Development Implementation Affiliations : CIRODD (Co-Investigator), Michael D. Penner Institute on ESG Issues (Member) Scientific Contributions Millette’s work bridges engineering pedagogy and environmental stewardship, emphasizing human-centric solutions over techno-enthusiasm. Her publications span topics like soil remediation, duckweed-based water treatment, and stakeholder mobilization in circular economy transitions. Awards & Recognition 2024: King Charles III's Coronation Medal 2022: Ordre de Montréal - Chevalier 2020: Quebec's Minister of Higher Education Award 2019: Quebec Business Women's Award 2018: Fellow - Engineers Canada Academic Leadership She has supervised six Master’s theses on climate change adaptation, portable water treatment, and urban environmental decision-making tools. Her advocacy includes public critiques of lithium-based green economy plans and contributions to debates about Montreal’s educational and infrastructure legacy projects.

Soumaya Yacoutمشاهده پروفایل

استاد

• Industrial Engineering
• Operations Management
• Operations Research
• +۷ مورد دیگر

Soumaya Yacout is a Full Professor in the Department of Mathematical and Industrial Engineering at Polytechnique Montréal. She holds a Doctorate in Science from George Washington University and has been a leading academic in industrial engineering and artificial intelligence for over two decades. Her research focuses on Industry 4.0, predictive maintenance, and data-driven decision-making. Key projects include the Intelligent Cyber-Physical Systems Lab, developing cyber-physical platforms for Industry 4.0 factories, and creating algorithms for big data analysis in manufacturing systems. She also leads the CĒOS Net network, advancing smart maintenance strategies for heavy-duty electrical buses. Yacout has supervised over 27 PhD and Master’s students, with notable alumni contributing to sectors like aerospace, automotive, and smart manufacturing. Her work integrates AI, optimization, and machine learning to address complex industrial challenges, including fault diagnosis, prognosis, and real-time decision-making systems. Her recent publications emphasize AI applications in maintenance, digital twins, and predictive modeling. She leads interdisciplinary teams and collaborates with industry partners on projects funded by IVADO and NSERC, driving innovation in sustainable manufacturing and smart infrastructure.

Han Yanمشاهده پروفایل

استادیار

• Banking
• Climate Finance
• Voluntary Disclosure

Han Yan is an Assistant Professor at UBC Sauder School of Business specializing in banking, climate finance, and corporate disclosure practices. He holds a PhD from NYU Stern and teaches managerial accounting courses. His research bridges finance and environmental economics, with recent focus on climate risk integration in financial systems. Prior to his finance career, he conducted significant research in materials science and nuclear engineering, publishing on cyclotron target systems and cellulose-based materials. This interdisciplinary background informs his current work on sustainable finance and environmental disclosure frameworks.

• Continuous Optimization
• Machine Learning
• Design and Analysis of Optimization Algorithms
• +۳ مورد دیگر

Jiajin Li is an Assistant Professor in the Operations and Logistics Division at the UBC Sauder School of Business, concurrently affiliated with the Institute of Applied Mathematics (IAM) at the University of British Columbia. He holds a BSc in Statistics from Chongqing University and a PhD in Systems Engineering and Engineering Management from the Chinese University of Hong Kong (CUHK). Prior to joining UBC, he was a postdoctoral researcher at Stanford University's Department of Management Science and Engineering. His research focuses on continuous optimization , design and analysis of optimization algorithms , and machine learning , with emphasis on nonsmooth/nonconvex optimization, minimax problems, and distributionally robust optimization. His work bridges theoretical foundations with applications in graph data analysis and algorithmic stability. He teaches courses including Logistics and Operations Management (BCom), Seminar on Theoretical Developments in Management (PhD), and Optimization Theory and Applications (PhD). He actively seeks PhD students with strong mathematical or coding backgrounds through UBC Sauder or IAM programs. Key research contributions include advancements in primal-dual balancing for minimax optimization, stability evaluation via distributional perturbation analysis, and outlier-robust algorithms for graph data. His methodologies often integrate optimal transport theory and subdifferential analysis. He is affiliated with multiple research communities, including the IEEE and conferences like NeurIPS, ICML, and ICLR. His work emphasizes algorithmic robustness and scalability in complex optimization landscapes.

Jolene Reidمشاهده پروفایل

استادیار

• Organic Chemistry
• Computational Chemistry
• Catalysis
• +۳ مورد دیگر

Jolene Reid is an Assistant Professor in the Department of Chemistry at the University of British Columbia (Vancouver Campus), affiliated with the Faculty of Science. Her research integrates computational and experimental methods to advance data-driven approaches in organic chemistry, focusing on reaction optimization, catalyst discovery, and mechanistic analysis. Research Interests: Her work emphasizes machine learning applications for reaction prediction, development of efficient chiral catalyst systems, and automation of reaction condition selection. Key themes include understanding noncovalent interactions in enantioselectivity, mechanism-based reaction design, and bridging physical organic principles with synthesis. Publications: Recent work highlights advancements in predictive modeling for catalyst generality, machine learning-driven mechanistic elucidation, and the design of novel chiral phosphoric acid catalysts. Her studies often explore the synergy between computational insights and experimental validation. Lab Team: The Reid Lab at UBC fosters interdisciplinary collaboration, with current members including Yutao, Isaiah, Jiajing, Junshan, and Saumya. They focus on predictive chemistry tools for selective synthesis, emphasizing innovation at the computational-organic interface. Labs/Teams: The Reid Lab is equipped to tackle challenges in catalyst design and reaction optimization, leveraging both experimental and computational infrastructure. Current projects aim to expand the scope of asymmetric catalysis through algorithmic and mechanistic innovation.