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نمایش ۴۶-۶۰ از ۵۸۸ استاد راهنما

اطلاعات این پروفایل‌ها از صفحات عمومی دانشگاه‌ها جمع‌آوری شده و ممکن است به‌روز نباشد.

Mohammad Piraniمشاهده پروفایل

استادیار

University of OttawaCanada

Mohammad Pirani is an Assistant Professor in the Department of Mechanical Engineering at the University of Ottawa, with a joint appointment at the School of Electrical Engineering and Computer Science. Previously, he held postdoctoral and research assistant professor roles at the University of Waterloo, University of Toronto, and KTH Royal Institute of Technology. Education: Ph.D., Mechanical and Mechatronics Engineering, University of Waterloo (2017) MASc., Electrical and Computer Engineering, University of Waterloo (2014) BASc., Mechanical Engineering, Amirkabir University of Technology (2011) His research focuses on resilient and fault-tolerant control in complex systems, including networked control systems and multi-agent systems . He explores intersections with network science , cybersecurity , and machine learning , addressing vulnerabilities in cyber-physical systems like automotive networks. Notable contributions include publications in IEEE Transactions on Control of Network Systems and Automatica , with recent work on network critical slowing down and graph-theoretic resilience strategies. His research trends emphasize reliable learning , security in distributed systems , and data-driven detection of critical transitions . Scientific Awards: Senior Member, IEEE Mohammad Pirani holds a dual appointment at the University of Ottawa and an adjunct professor position at the University of Waterloo. His work bridges mechatronics , robotics and automation , and networked systems , with future directions targeting cybersecurity in cyber-physical systems.

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Marcelo M. Wanderleyمشاهده پروفایل

استاد

McGill UniversityCanada

Marcelo M. Wanderley is a Professor and Director of the Centre for Interdisciplinary Research in Music Media and Technology (CIRMMT) at McGill University's Schulich School of Music. His academic roles include Area Coordinator for Music Technology and membership on the Executive Committee. He holds a PhD in acoustics, signal processing, and computer science from Université Pierre et Marie Curie (Paris VI). Wanderley's research focuses on novel interfaces for music performance, digital musical instruments (DMIs), and human-computer interaction. He has authored influential works such as New Digital Musical Instruments: Control and Interaction Beyond the Keyboard (2006) and pioneered research in gestural control of music. His work integrates engineering, computer science, and musicology to create innovative performance tools, including the T-Stick and Karlax instruments. He has held visiting professorships at Université de Bretagne Sud, Universidade Federal de Minas Gerais (Brazil), and the University of Mons (Belgium), where he was awarded prestigious chairs. Wanderley's awards include the Inria International Chair (2016–2020) and the Distinguished Visitor Award from the University of Auckland. His research has been widely cited in the International Conference on New Interfaces for Musical Expression (NIME), and he actively contributes to editorial boards (e.g., Computer Music Journal ) and academic leadership roles. Wanderley's lab, the Input Devices and Music Interaction Lab (IDMIL), develops open-source frameworks like Puara and Probatio for DMI design and mapping. Key research areas include haptic feedback systems, motion capture of musical performances, and accessibility in music technology. He emphasizes interdisciplinary collaboration, bridging engineering, art, and cognitive science to advance musical expression and performance practices.

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Young-Jin Chaمشاهده پروفایل

استاد

University of ManitobaCanada

Dr. Young-Jin Cha is a tenured full Professor in the Department of Civil Engineering at the University of Manitoba, affiliated with the Price Faculty of Engineering. He holds a PhD from Texas A&M University and has postdoctoral experience at MIT. His research focuses on deep learning-based structural health monitoring (SHM), autonomous UAVs for infrastructure inspection, and smart transportation systems, with over 100 peer-reviewed publications and $1.2M in grants. He is a Fellow of ASCE and has received notable awards including the 2021 Merit Award and 2022 International Association of Advanced Materials Scientist Award. His work has been cited over 9,200 times globally. Research interests include automated SHM with UAVs, nonlinear system identification, unsupervised deep learning for damage detection, and sustainable infrastructure design. He serves as an editor for journals like Structural Control & Health Monitoring and Engineering Reports . His lab, the Laboratory for Infrastructure Science and Technology (LIST), develops advanced technologies for infrastructure resilience. Key achievements include pioneering deep learning-based SHM with UAVs, top-cited papers in civil engineering journals, and leadership in organizing international conferences. He actively seeks graduate students for research in AI-driven infrastructure solutions.

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Brian Surgenorمشاهده پروفایل

استاد

Queen's University at KingstonCanada

Professor Brian Surgenor is a faculty member at Queen's University's Department of Mechanical and Materials Engineering, part of the Smith Engineering faculty. He holds a B.Sc. (1977), M.Eng. (AECL/Whiteshell), and Ph.D. (1983) in Mechanical Engineering from Queen's University. His research focuses on machine vision systems for automation, autonomous vehicle navigation, and mechatronic system design education. He has held key administrative roles including Department Head (1993-2002), Associate Dean (2008-2013), and Vice-Dean (2013-2016). His work emphasizes interdisciplinary innovation, such as the Mitchell Hall design project and contributions to Ingenuity Labs. Education: B.Sc. Mechanical Engineering, Queen's University (1977) M.Eng. Engineering Physics, McMaster University (AECL/Whiteshell) Ph.D. Mechanical Engineering, Queen's University (1983) Research interests include: - Pneumatic servosystems - Intelligent algorithms for machine vision - Off-road autonomous vehicle systems - Mechatronics education methodologies - Hybrid powertrain systems for vehicles His recent publications (2017–2024) explore autonomous systems, machine vision applications, and fuel cell hybrid technologies. Notable trends include advancements in UAV-based infrastructure inspection, terrain-adaptive autonomous driving, and low-cost machine vision solutions for small part sorting. His work bridges theoretical control systems with practical industrial automation challenges. He has contributed to laboratory design for CDIO curricula and pioneered mechatronics education through problem-based learning. His administrative leadership has shaped Queen's engineering graduate programs and research infrastructure. Currently involved in Ingenuity Labs, fostering cross-disciplinary innovation.

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Thomas K. Uchidaمشاهده پروفایل

دانشیار

University of OttawaCanada

Thomas K. Uchida is an Associate Professor in the Department of Mechanical Engineering at the University of Ottawa, a position he has held since May 2024. Prior to this promotion, he served as an Assistant Professor at the same institution from October 2018 to May 2024. Before joining the University of Ottawa, Dr. Uchida was an Engineering Research Associate (April 2015-August 2018) and Simbios Distinguished Postdoctoral Fellow (July 2012-April 2015) in the Department of Bioengineering at Stanford University. Dr. Uchida's research focuses on the modeling and simulation of dynamic systems, with particular emphasis on human movement biomechanics. His work spans multiple areas including: Simulation-guided design of assistive devices for improving mobility Modelling musculotendon dynamics and energy expenditure Parameter identification and model reduction methods Impact and contact dynamics Development of computational tools for biomechanical analysis He is a co-author of the book "Biomechanics of Movement: The Science of Sports, Robotics, and Rehabilitation" published by MIT Press, and actively contributes to the development of OpenSim, an open-source software platform for modeling musculoskeletal systems and generating simulations of human and animal movement. His work on OpenSim was featured on the cover of PLoS Computational Biology. Dr. Uchida's recent publications demonstrate strong activity in biomechanics, robotics, and computational modeling. His work bridges engineering principles with biological applications, particularly in understanding human movement mechanics. Key trends include applying machine learning to gait analysis, developing enhanced spine models, analyzing human balance stability with time delays, and advancing musculoskeletal simulation techniques. As an academic advisor, Dr. Uchida currently supervises seven graduate students: Firas Baklouti (expected completion August 2025) Shahin Sharafi Kazem Alambeigi Jiawei Gao Yuzhen Yan Manuel Lucas De Oliveira Blake Scott Miller Dr. Uchida collaborates with research teams focused on biomechanics and movement science. His work with OpenSim places him within an international community of researchers developing computational tools for biomechanical analysis, connecting mechanical engineering with biomedical applications in sports, robotics, and rehabilitation.

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Angelica Limمشاهده پروفایل

استادیار

Simon Fraser UniversityCanada

Angelica Lim is an Assistant Professor of Professional Practice and Rajan Family Scholar in the School of Computing Science at Simon Fraser University. Her research focuses on Human Robot Interaction, Affective Computing, and Multimodal Perception with applications in healthcare and developmental robotics. She holds a PhD in Informatics from Kyoto University (2014), an M.Sc. from Kyoto University (2012), and a B.Sc. in Computing Science from SFU (2008). Her work bridges robotics and human-centered AI through projects like the ROSIE Lab, exploring emotion-aware systems, socially assistive robots, and VR programs for aging populations. Key contributions include benchmarking emotional speech recognition (BERSting), developing embodied emotion models for robots, and co-designing healthcare technologies with patient partners. Recent publications emphasize ethical AI, multimodal perception systems, and human-robot collaboration in dynamic environments. Teaching includes courses on software engineering, artificial intelligence, and introductory computer science. Her research has been applied in dementia care through VR programs, robotic companionship for older adults, and emotion-aware human-robot communication systems. Current initiatives focus on inclusive HRI design and sim2real methodologies for underrepresented data in affective computing.

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Jason Heinمشاهده پروفایل

دانشیار

University of British ColumbiaCanada

Jason Hein is an Associate Professor in the Department of Chemistry at the University of British Columbia's Faculty of Science. His research focuses on the development of automated reaction analysis technology and self-driving laboratories that integrate robotics with synthetic organic chemistry. Dr. Hein leads the Hein Lab, which pioneers innovative solutions for mechanistic organic chemistry, catalytic reaction mechanisms, and chemical manufacturing processes. His research interests center on creating modular robotic tools and integrated analytical hardware for automated reaction profiling, with applications in pharmaceutical manufacturing, battery materials processing, and sustainable chemistry. The lab's work combines advanced robotics, artificial intelligence, and process analytical technology to develop self-optimizing chemical systems that accelerate discovery and improve manufacturing efficiency. Analysis of Hein's recent publications reveals a strong focus on AI-driven laboratory automation, with particular emphasis on crystallization optimization for battery materials, computer vision for process monitoring, and interoperable software systems for self-driving laboratories. His work bridges fundamental mechanistic understanding with practical industrial applications, particularly in lithium extraction from waste brines and pharmaceutical process development. NSERC Postdoctoral Fellowship Dr. Hein's research program includes significant grant funding supporting the development of self-driving laboratory technologies and their application to challenging chemical problems. His lab actively collaborates with industry partners in pharmaceuticals and clean energy sectors to translate fundamental insights into deployable technologies. Current projects focus on battery-grade lithium carbonate production, continuous manufacturing processes, and AI-optimized chemical synthesis. The Hein Lab operates as a multidisciplinary research environment combining expertise in organic chemistry, robotics engineering, computer science, and data analytics to create the next generation of autonomous chemical discovery systems.

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Irina T. Garcesمشاهده پروفایل

استادیار

Carleton UniversityCanada

Dr. Irina T. Garces is an Assistant Professor in the Department of Mechanical and Aerospace Engineering at Carleton University. She holds a Ph.D. from the University of Alberta and specializes in composite-smart materials, additive manufacturing, and polymer processing. Her research focuses on developing 'materials as machines'—adaptive material systems for applications in soft robotics, biomedical devices, and aerospace. Key areas include shape memory polymers, electro-active composites, and novel 3D printing technologies for biodegradable materials. Her publications demonstrate consistent focus on smart material innovation, with recent work exploring moisture effects in additive manufacturing and cellulose-based medical implants.

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Erik Schemeمشاهده پروفایل

دانشیار

University of New BrunswickCanada

Erik Scheme is an Associate Professor in the Department of Electrical and Computer Engineering at the University of New Brunswick (UNB), and serves as Associate Director of the Institute of Biomedical Engineering (IBME). He holds a PhD and is a Professional Engineer (PEng). His roles include advising the Dr. J. Herbert Smith Centre for Technology Management and Entrepreneurship, emphasizing innovation in biomedical technologies and healthcare systems. His research focuses on advanced human-machine interaction through biomedical engineering, with a strong emphasis on myoelectric prosthetics, wearable sensors, and machine learning applications. Key areas include improving neuroprosthetic control via incremental learning, gait analysis using underfoot pressure sensors, and developing robust EMG-based gesture recognition systems. His work bridges clinical needs with technological innovation, addressing challenges in rehabilitation, activity monitoring, and user-centric design. Recent publications highlight advancements in adaptive control systems, sensor fusion, and ethical data practices in healthcare. His contributions span both theoretical frameworks (e.g., self-supervised learning models) and applied technologies (e.g., gold-plated 3D-printed electrodes). Dr. Scheme collaborates across disciplines, integrating robotics, signal processing, and clinical validation to create impactful solutions. His lab, affiliated with IBME, actively explores emerging areas like exhaled breath analysis for disease detection and federated learning in healthcare data analytics.

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Reza Fotouhiمشاهده پروفایل

استاد

University of SaskatchewanCanada

Reza Fotouhi is a Professor in the Department of Mechanical Engineering at the University of Saskatchewan, specializing in Robotics (Dynamics and Control), Structural Dynamics and Vibrations, Computational Mechanics, and Biomechanics. He leads research in agricultural robotics, finite element modeling, and teleoperated systems. Education: BSc, MSc (Iran) MSc, PhD (University of Saskatchewan) His research focuses on human-robot interaction, vibration control for flexible manipulators, composite material applications, and teleultrasound systems. He has developed mobile platforms for crop phenotyping and optimized control strategies for robotic arms. Recent Article Trends: His work spans telerobotic medical systems, agricultural automation, advanced control algorithms (e.g., Particle Swarm Optimization), and structural analysis of composite materials. Key subfields include musculoskeletal imaging, path planning, and dynamic modeling of flexible systems. Research Groups: Applied Mechanics and Machine Design Control Systems, Robotics and Fluid Power Engineering for Agriculture

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Monica Malyمشاهده پروفایل

دانشیار

McMaster UniversityCanada

Monica Maly is a Part-Time Associate Professor in Rehabilitation Science within the Faculty of Health Sciences at McMaster University. Her academic profile demonstrates extensive expertise in biomechanics and rehabilitation, with particular focus on knee osteoarthritis research. She maintains an active research program with numerous recent publications spanning rheumatology, biomechanics, and rehabilitation science. Dr. Maly's research interests center on understanding the biomechanical and physiological factors contributing to knee osteoarthritis progression and developing effective interventions. Her work examines knee joint mechanics, muscle strength and capacity, gait analysis, pain management strategies, and the impact of exercise interventions on OA symptoms. She has conducted significant research on sex differences in OA, racial disparities in pain experiences, and the relationship between obesity, inflammation, and joint function. Her methodological approaches include biomechanical analysis, clinical trials, systematic reviews, and innovative technologies like soft robotics for knee bracing. Analysis of her recent publications (2023-2025) reveals a strong focus on understanding knee osteoarthritis mechanisms through biomechanical and physiological lenses, with increasing attention to social determinants of health and health disparities. Her work spans multiple disciplines including rheumatology, biomechanics, rehabilitation science, and public health, demonstrating interdisciplinary collaboration. Key trends include examining racial disparities in pain experiences, developing novel interventions like soft robotic knee braces, and investigating the complex relationships between joint loading, biomarkers, and cartilage changes. Dr. Maly has collaborated extensively with researchers across multiple institutions, as evidenced by her numerous publications in high-impact journals such as Osteoarthritis and Cartilage, Arthritis & Rheumatology, and Clinical Biomechanics. Her work often utilizes data from large longitudinal studies including the Osteoarthritis Initiative and the Canadian Longitudinal Study on Aging. While specific grant information isn't detailed in the provided text, her extensive publication record suggests successful funding of multiple research projects.

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Philippe Dixonمشاهده پروفایل

استادیار

McGill UniversityCanada

Dr. Philippe Dixon is an Assistant Professor in the Department of Kinesiology & Physical Education at McGill University, with a division in Biomechanics and Neuroscience. He holds adjunct professor roles at the University of Montreal (School of Kinesiology and Physical Activity Sciences) and the University of Laval (Department of Kinesiology). His research focuses on human movement biomechanics using motion capture systems and wearable sensors, combined with machine learning for health and athletic performance optimization. He has expertise in gait analysis, muscle coactivation patterns in cerebral palsy, and predictive modeling of physiological states. Dr. Dixon earned a Post-doctoral fellowship in Public Health at Harvard University, a PhD in Engineering Science from the University of Oxford, and dual degrees in Biomechanics and Physics from McGill University. His education includes a Bachelor of Education in Mathematics and Physics (McGill), a Master of Science in Biomechanics (McGill), and a PhD in Engineering Science (Oxford). He has received grants such as the NSERC Discovery Grant (2022–2027) and the FRQSC AUDACE Grant (2022). His work emphasizes wearable sensor integration, with contributions to datasets like NACOB and tools like OpenOFM. He currently supervises Master’s and PhD students in biomechanics and machine learning applications. Key research themes include gait adaptations on uneven surfaces, machine learning for cough detection via smart garments, and musculoskeletal coordination in clinical populations. His articles span biomechanical modeling, wearable sensor validation, and neuro-musculoskeletal analysis, reflecting interdisciplinary innovation in human movement science.

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Lyndia Wuمشاهده پروفایل

استادیار

University of British ColumbiaCanada

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.

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Shahin Sirouspourمشاهده پروفایل

استاد

McMaster UniversityCanada

Shahin Sirouspour is a Professor in the Department of Electrical and Computer Engineering at McMaster University. His research focuses on robotics, autonomous systems, control systems, and optimization, with applications in aerial robotics, teleoperation, haptics, medical robotics, and smart energy grids. He is affiliated with the Telerobotics, Haptics and Computational Vision Laboratory and teaches courses such as Non-linear Control Systems and Electrical Systems Integration Project. He holds a Ph.D. from the University of British Columbia and has supervised numerous graduate students. His lab includes advanced equipment like multi-axis robotic manipulators, haptic interfaces, and real-time computing systems. Education: B.Sc. and M.Sc. from Sharif University of Technology (Iran), Ph.D. from University of British Columbia (Canada). Current roles include accepting graduate students and leading research clusters in Digital & Smart Systems, Energy, and Transportation. Awards include the McMaster President's Award for Excellence in Graduate Supervision. His work bridges theoretical control systems with practical applications in healthcare, energy, and autonomous systems. Research highlights include developing control strategies for multi-agent robotic systems, smart grid optimization, and medical robotics. Collaborations with institutions like MacAUTO and industry partners (e.g., MDA Space Missions) enhance translational impact. His lab supports projects on asymmetric teleoperation, deformable tissue simulation, and microgrid energy management.

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Tina Shoaمشاهده پروفایل

دانشیار

Simon Fraser UniversityCanada

Tina Shoa is an Associate Professor in the School of Sustainable Energy Engineering at Simon Fraser University. She holds a Ph.D. in Electrical Engineering from the University of British Columbia (2010), an M.Sc. from the University of Manitoba (2004), and a B.Sc. from Iran University of Science and Technology (2000). Her research focuses on battery performance modeling, electrochemical methods for fault detection, sustainable battery manufacturing, and AI-based diagnostics. Education: Ph.D., Electrical Engineering, University of British Columbia, 2010 M.Sc., Electrical Engineering, University of Manitoba, 2004 B.Sc., Electrical Engineering, Iran University of Science and Technology, 2000 Research Interests: Battery performance modeling, analysis, and optimization Electrochemical and ultrasound-based battery fault detection Sustainable battery manufacturing processes AI-driven battery diagnostics Teaching and Courses: Advanced Battery and Fuel Cell Technologies Power Plant Systems Smart Grids Practicum SEE 354 D100 Energy Storage (Summer 2025) Patents: Battery State-of-health Determination upon charging (US Patent 11079437B2, 2022) Battery State-of-health Determination using multi-factor normalization (US Patent 10,302,709, 2019) Apparatus and Method for testing electrochemical systems (US Provisional Patent 62/994687, 2020) Key Contributions: Her work integrates electrochemical principles and AI to advance battery diagnostics and sustainable energy storage solutions. She has authored over 15 publications in top-tier journals and conferences, addressing battery aging, state estimation, and novel manufacturing techniques.

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