جست‌وجوی استاد و پژوهشگر

Alan Fungمشاهده پروفایل

دانشیار

• Sustainable Building and Community Energy Systems
• Renewable Energies
• Building Integrated Energy Systems
• +۱۲ مورد دیگر

Dr. Alan Fung is an Associate Professor in the Department of Mechanical, Industrial, and Mechatronics Engineering at Toronto Metropolitan University, Faculty of Engineering and Architectural Science. His research focuses on sustainable building and community energy systems, renewable energies, and smart control technologies for net-zero energy applications. Research Interests: Dr. Fung specializes in energy efficiency, building-integrated energy systems, hybrid renewable systems, HVAC optimization, and adaptive control using AI and machine learning. His work aims to reduce building sector emissions and support carbon-neutral urban development. Research Trends: His recent publications highlight a strong focus on real-world energy modeling, urban building energy benchmarking, geothermal heat exchangers, industrial energy savings, and innovative energy sharing networks—particularly in cold climates. The integration of simulation and experimental validation is a consistent theme. Scientific Awards: Governor General Gold Medal CMHC Excellence in Education Award Mitacs Professor Award for Exceptional Leadership Champion of Diversity Award Advising and Grants: Dr. Fung is available to supervise students and has led research initiatives funded by government and industry partners, including projects on clean coal, sewage-based hybrid systems, and AI-optimized building controls. His leadership in education and sustainability reflects strong mentorship and grant acquisition capabilities. Labs and Teams: He is affiliated with the Centre for Sustainable Energy Systems (CSES), where interdisciplinary research on renewable energy integration, building performance, and sustainable infrastructure is conducted.

Jason Bramburgerمشاهده پروفایل

استادیار

• Dynamical Systems
• Data-Driven Methods
• Pattern Formation
• +۳ مورد دیگر

Jason Bramburger is an Assistant Professor at Concordia University and an adjunct professor at McGill University. He is a member of the CRM Applied Math Lab and contributes to the Physica D Editorial Board. His research focuses on dynamical systems, data-driven discovery, pattern formation, and polynomial optimization applied to differential equations. He holds a Ph.D. from the University of Ottawa (2017), with postdoctoral fellowships at Brown University and the University of Victoria, and prior experience as an acting instructor at the University of Washington. Research interests include multiscale dynamics, nonlinear Floquet theory, and Koopman operator methods. Recent work emphasizes data-driven analysis of dynamical systems, with applications to Poincaré maps, invariant measures, and control systems. Key contributions include methods for discovering Poincaré maps via sparse regression and bounding long-term system behaviors using convex optimization. Notable publications span topics like real-time motion detection, localized patterns in networks, and ergodic optimization. Bramburger actively contributes to open-source projects, including a textbook on Data-Driven Methods for Dynamic Systems , and maintains GitHub repositories for computational tools in dynamical systems and neural networks.

Fabrice Labeauمشاهده پروفایل

استاد

• Telecommunications
• Signal Processing
• Cybersecurity
• +۴ مورد دیگر

Fabrice Labeau is a Professor in the Department of Electrical & Computer Engineering at McGill University. He holds additional administrative roles as Vice-President (Administration and Finance) and Director of Operations for the STARaCom Centre. His research focuses on telecommunications, signal processing, cybersecurity, and smart grids, with notable contributions to privacy-preserving techniques in machine learning and secure communication systems. He has received prestigious awards including the IEEE VTS Outstanding Service Award (2008, 2016), the IEEE Canada W.S. Read Outstanding Service Award Medal (2017), and recognition for leadership in organizing major IEEE conferences. His work spans theoretical advancements and practical applications, particularly in smart grid security and wireless communication systems. Prof. Labeau's professional activities include leadership roles in IEEE societies (e.g., President of the IEEE Consumer Technology Society 2025-2026) and extensive conference organization (e.g., General Chair of IEEE GlobalSIP 2017, VTC-Fall 2016). His research group collaborates on cutting-edge topics like adversarial robustness, privacy in smart meters, and UAV-assisted networks. Key technical contributions include algorithms for secure channel estimation, resource allocation in 5G networks, and frameworks for detecting cyberattacks in power systems. He maintains active engagement with industry standards through IEEE committees and has authored over 150 peer-reviewed publications and a Springer book on wireless communication for power substations.

Marcia Friesenمشاهده پروفایل

استاد

• Engineering Education
• Indigenous Knowledge Integration
• mHealth Applications
• +۳ مورد دیگر

Marcia Friesen is the current Dean of the Price Faculty of Engineering and a Professor in the Department of Engineering Education at the University of Manitoba. She holds a PhD in Biosystems Engineering from the same institution. Her roles include leading the Faculty’s strategic vision, research initiatives, and community outreach programs such as WISE-KidNetic Energy and the ENGAP Program for Indigenous Canadians. Dr. Friesen has served as NSERC Chair in Design Engineering (2018–2023) and previously held leadership positions including Director of the Internationally Educated Engineering Qualifications Program (IEEQ). Her research focuses on engineering education innovation, Indigenous knowledge integration into curricula, sustainable development, and mHealth technologies. Notable projects include advancing design education for resilience and sustainability, particularly in Indigenous communities, and developing agent-based models for public health applications. She has secured over $2M in research funding and contributed to policy through roles at Engineers Geoscientists Manitoba and the Canadian Engineering Memorial Foundation. Dr. Friesen’s scholarly work spans engineering education pedagogy, intercultural competency, and technology for healthcare. Her recent publications emphasize empathy-driven design, equity in hiring practices, and Indigenous perspectives in STEM education. Beyond academia, she fosters industry partnerships through programs like Engineers-in-Residence and co-op placements, enhancing student experiential learning opportunities.

• Sleep Medicine
• Orofacial Pain
• Bruxism
• +۴ مورد دیگر

Gilles Lavigne is an Associate Professor at the Faculty of Dental Medicine, University of Montreal, with affiliations to institutions including CHUM (Centre hospitalier de l'Université de Montréal), CIUSSS Nord-de-l'île-de-Montréal, and the Canadian Sleep and Circadian Network. He specializes in sleep medicine, orofacial pain, and bruxism research, holding leadership roles in the Canadian Pain Trials Network and the Research Group on Oral and Craniofacial Sciences. Key research areas: Sleep-bruxism-pain interactions, sleep apnea, temporomandibular disorders Scientific honors: Member of Canadian Academy of Health Sciences (2017), Order of Canada (2018), Honorary Doctorate (University of Zurich, 2009) Grants: Canadian Institutes of Health Research (CIHR), Fonds de recherche du Québec - Santé (FRQS), National Institutes of Health (NIH) His clinical work focuses on orofacial pain and dental sleep medicine at CHUM. He has supervised 14 graduate students (PhD/MSc) and published extensively on sleep disorders, pain mechanisms, and dental interventions.

• Health Sciences
• Medical Sciences
• Pediatrics
• +۹ مورد دیگر

Hugo Soudeyns is a Full Professor at the Faculty of Medicine , Université de Montréal, and a senior researcher at the CHU Sainte-Justine Research Center . He holds cross-appointments in both the Department of Microbiology, Infectious Diseases and Immunology and the Department of Pediatrics . Academic Affiliation: Université de Montréal Faculty of Medicine Laboratory: CHU Sainte-Justine Research Center Research Focus: His work investigates viral pathogenesis and immune responses in maternal-fetal medicine, with specific expertise in HIV-1 and Hepatitis C Virus (HCV) transmission. He examines: Vertical transmission mechanisms of HIV and HCV Immune responses in HIV-exposed uninfected children Antiviral immunity reconstitution after hematopoietic stem cell/cord blood transplantation Impact of antiretroviral therapy on immune development Viral reservoir dynamics in pediatric HIV infection Novel immunotherapeutic approaches for viral control Publications demonstrate expertise in viral evolution, immune checkpoint regulation, and perinatal virology. His scientific awards include: Prix Justine (2011) McGill Dean's Honor List (1997) CIHR Canadian HIV Research Network Young Investigator Award (1996) Supervision spans 20+ graduate students in HIV cure strategies, HCV pathogenesis, and cord blood transplantation immunology. His grants come from CIHR , FRQS , Bill & Melinda Gates Foundation , and Elizabeth Glaser Pediatric AIDS Foundation .

Berj L. Bardakjianمشاهده پروفایل

استاد

• Neural Engineering
• Computational Neuroscience
• Epilepsy Research
• +۴ مورد دیگر

Berj L. Bardakjian is a Professor in the Edward S. Rogers Sr. Department of Electrical & Computer Engineering and the Institute of Biomedical Engineering at the University of Toronto's Faculty of Applied Science and Engineering. He holds a PhD in Electrical Engineering (Biomedical Engineering Group) from McMaster University and is a Professional Engineer (PEng) registered with the Professional Engineering Association of Ontario. His educational background includes: PhD in Electrical Engineering (Biomedical Engineering Group) from McMaster University, Hamilton, Ontario, Canada Professor Bardakjian's research focuses on neural engineering and computational neuroscience, with particular emphasis on understanding electrical rhythmic activities in the brain. His work spans multiple areas including: Analysis, modeling, and control of electrical rhythmic activities in neuroglial networks Research on intractable (anti-convulsive-drug-resistant) epilepsy Studies on sudden unexpected death in epilepsy (SUDEP) Investigations into infantile spasms and Alzheimer disease Development of machine learning applications for risk assessment of neurological disorders Signal processing of nonstationary electrical signals from the brain He established the Neural Systems Lab (NSL) to elucidate the nature of neural electrical rhythmic activities in health and disease. Recent work from his lab has provided new insights into sudden unexpected death in epilepsy through advanced brain wave analysis, as reported in October 2024. His notable awards and professional recognitions include: Bionetics Outstanding Canadian Bioengineer, Canadian Medical and Biological Society, 1991 Medical Research Council (MRC) Scholar MRC Postdoctoral Fellow Professor Bardakjian has served as an advisor to numerous graduate students, including current PhD student Adam Gravitis (since 2020) and alumni including Marija Cotic (PhD, 2008-2014), Vasily Grigorovsky (PhD, 2014-2020), Mirna Guirgis (PhD, 2009-2015), Trevor Hilton (MASc, 2015-2017), and Osbert Zalay (PhD, 2006-2011). His research has received significant funding, including recent NSERC grants that provided over $500,000 to BME faculty in June 2024. He is actively involved in several professional organizations including IEEE/EMBS, Biomedical Engineering Society (BMES), and the Organization of Computational Neuroscience (OCNS). As an associate editor for the journal IEEE Transactions on Biomedical Engineering, he contributes to advancing scholarship in his field.

Steve Mannمشاهده پروفایل

استاد

• Wearable Computing
• Augmented Reality (AR)
• Digital Imaging
• +۷ مورد دیگر

Prof. Steve Mann is a tenured full professor at the University of Toronto in the Department of Electrical and Computer Engineering , Faculty of Applied Science and Engineering. He is also the Director of the EyeTap Personal Imaging (ePi) Lab and the FL_UI_D Laboratory , while serving as Chief Scientist for both the Rotman School of Management's CD Lab and Meta . Education: PhD from MIT (1997) As the inventor of wearable computing , Mann's research spans augmented reality (EyeTap) , high dynamic range (HDR) imaging , comparametric equations , and humanistic intelligence (HI) . He pioneered inventrepreneurship education and developed the hydraulophone , an instrument based on absement theory. His recent work includes the 2025 IEEE Consumer Electronics Award and 2024 Lifeboat Foundation Guardian Award , recognizing contributions to wearable tech and humanity. Scientific achievements include over 200 publications , patents , and media exhibits at institutions like MoMA and the Smithsonian. Scientific Awards: 2025 IEEE Consumer Electronics Award 2024 Lifeboat Foundation Guardian Award 2004 Leonardo Award for Excellence Coram International Sustainable Design Award (First Place) Advising and Innovation: Co-founded over $1B in tech ventures with students, integrating invention and entrepreneurship into academia. His labs explore fluid-based musical instruments and privacy-enhancing wearables . Labs & Teams: Leads the ePi Lab and FL_UI_D Lab , focusing on wearable imaging, mediated reality, and reverse kinematics in fluidic musical systems.

John Konstantine Tsotsosمشاهده پروفایل

استاد پژوهشی

• Computer Vision
• Visual Attention
• Active Vision Systems
• +۵ مورد دیگر

John Konstantine Tsotsos is a Research Professor in the Department of Electrical Engineering and Computer Science at Lassonde School of Engineering, York University . He is a member of the Centre for Innovation in Computing and the Centre for Vision Research at York, as well as an Adjunct Professor in the Department of Ophthalmology and Vision Sciences at the Temerty Faculty of Medicine, University of Toronto . Education Ph.D. in Computer Science, University of Toronto (1980), titled A Framework for Visual Motion Understanding M.Sc. in Computer Science, University of Toronto (1976) B.A.Sc. (Honours) in Engineering Science (Computer Science Option), University of Toronto (1974) Dr. Tsotsos is a world leader in interdisciplinary vision science , spanning human and computational vision . His Selective Tuning theory revolutionized visual attention research, predicting novel aspects of top-down processing in perception. Contributions include computational complexity of vision , active perception systems , and medical image analysis . His work underpins advancements in robotic vision , gaze prediction , and abnormal gait detection . His scientific awards include the Sir John William Dawson Medal (2015) , CS-Can|Info-Can Lifetime Achievement Award (2020) , and fellowships in the Royal Society of Canada (2010) , IEEE (2018) , and Canadian Academy of Engineering (2024) . He held the NSERC Tier I Canada Research Chair in Computational Vision (2003–2024) and has been cited for 1000+ research publications . Dr. Tsotsos has advised over 200 trainees (Ph.D., M.Sc., and postdocs) and shaped vision science through founding the Computer Vision Research Group at the University of Toronto (1980) and directing the Centre for Innovation in Computing at York University (2014–2024) . His patents in touch-sensitive displays and face recognition (e.g., US Patent #6,118,433) demonstrate practical applications of his research.

Gregory Hagenمشاهده پروفایل

دانشیار

• Artificial Intelligence Law
• Intellectual Property Law
• Information Security and Privacy Law
• +۴ مورد دیگر

Gregory Hagen is an Associate Professor at the Faculty of Law, University of Calgary, specializing in intellectual property law, artificial intelligence law, information security, and biotechnology law. He has served as Associate Dean (Research) and Graduate Program Director from 2014-2019 and has taught at multiple international institutions including University of Ottawa, Western University, Duke University's Asia America Institute in Transnational Law at University of Hong Kong, and Peking University. Educational Background: PhD in Philosophy of Science, University of Western Ontario LLM (Law & Technology), University of Ottawa LLB, Dalhousie University MA in Philosophy, University of British Columbia BA in Philosophy, University of British Columbia Professor Hagen's research focuses on patent law and legal issues related to artificial intelligence, information security, privacy technologies, and biotechnology. His work spans Information Technology and Internet Law (including AI, blockchain, smart contracts, and cryptocurrency), Intellectual Property Law, Information Security and Privacy Law, Biotechnology Law, and Legal Theory and Philosophy. His interdisciplinary approach bridges legal frameworks with technological advancements, particularly focusing on how emerging technologies challenge traditional legal concepts and require innovative regulatory solutions. His publications reveal a consistent focus on the intersection of law and rapidly evolving technologies, with particular attention to intellectual property frameworks. Recent works emphasize AI-related legal challenges, blockchain applications, and the regulatory complexities of synthetic biology. His scholarship shows progression from traditional copyright and patent issues toward cutting-edge concerns in AI governance, misinformation challenges, and the legal implications of decentralized technologies. The breadth of his work demonstrates expertise across both theoretical legal philosophy and practical regulatory frameworks. Professor Hagen has taught courses including Ethical Lawyering, Graduate Seminar in Legal Research & Methodology, Intellectual Property, and Legal Theory: Artificial Intelligence. His teaching reflects his research interests, with specialized courses addressing the legal implications of emerging technologies. While specific grant information isn't provided in the available text, his extensive publication record spanning multiple disciplines suggests significant research activity and likely grant funding in technology law areas.

Sebastian Fischmeisterمشاهده پروفایل

استاد

• Embedded Systems
• Distributed Systems
• Formal Methods
• +۸ مورد دیگر

Sebastian Fischmeister is a Professor and NSERC/Magna Industrial Research Chair in Automotive Software for Connected and Automated Vehicles at the Department of Electrical and Computer Engineering, University of Waterloo. His research focuses on systems at the intersection of software technology, distributed systems, and formal methods, with applications in automotive systems, avionics, and medical devices. He has pioneered frameworks for scalable location-based pervasive computing and verifiable real-time communication schedules, contributing to the ASTM F29.21 standard. Education: Dipl.-Ing. in Computer Science (Vienna University of Technology, 2000), Ph.D. in Computer Science (University of Salzburg, 2002) Research Themes: Real-time embedded systems, runtime monitoring, security analysis, data analytics for validation, and performance evaluation. Scientific Awards: APART Stipend (2005) Ontario Early Researcher Award (2014) Multiple best paper and tool awards He is an ACM Distinguished Speaker and actively participates in organizing conferences such as ESCAR, RTSS, DATE, and ICPE. His work includes significant contributions to anomaly detection, cybersecurity in automotive networks, and runtime verification techniques under unreliable conditions.

• Machine learning
• Computer vision
• Pattern recognition
• +۷ مورد دیگر

Eric Granger is a Professor in the Department of Systems Engineering at École de technologie supérieure (ETS) in Montreal, Quebec, Canada. He holds a B.Sc.A. from UQAM, and M.Sc.A. and Ph.D. from Polytechnique Montréal. Dr. Granger leads research at the LIVIA – Imaging, Vision and Artificial Intelligence Laboratory and holds the Distech Controls Research Chair on Embedded Neural Networks in a Controller for Connected Buildings. His research spans intelligent and autonomous systems with applications in health technologies. Dr. Granger's expertise includes machine learning, computer vision, pattern recognition, deep models, multimodal information fusion, domain adaptation, weakly supervised learning, and adaptive intelligent systems. His specific applications focus on face analysis and recognition, biometrics, medical imaging, affective computing, computer security, and video surveillance. Analysis of his recent publications reveals a strong focus on person re-identification across different modalities (visible-infrared), weakly supervised object localization, depression detection from facial analysis, and medical image analysis. His work consistently addresses domain adaptation challenges and develops innovative neural network architectures for real-world applications in surveillance and healthcare. Dr. Granger has supervised numerous doctoral students across various research topics including adaptive anomaly detection, signature verification, face recognition, medical image segmentation, and domain adaptation. His research is supported by multiple grants and collaborations with industry partners like Distech Controls. He leads the LIVIA research laboratory which focuses on imaging, vision, and artificial intelligence applications. The lab works on projects involving embedded neural networks for connected buildings, video surveillance systems, medical imaging applications, and affective computing solutions.

• Computer Graphics
• Physically Based Animation
• Motion Capture
• +۴ مورد دیگر

Paul G. Kry is an Associate Professor in the School of Computer Science at McGill University, where he leads the Computer Animation and Interaction Capture Laboratory. His research focuses on physically based animation, computer graphics, and human motor control, with applications in video games, movies, training simulations, ergonomics, and robotics. He teaches graduate and undergraduate courses including COMP 557 (Fundamentals of Computer Graphics) and COMP 559 (Fundamentals of Computer Animation). Dr. Kry's research interests center on computer graphics, physically based animation, skin deformations of articulated characters, motion capture, interaction, and physically based modeling of humans and animals. He investigates human and animal motor control (locomotion, grasping, manipulation) in combination with the physics of rigid objects, deformation, and contact. His work emphasizes the combination of real-world measurements, approximate models, and physically based simulation, with additional interests in machine learning, numerical methods, and audio. His recent publications demonstrate strong trends in physically based animation, with focus areas including adaptive simulation techniques, real-to-sim calibration, constraint-based physics, neural network applications in graphics, and motion control policies. His work spans both theoretical foundations and practical applications, often bridging the gap between computer graphics and robotics. BEST PAPER at Graphics Interface, 2023 BEST STUDENT PRESENTATION at ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games, 2019 BEST PAPER at Computational Aesthetics / Expressive, 2016 Dr. Kry actively supervises numerous PhD and MSc students, with many graduates going on to positions at leading companies including Ubisoft, Google, Facebook, and Autodesk. He has served on program committees for major conferences including ACM SIGGRAPH, Symposium on Computer Animation, and Graphics Interface. His lab maintains specialized equipment including a 24-camera motion capture system, force plates, consumer DSLR cameras, high-speed cameras, data gloves, quadrotor robots, and various pressure sensors.

Benoit Gosselinمشاهده پروفایل

استاد

• Wireless Implantable Electronics
• Brain-Computer Interfaces
• CMOS Microelectronic Circuits
• +۴ مورد دیگر

Benoit Gosselin , Professor at Université Laval's Department of Electrical and Computer Engineering and Canada Research Chair in Smart Biomedical Microsystems, specializes in wireless implantable electronics, brain-computer interfaces, and biomedical microsystems. He leads the Biomedical Microsystems Lab at CERVO Brain Research Centre. Education : Ph.D. in Electrical Engineering (École Polytechnique de Montréal, 2009), NSERC Postdoctoral Fellow (Georgia Institute of Technology, 2010) Research Focus : Development of wireless electro-optic platforms for neural monitoring, optogenetics, and closed-loop applications, with emphasis on CMOS circuits, energy harvesting, and multimodal biosensors. Recent Publications highlight advancements in implantable neural probes with embedded micropumps, ultra-compact UWB transmitters for neural implants, and wearable biosensors leveraging machine learning for gesture recognition and pain management. His work bridges microelectronics, neuroscience, and personalized healthcare. Scientific Awards : Fellow of the Canadian Academy of Engineering (2020) Génie Innovation Prize (Order of Engineers of Quebec, 2019) NSERC Brockhouse Canada Prize (2018) Collaborations with Doric Lenses Inc. led to commercialization of wireless optogenetics platforms. He serves as Associate Editor of IEEE Transactions on Biomedical Circuits and Systems and founded the IEEE CAS/EMB Quebec Chapter.

Hyock Ju Kwonمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Manufacturing Engineering
• +۵ مورد دیگر

Hyock Ju Kwon is a Professor in the Department of Mechanical and Mechatronics Engineering at the University of Waterloo . Active in research and teaching, he focuses on integrating Artificial Intelligence (AI) with manufacturing practices and biomedical ultrasound techniques . Doctorate in Mechanical Engineering, University of Alberta (2007) Master's in Mechanical Engineering, University of Alberta (2003) Master's in Mechanical Engineering, KAIST (1988) Bachelor's in Mechanical and Design Engineering, Seoul National University (1985) His research spans AI and machine learning , with applications in manufacturing (robotic assembly, NDT, predictive maintenance) and biomedical fields (therapeutic ultrasound, tactile neuroimaging). He leads the AI for Manufacturing Laboratory , emphasizing digital twin and multi-physics modeling . The 15 most recent articles reflect trends in AI-driven manufacturing , ultrasound diagnostic/therapeutic systems , and robotic path planning . Keywords include machine learning , medical imaging , and fluid dynamics , with subfields like predictive maintenance , nanoparticle-enhanced therapy , and topological navigation . As a Sole-Supervisory Privilege Status (SSPS) holder, he supervises graduate students. Teaching includes courses like ME 212 - Dynamics and ME 526 - Fatigue and Fracture Analysis . The AI for Manufacturing Laboratory develops cutting-edge technologies for industrial AI , collaborating with Korean municipal governments on large-scale projects. Areas include robotic assembly , non-destructive testing , and machine condition monitoring .