جست‌وجوی استاد و پژوهشگر

• Biomedical Engineering
• Digital Signal Processing
• Smart Homes
• +۶ مورد دیگر

Rafik A. Goubran is a Professor at Carleton University's Department of Systems and Computer Engineering, and currently serves as Vice-President (Research and International). He previously held roles as Dean of the Faculty of Engineering and Design and Chair of the Department of Systems and Computer Engineering. His research focuses on digital signal processing applications in biomedical engineering and audio processing, with a strong emphasis on smart environments for seniors' independent living, patient monitoring, and sensor analytics. Dr. Goubran has co-supervised 24 PhD and 72 Master’s students, authored/co-authored 70 journal papers, 260 conference papers, and 12 patents. He is a Life Fellow of the IEEE and a Fellow of the Canadian Academy of Engineering. Education: Ph.D. (Carleton University), M.Sc. and B.Sc. in Electrical Engineering (Cairo University). Key roles include co-leader of the Technology Assisted Environment for the Third Age (TAFETA) project and founder of the Ottawa-Carleton Institute for Biomedical Engineering (OCIBME). Awards include the University Senate Medal for Academic Achievement (students' work) and multiple grants. His research spans smart home technologies, patient monitoring systems, and audio signal processing for healthcare. Publications highlight innovations like unobtrusive patient monitoring via pressure sensors, respiratory rate estimation from thermal video, and AI-driven health analytics. Collaborations with institutions like Bruyère Research Institute and industry partners (e.g., Mitel, Nortel) underpin his applied research. Ongoing projects include supportive smart home systems for dementia care and AI-driven driving behavior analysis for older adults.

Sreeraman Rajanمشاهده پروفایل

استاد

• Sensors and Sensor Systems
• Compressive Sensing
• Signal Processing
• +۸ مورد دیگر

Prof. Sreeraman Rajan is a Professor and Tier II Canada Research Chair in Sensor Systems at Carleton University's Department of Systems and Computer Engineering, Faculty of Engineering and Design. He holds a Ph.D. from the University of New Brunswick and has prior experience at Defence Research and Development Canada (DRDC), Biopeak Corporation, and JDS Uniphase. His research focuses on sensors, compressive sensing, signal processing, and machine learning with applications in biomedical, defense, and security domains. Education : Bachelor’s in Electronics and Communications Engineering (Bharathiyar University, 1987) M.Sc. Electrical Engineering (Tulane University) Ph.D. Electrical and Computer Engineering (University of New Brunswick) Research Interests : Sensors and sensor systems for biomedical and defense applications Compressive sensing and signal processing techniques Machine learning and pattern classification Doppler radar-based life sign monitoring and human activity recognition Biomedical signal processing for noninvasive diagnostics Awards : Tier II Canada Research Chair (2015) IEEE MGA Achievement Award (2012) Queen Elizabeth II Diamond Jubilee Medal (2012) Outstanding Contribution Award (Defence Research and Development Canada, 2013) Grants : Tier II Canada Research Chair: $500,000 (2015-2019) Correctional Services Canada: $98,850 (2014-2015) Royal Canadian Air Force: $50,000 (2013-2015) Advising & Collaborations : Supervised over 20 graduate and undergraduate students Co-founder of multiple patents in radar and biomedical systems Active in IEEE leadership roles, including chair of IEEE Ottawa Section Labs & Teams : Conducts research in Carleton’s Systems and Computer Engineering labs, focusing on sensor systems, radar technology, and biomedical signal processing. Collaborates with DRDC, industry partners, and international researchers on defense and healthcare projects.

Carlos Rossaمشاهده پروفایل

دانشیار

• Medical Robotics
• Autonomous Systems
• Robot-Assisted Surgery
• +۵ مورد دیگر

Carlos Rossa is an Associate Professor at Carleton University's Faculty of Engineering and Design. His research focuses on medical robotics, autonomous systems, and human-robot interaction, with key contributions in robot-assisted surgery, haptic feedback systems, and image-guided interventions. He holds a Ph.D. from Sorbonne Université (UPMC) and has extensive experience in developing innovative surgical tools and training simulations. Education: Ph.D. in Engineering, Sorbonne Université (UPMC) Research Interests: Medical Robotics & Needle Steering Robot-Assisted Surgery & Imaging Haptic Feedback Systems Ultrasound & Bioimpedance Imaging Autonomous Surgical Systems His work bridges robotics, computer science, and biomedical engineering to address challenges in minimally invasive surgery and rehabilitation. Recent Work: Recent publications emphasize advancements in needle tracking algorithms, real-time tissue classification via dielectric spectroscopy, and Doppler-based motion estimation for autonomous systems. These studies highlight trends in integrating AI-driven sensor fusion and multi-modal imaging for surgical precision. Awards & Recognition: Notable contributions in IEEE journals/conferences on medical robotics. Advising & Labs: Focuses on graduate student mentorship in robotics and biomedical engineering. Labs: Medical Robotics & Surgical Simulation Lab (MRSSL) at Carleton University.

Chao Shenمشاهده پروفایل

استادیار

• Robotics Control
• Autonomous Underwater Vehicles
• Model Predictive Control (MPC)
• +۵ مورد دیگر

Dr. Chao Shen is an Assistant Professor at the Department of Systems and Computer Engineering, Carleton University, within the Faculty of Engineering and Design. His research focuses on control theory, machine learning, and optimization applied to robotics systems, autonomous underwater vehicles (AUVs), and intelligent control of mechatronic systems. He leads the Robotics Control and Optimization Laboratory and has supervised multiple capstone projects, including a winning team in the 2022 departmental competition. Dr. Shen holds a PhD from the University of Victoria. He has been appointed as a Technical Editor for IEEE/ASME Transactions on Mechatronics (2023) and Associate Editor for IEEE Canadian Journal of Electrical and Computer Engineering (2022). He also served as Technical Program Chair for the 2022 IEEE Electrical Power and Energy Conference. His research interests include perception and navigation for robotics, cooperative control of multi-agent systems, and distributed model predictive control (MPC) for large-scale systems. Notable contributions include a recently published Springer book on 'Advanced Model Predictive Control for Autonomous Marine Vehicles' (2023) and award-winning work funded by NSERC Discovery Grants. Dr. Shen actively mentors graduate and undergraduate students in topics like robust MPC for visual servoing, UAV coordination, and energy-optimal control strategies. His lab offers funded PhD and MASc positions focusing on control theory applications in robotics and autonomous systems.

Mojtaba Ahmadiمشاهده پروفایل

استاد

• Robotic analysis, design, and control
• Machine and biological locomotion
• Mechatronics
• +۵ مورد دیگر

Mojtaba Ahmadi is a Professor in the Department of Mechanical and Aerospace Engineering at Carleton University, cross-appointed within the Faculty of Engineering and Design. He holds a B.Sc. from Sharif University, an M.Sc. from the University of Tehran, and a Ph.D. from McGill University. His research focuses on robotics, mechatronics, and control systems with applications in rehabilitation, aerospace, and biologically inspired systems. Key areas include robotic locomotion, real-time control, and neuromorphic computing. He has contributed to advancements in FPGA-based neural network implementations, memristor circuits, and soft actuators. Dr. Ahmadi has served on technical committees for conferences such as CA2008, ICA2009, and CSME 2008, and organized special sessions on control applications. His work bridges theoretical models with practical hardware solutions, emphasizing interdisciplinary approaches. Publications span topics from spiking neural networks and neuromorphic vision systems to low-resource digital neuron implementations. He actively explores applications in healthcare robotics and energy-efficient computing architectures.

Paulo Garciaمشاهده پروفایل

استادیار

• Embedded Real-Time Systems
• Hardware/Software Co-Design
• FPGA Acceleration
• +۳ مورد دیگر

Paulo Garcia is an Assistant Professor in the Department of Systems and Computer Engineering at Carleton University, Ottawa, Canada. He holds a Ph.D. in Computer Engineering from the University of Minho, Portugal, with research periods at Asian Institute of Technology and University of Würzburg. His academic roles include serving as a faculty member, thesis chair/examiner, and committee member in multiple university initiatives. Research Focus: Embedded real-time systems, hardware/software co-design, FPGA acceleration, and engineering pedagogy. Specific technical areas include multicore architectures, runtime systems, and hardware accelerators for embedded applications. His work emphasizes synergies between processor architectures, compilers, and FPGA-based solutions. Teaching: Courses include SYSC 3310 (Real-Time Systems), SYSC 4310 (Computer Architecture), and SYSC 5807 (Hardware/Software Co-Design). He supervises senior projects like robotic systems and eHealth wearable devices. Awards & Grants: Includes 2020 awards from General Dynamics Mission Systems and Carleton’s Rapid Response Grant, plus multiple scholarships from FCT Portugal and EU programs. His research has been supported by industry partnerships and defense collaborations. Service: Active in academic service as a thesis evaluator, member of student mental health committees, and representative in university governance bodies. Engaged in curriculum development and embedded systems program revisions.

R. Bruce Wallaceمشاهده پروفایل

استاد مدعو

• Aging in Place Technology
• Smart Homes
• Sensors and Data Analytics
• +۴ مورد دیگر

R. Bruce Wallace is an Adjunct Professor at Carleton University's Faculty of Engineering and Design and an Adjunct Research Professor affiliated with Bruyère Health Research Institute. He serves as Executive Director of the AGEWELL National Innovation Hub (SAM3), focusing on sensors and analytics for aging in place. His expertise spans signal processing, data analytics, and healthcare technology. Dr. Wallace holds a Ph.D. from Carleton University, an M.Eng. from Carleton, and a B.E.Sc. from the University of Western Ontario, alongside a P.Eng. license and Senior Member status in IEEE. His research focuses on innovative smart home technologies to support aging populations, including sensor-based monitoring systems, cognitive health assessment, and assistive vehicle technologies. Key projects include the SAM3 initiative, which integrates multi-disciplinary teams to develop solutions for independent living. He co-authored the book *Supportive Smart Homes: Their Role in Aging in Place* and holds 24 patents in telecommunications and healthcare systems. Dr. Wallace’s work emphasizes collaboration with industry, clinical partners, and end-users to bridge technology development and real-world applications. His speaking engagements span academic, industry, and public audiences, advocating for age-friendly technology adoption. His research has been published in journals like IEEE Transactions on Instrumentation and Measurement, with a focus on sensor technologies, health monitoring, and driver safety for older adults. Current affiliations include leadership roles at SAM3, Bruyère Research, and Carleton’s ARISE Lab, where he oversees projects such as the SAM3 Smart Apartment and Virage Simulator. His contributions address ethical, legal, and policy challenges in smart home technologies, ensuring user-centered design and accessibility.

Elina Birminghamمشاهده پروفایل

دانشیار

• Autism Spectrum Disorder
• Neurodiversity
• Sound Sensitivity
• +۵ مورد دیگر

Dr. Elina Birmingham is an Associate Professor at Simon Fraser University's Faculty of Education, specializing in autism spectrum disorder (ASD) research with a focus on neurodiversity, sound sensitivity, and technology-based interventions. Her work includes five core research programs: AI-driven interventions for sound sensitivity, neurodiversity advocacy, university mentorship for autistic students, eye-tracking studies on social attention, and facial expression analysis. Funded by NSERC and Kids Brain Health Network, her research emphasizes incorporating autistic perspectives into studies. She has received the 2019 Faculty of Education Award for Excellence in Graduate Student Supervision. Dr. Birmingham teaches courses on developmental psychology and supervises graduate students in ASD and attention mechanisms. She actively participates in organizing conferences like the 'Creating Connections with the National Autism Research Center of Israel' and contributes to interdisciplinary collaborations. Her lab, the Autism and Developmental Disabilities Lab, drives innovation in assistive technologies and social inclusion initiatives for neurodiverse populations.

Mrigank Rochanمشاهده پروفایل

استادیار

• Computer Vision
• Machine Learning
• Deep Learning
• +۴ مورد دیگر

Dr. Mrigank Rochan is an Assistant Professor in the Department of Computer Science at the University of Saskatchewan. Previously, he served as a Senior Researcher in Huawei Noah's Ark Lab's Autonomous Driving Perception team. He holds a Ph.D. and M.Sc. from the University of Manitoba (2020 and 2016) and a B.Tech. from Amrita University, India (2011). His research focuses on Deep Learning applications in Computer Vision, including video highlight detection, domain adaptation, and autonomous systems perception. Notable awards include the 2020 CIPPRS John Barron Doctoral Dissertation Award and the 2024 Google PaliGemma Academic Program Award. Education Ph.D. in Computer Science, University of Manitoba, Canada (2020) M.Sc. in Computer Science, University of Manitoba, Canada (2016) B.Tech. in Computer Science and Engineering, Amrita Vishwa Vidyapeetham University, India (2011) Research Interests His work emphasizes unsupervised learning techniques, domain adaptation for autonomous systems, and multimodal learning (e.g., audio-visual fusion). Recent projects include improving LiDAR-based 3D object detection and developing adaptive crowd counting models. He explores video summarization methods and cross-modal networks for referring segmentation. Grants & Awards NSERC Discovery Grant (2024) Google PaliGemma Academic Program Award (2024) CIPPRS John Barron Doctoral Dissertation Award (2020) Advisees & Teaching He teaches CMPT 489/828: Deep Learning and CMPT 318: Data Analytics . While no named students are listed, his publications suggest active collaboration with graduate researchers like Zahidul Islam, Sujoy Paul, and Linwei Ye. Labs & Collaborations Prior work at Huawei's Autonomous Driving Perception team informs his current focus on real-world perception challenges. His lab at USask likely addresses interdisciplinary AI applications in vision systems.

Roger A. Piersonمشاهده پروفایل

استاد

• Reproductive Medicine
• Ultrasonography
• Endometrial Receptivity
• +۳ مورد دیگر

Dr. Roger A. Pierson is a University Distinguished Professor in Obstetrics and Gynecology at the University of Saskatchewan's College of Medicine. He holds advanced degrees from Purdue University and the University of Wisconsin-Madison, specializing in Reproductive Endocrinology/Physiology. His research focuses on ovarian physiology, endometrial receptivity, and AI-driven diagnostic tools in women's healthcare. Dr. Pierson pioneered ultrasonography visualization of human ovulation (1990) and contributed groundbreaking studies recognized as one of Discover Magazine's Top 100 scientific discoveries (2004). His laboratory develops imaging technologies for ovarian function assessment and endometrial analysis, with applications in infertility treatment and breast mass evaluation. He founded the Synergyne Group, commercializing Matris™ endometrial assessment software. Professional achievements include Fellowships in the European Academy of Sciences and Canadian Academy of Health Sciences, plus leadership roles such as CFAS President (1999–2000). Over 650 scientific publications and 50+ patented software solutions reflect his prolific output. Awards span clinical teaching excellence to national recognition for advancing women’s health. Research interests span follicular dynamics, hormonal contraception, and AI applications in reproductive medicine. His work bridges clinical practice with technological innovation, particularly in improving assisted reproductive technologies through imaging advancements.

Christopher Yee WONGمشاهده پروفایل

استادیار

• Human-Robot Interaction
• Robot Kinematics
• Machine Learning
• +۶ مورد دیگر

Dr. Christopher Yee WONG is an Assistant Professor in the Department of Mechanical, Industrial and Aerospace Engineering at Concordia University, Montreal, Canada. He leads the Living with Assistive and Interactive Robots (LAIR) Lab, focusing on human-robot interaction (HRI), robot kinematics, and multimodal sensing. His research aims to develop safe and intuitive robotic systems for healthcare, retail, and manufacturing environments. He holds a Ph.D. (2017) from the University of Toronto and M.Eng. (2014) and B.Eng. (2011) from McGill University. His education includes advanced robotics training, with a Ph.D. in Robotics from the University of Toronto and a B.Eng./M.Eng. in Mechanical Engineering from McGill University. His work spans physical and social HRI, including robot-to-human grasping, sensor observability analysis, and virtual reality applications. He also focuses on ethics in robotics education and has contributed to K-12 roboethics modules. Dr. Wong’s research projects include robots in retail spaces for visually impaired users, VR environments for HRI studies, and foundational work on sensor observability metrics for robotic mechanisms. His recent publications emphasize practical applications in assistive robotics and ethical considerations in technology deployment. As an educator, he employs evidence-based teaching methods, emphasizing student engagement and problem-solving. He has taught courses at Concordia and McGill, including Dynamics, Automated Manufacturing, and Control Systems, with consistently high student ratings. His teaching philosophy prioritizes guiding students to reconstruct knowledge through active learning.

Jamal Bentaharمشاهده پروفایل

استاد

• Artificial Intelligence
• Multi-Agent Systems
• Federated Learning
• +۷ مورد دیگر

Prof. Jamal Bentahar is a Professor at the Concordia Institute for Information Systems Engineering (CIISE), part of Concordia University's Faculty of Engineering and Computer Science. His research focuses on intelligent agents, multi-agent systems, federated learning, reinforcement learning, cybersecurity, and their applications in healthcare, IoT, and autonomous systems. He leads research initiatives in AI-driven medical imaging, edge-cloud computing, and blockchain-empowered distributed systems. Key research areas include: Multi-Agent Systems: Formal verification of trust and commitments, group trust modeling, and distributed decision-making Federated Learning: On-demand client/model deployment, trust-aware optimization, and privacy-preserving frameworks Medical AI: Cardiac ultrasound analysis, CPR signal processing, and robotic telemedicine systems Edge/IoT Intelligence: UAV-enabled vehicular networks, energy-efficient LoRa gateways, and fog computing optimization His work bridges theoretical foundations (e.g., multi-valued model checking) with practical applications in healthcare robotics, smart city infrastructure, and autonomous vehicle safety. Recent publications highlight innovations in transformer-based reinforcement learning, spherical topic modeling, and explainable AI for cybersecurity. Prof. Bentahar's contributions include tools like MV-Checker for multi-valued verification and frameworks like CACTUS for cardiac ultrasound analysis. He actively publishes in top venues and serves as editor for special sections on federated learning and AI applications.

Zachary Pattersonمشاهده پروفایل

استاد

• Transportation Engineering
• Data Science
• Machine Learning
• +۵ مورد دیگر

Zachary Patterson is a Professor at the Concordia Institute for Information Systems Engineering, Concordia University. His research focuses on emerging technologies in transport-related data collection, computational geospatial data processing, and the application of statistical and artificial intelligence techniques to transportation and environmental challenges. He specializes in discrete choice experiments, greenhouse gas emission prediction, and smart mobility solutions. Dr. Patterson's work integrates machine learning, graph neural networks, and geospatial analysis to address complex issues such as public transit optimization, passenger flow prediction, and environmental impact assessment. He has developed frameworks for privacy-preserving data collection and innovative solutions for on-demand transit systems. His interdisciplinary approach bridges computer science, transportation engineering, and environmental science. Notable contributions include the TMS-GNN model for traffic-aware passenger flow prediction, HydroVision for hydrometric forecasting, and frameworks for electric vehicle adoption analysis. His research often emphasizes interpretability of black-box machine learning models and the ethical use of data in urban systems. Dr. Patterson has authored over 50 publications, with a focus on transportation data analytics, sustainability, and smart cities. His work has been applied in real-world contexts such as Montreal’s transportation infrastructure and environmental policy design.

Adam Krzyzakمشاهده پروفایل

استاد

• Computer Vision
• Image Processing
• Neural Networks
• +۵ مورد دیگر

Adam Krzyzak is a Professor in the Department of Computer Science and Software Engineering at Concordia University. His research focuses on computer vision, image processing, neural networks, and pattern recognition. He has contributed extensively to the development of algorithms for tasks such as palmprint classification, face recognition, hyperspectral imagery analysis, and noise reduction in images. His work bridges theoretical foundations of machine learning with practical applications in biometric systems, medical imaging, and autonomous navigation systems. Recent studies emphasize the convergence properties of deep neural networks and the robustness of pattern recognition techniques under noisy conditions. His research spans over three decades, with a strong emphasis on combining statistical methods with deep learning architectures. Key advancements include novel approaches to feature extraction, filter-based classification, and the application of wavelet transforms in 3D data denoising. Krzyzak's contributions to conferences like the IAPR TC3 Workshop highlight his role in advancing neural network methodologies for real-world pattern recognition challenges.

Charalambos Poullisمشاهده پروفایل

استاد

• Computer Vision
• Computer Graphics
• Virtual Reality
• +۳ مورد دیگر

Charalambos Poullis is a Professor in the Department of Computer Science and Software Engineering at Concordia University. He leads the Immersive and Creative Technologies Lab and specializes in Computer Vision, Computer Graphics, and Virtual/Augmented/Mixed Reality. He currently supervises students in Computer Science (MCompSc) and PhD programs. Education: Ph.D. (specific details not provided) His research focuses on advancing immersive technologies, including applications in virtual environments and interactive systems. He maintains active collaboration through his lab and is available at charalambos.poullis@concordia.ca or poullis.org .