جست‌وجوی استاد و پژوهشگر

Vadim Geurkovمشاهده پروفایل

دانشیار

• Built-In Self-Test and Self-Repair in Reconfigurable Computing Systems
• Digital and Mixed-Signal Systems Testing and Testable Design
• Self-Diagnosis in Microprocessor Based Measurement Instruments
• +۲ مورد دیگر

Vadim L. Geurkov is an Associate Professor at the Department of Electrical and Computer Engineering, Toronto Metropolitan University. He earned an M.A.Sc. in Electrical Engineering from Georgian Technical University (1981) and a Ph.D. in Computer Engineering from the Institute of Control Sciences, Moscow (1993). Research Focus: Specializes in digital and mixed-signal systems testing, with expertise in built-in self-test/repair mechanisms, fault tolerance, error-control codes, and self-diagnosis in reconfigurable computing systems. His work bridges theoretical and applied aspects of hardware reliability. Industry Collaborations: Led projects with OCE-CCIT, MDA Space Missions Inc., NSERC, and other partners on reconfigurable processors, FPGA self-restoration, and error-control applications. Professional Affiliations: Senior IEEE member, ACM member, and licensed with the Ontario Society of Professional Engineers.

Lian Zhaoمشاهده پروفایل

استاد

• Wireless Communications
• Edge Computing
• Internet of Things (IoT)
• +۷ مورد دیگر

Lian Zhao is a Professor in the Department of Electrical, Computer and Biomedical Engineering at Toronto Metropolitan University. She holds a Ph.D. from the University of Waterloo and has been with the university since 2003. Her research focuses on wireless communications, edge computing, vehicular networks, and resource management. She is a Fellow of the IEEE and multiple professional organizations. Education: B.Sc. (Civil Aviation University of China, 1990), M.S. (Wuhan University, 1993), Ph.D. (University of Waterloo, 2002), all in electrical engineering. Research Interests include green communication, IoT, centralized/distributed resource management, and incentive mechanisms. She leads the Intelligent Communication and Computing Laboratory and teaches courses such as Digital Communications and Random Processes. Awards include the IEEE VTS Best Land Transportation Paper Award (2016 and 2024), Outstanding New Leader Award (2021), and CFI New Opportunity Award (2004). She serves as an editor for multiple journals, including IEEE Transactions on Wireless Communications and IEEE Internet of Things Journal. Advising: Supervised over 30 graduate students, including Ph.D. and Master’s candidates in areas like vehicular networks, edge computing, and resource allocation. Active in funded research projects on 6G networks, UAV communications, and smart grid systems. Labs/Teams: Leads the Intelligent Communication and Computing Lab, contributing to innovations in vehicular ad-hoc networks, IoT, and green communication technologies.

Pin-Han Hoمشاهده پروفایل

استاد

• Wireless Communications
• Quantum Communications
• Unmanned Aerial Vehicles (UAV)
• +۴ مورد دیگر

Pin-Han Ho is a Professor at the University of Waterloo's Department of Electrical and Computer Engineering (ECE), part of the Faculty of Engineering. His research focuses on advanced wireless communication systems, including Near-Field Communications (NFC), Reconfigurable Intelligent Surfaces (RIS), and Quantum Key Distribution (QKD). He explores applications in UAV-enabled networks, IoT security, and energy-efficient trajectory planning for autonomous systems. His work integrates machine learning techniques such as Deep Reinforcement Learning (DRL) and Graph Neural Networks (GNN) to address challenges in signal processing, resource allocation, and network optimization. Key contributions include beamforming design for dynamic environments, secure resource management in optical networks, and hybrid communication systems combining near-field and far-field capabilities. Dr. Ho's publications span over 50 peer-reviewed articles, emphasizing interdisciplinary approaches to modern communication challenges. Notable areas include UAV trajectory optimization, quantum CNN-based detection systems, and connectivity-preserving routing algorithms. His research has been featured in special issues on NFCs, quantum networks, and IoT security. Despite extensive contributions, no academic awards or grants are explicitly listed in the provided information. His advising role and lab affiliations remain unspecified in the text.

Fantahun M. Defershaمشاهده پروفایل

استاد

• Manufacturing system analysis
• Flexible and cellular manufacturing systems
• Reconfigurable manufacturing systems
• +۷ مورد دیگر

Fantahun M. Defersha is a Full Professor in the Department of Mechanical and Industrial Engineering at the University of Guelph, Ontario, Canada. He holds a PhD in Mechanical Engineering from Concordia University (2006) and has over 28 years of academic experience, including roles as Area Head in Mechanical Engineering. His research focuses on manufacturing systems optimization, cellular manufacturing, supply chain modeling, meta-heuristics, and parallel computing applications. Education: B.Sc. Mechanical Engineering (1995), Addis Ababa University MEng. Mechanical Engineering (2000), University of Roorkee (IIT Roorkee) PhD Mechanical Engineering (2006), Concordia University Research Interests: Manufacturing system analysis, flexible/cellular manufacturing systems, reconfigurable manufacturing systems, supply chain optimization, meta-heuristics, parallel computing, and additive manufacturing sustainability. His work integrates computational methods like genetic algorithms and machine learning to solve complex industrial problems. Publications: Over 50 peer-reviewed journal articles, emphasizing sustainable manufacturing, optimization algorithms, and industrial systems. Recent work includes hybrid machine learning approaches for additive manufacturing and cloud-based digital twin systems. Honors: Campaign for a New Millennium Graduate Scholarship (2004–2005) Concordia University International Tuition Fees Remission Award (2004–2005) Concordia University Graduate Fellowship (2004–2005) Teaching & Advising: Taught over 25 courses, including Optimization in Engineering, Discrete Event Simulation, and Manufacturing Systems Design. Actively advises graduate students in mechanical and industrial engineering. Current research funding includes NSERC grants for Industry 4.0 integration and digital twin technologies. Labs/Teams: Leads research on smart manufacturing systems, digital twins, and sustainable production processes through collaborations with industry partners like AVL Manufacturing Inc.

Waguih ElMaraghyمشاهده پروفایل

استاد

• Manufacturing Engineering
• Industrial Engineering
• Systems Engineering
• +۳ مورد دیگر

Waguih ElMaraghy is a Professor at the University of Windsor's Faculty of Engineering, specializing in the Department of Mechanical, Automotive, and Materials Engineering. He is a renowned academic with notable contributions to manufacturing systems, reconfigurable robotics, and Industry 4.0 technologies. ElMaraghy holds prestigious fellowships from the Canadian Academy of Engineering and the Society of Manufacturing Engineers (SME), and actively serves on professional boards like the Canadian Engineering Accreditation Board. His research focuses on advanced manufacturing paradigms, including digital twin frameworks, supply chain resilience, and cognitive manufacturing systems. He has pioneered work on adaptable assembly lines and fault detection systems, integrating machine learning into manufacturing processes. His cross-disciplinary efforts extend to biomedical applications, such as using deep learning for breast cancer biomarker identification. ElMaraghy has been honored for over three decades of volunteer service to Professional Engineers Ontario and the American Society of Mechanical Engineers (ASME). His work on sustainable supply networks and reconfigurable machinery has shaped modern industrial practices, particularly in automotive framing systems for vehicles like GO trains. Awards: Ontario Volunteer Service Award, SME College of Fellows, Canadian Academy of Engineering Fellow Key Roles: Former Head of Industrial and Manufacturing Systems Engineering, Board Member of Canadian Engineering Accreditation Research Themes: Industry 4.0, Digital Twins, Supply Chain Resilience, Biomedical Applications of AI

David Rokebyمشاهده پروفایل

استادیار

• New Media Art
• Interactive Installations
• Digital Surveillance
• +۳ مورد دیگر

David Rokeby is an Assistant Professor (Teaching Stream) at the University of Toronto and Director of the BMO Lab. He is an internationally renowned new media artist with a 40-year career examining human relationships with digital systems, focusing on surveillance, artificial intelligence, and interactive installations. 2018-2019 JHI Artist-in-Residence (Jackman Humanities Institute) Representation: Pari Nadimi Gallery Education : BFA in Experimental Art, Ontario College of Art (1984) His research explores critical intersections of technology and humanity , including automated surveillance systems , computer vision limitations , and philosophical differences between human/machine intelligence . Works like Very Nervous System (1982-) pioneered gesture-to-sound translation, while Sorting Daemon (2003) critiques algorithmic profiling. Article analysis reveals consistent engagement with interactive systems , digital ethics , and perception studies across his publications. Recent projects examine tactile virtuality and spatiotemporal relationships in digital environments. Scientific Recognition : First BAFTA Award for Interactive Art (2000) World Technology Award for the Arts (2004) Prix Ars Electronica Golden Nica (2002) First Petro-Canada Award for Media Arts (1988) His work has received continuous funding from Canada Council for the Arts and Ontario Arts Council , with permanent installations in major institutions including London Science Museum and Technopolis Brussels. Collaborations span Le Fresnoy Studio National des Arts Contemporains and Wood Street Galleries .

Parminder Singh Kangمشاهده پروفایل

دانشیار

• Supply Chain Management
• Machine Learning
• Artificial Intelligence
• +۵ مورد دیگر

Dr. Parminder Singh Kang serves as Associate Professor in the Department of Decision Sciences at MacEwan University's School of Business, specializing in supply chain optimization through advanced analytics and machine learning. His cross-disciplinary research integrates people, process, and technology elements to solve complex industrial and service operations challenges. Education: PhD from De Montfort University M.Sc. from De Montfort University Dr. Kang's research centers on applying AI/ML, combinatorial optimization, and simulation modeling to enhance supply chain resilience and customer-centric service systems. His work bridges theoretical frameworks with industry applications, focusing on sustainable digitization, risk profiling, and process improvement through evolutionary algorithms and Lean/Six Sigma methodologies. Recent projects address circular economy integration and Service 4.0 transformation. His publication portfolio reveals strong trends in machine learning applications for supply chain risk analysis, text mining for competency mapping, and digital twin development for customer-centric operations. The research spans theoretical models like HI-TOP to practical case studies on pandemic disruptions and ERP implementation, demonstrating industry-relevant academic contributions. Scientific Awards: Best Paper Award, Administrative Sciences Association of Canada (2018) Horace Pops Medal Award, Wire Cable Conference (2015) Dr. Kang supervises senior student independent studies while teaching business intelligence, machine learning, and supply chain management courses at undergraduate, graduate, and MBA levels. His research is funded by NSERC, MITACS, Alberta Innovates, and industry partners including Fluor Canada, Apana Technologies, and the City of Calgary, supporting projects valued at over $2M annually. He leads collaborative research with Panjab University, CPA Canada, and TATA Steel Europe, focusing on supply chain digitization and process optimization. His work with UK-based SMEs and Canadian organizations drives practical implementation of analytics frameworks in real-world operational environments.

Tri Nhu Doمشاهده پروفایل

استادیار

• Wireless Communications
• Artificial Intelligence
• Machine Learning
• +۶ مورد دیگر

Dr. Tri Nhu Do is an Assistant Professor in the Department of Electrical Engineering at Polytechnique Montréal, where he conducts cutting-edge research at the intersection of wireless communications and artificial intelligence. His academic journey spans institutions across Vietnam, South Korea, the United States, and Canada, bringing a global perspective to his work. Dr. Do is affiliated with the Advanced Microwave and Space Electronics Research Center (POLY-GRAMES) and contributes to the 'New Frontiers in Information and Communications Technologies' center of excellence. Dr. Do's research focuses on wireless communications systems, artificial intelligence applications in telecommunications, and integrated sensing and communication technologies. His work addresses critical challenges in next-generation wireless networks, particularly in security, resource allocation, and performance optimization. Recent research demonstrates a strong emphasis on applying deep learning, generative AI, and federated learning techniques to solve longstanding problems in wireless communications. His publication record shows remarkable productivity and impact, with numerous articles in top IEEE journals including IEEE Transactions on Communications, IEEE Transactions on Vehicular Technology, and IEEE Communications Letters. The research trends indicate a strategic shift toward integrating AI with traditional communication theory, particularly in security applications, reconfigurable intelligent surfaces, and UAV communications. Dr. Do teaches advanced courses in signal detection and estimation, communication theory, and digital transmission, sharing his expertise with the next generation of electrical engineers. His teaching reflects his research interests, providing students with both theoretical foundations and exposure to cutting-edge developments in the field.

Sébastien Le Digabelمشاهده پروفایل

استاد

• Operations Research
• Mathematical Optimization
• Black-box Optimization
• +۵ مورد دیگر

Sébastien Le Digabel is a Full Professor in the Department of Mathematics and Industrial Engineering at Polytechnique Montréal. He holds affiliations with GERAD (Groupe d'études et de recherche en analyse des décisions) and IVADO (Institut de valorisation des données), where he contributes to research in optimization and artificial intelligence. Professor Le Digabel's research focuses on black-box optimization and derivative-free methods, particularly the Mesh Adaptive Direct Search (MADS) algorithm. His work spans three main areas: development of optimization methods, application to engineering problems, and development of optimization software. He has made significant contributions to extending MADS for constrained optimization, mixed-variable problems, multiobjective optimization, and stochastic optimization. His recent publications (2023-2025) demonstrate continued innovation in handling complex optimization challenges including categorical variables, hierarchical constraints, and multi-fidelity approaches. These works appear in top journals like Computational Optimization and Applications, SIAM Journal on Optimization, and Optimization and Engineering. Professor Le Digabel actively supervises graduate students, having completed 8 PhD theses and 10 Master's theses with topics spanning multiobjective optimization, hyperparameter tuning, smart grid applications, and power systems optimization. His research is supported by diverse funding sources including NSERC, FRQNT, InnovÉÉ, IVADO, Hydro-Québec, Rio Tinto, and Huawei-Canada, reflecting the broad applicability of his work across academic and industrial domains. Professor Le Digabel leads the NOMAD Research Group and is the primary developer of the NOMAD optimization software, which implements the MADS algorithm and serves as a standard tool in the derivative-free optimization community. The software is available at www.gerad.ca/nomad and continues to evolve with new capabilities for challenging optimization problems.

Felipe Gohring de Magalhaesمشاهده پروفایل

استادیار

• Integrated circuits
• Microelectronics
• Computer systems organization
• +۷ مورد دیگر

Felipe Gohring de Magalhaes is an Assistant Professor in the Department of Computer Engineering and Software Engineering at Polytechnique Montréal, where he has been working since July 2018 and assumed his current position in October 2024. He holds a dual doctorate from PUC-RS (Brazil) and Polytechnique Montréal (2016), with degrees in both computer science and computer engineering. His research spans embedded system architectures, real-time systems, avionics, and cybersecurity for emerging technologies. He is affiliated with the Microelectronics and Microsystems Research Group and the Multidisciplinary Institute for Cybersecurity and Cyber Resilience, reflecting his focus on integrated circuits, microelectronics, and system security. Professor Gohring de Magalhaes has published over 40 articles in international journals and conferences, with recent work focusing on photonic integrated circuits security, optical neural networks, and post-quantum cryptography for avionic systems. His publication trend shows consistent output with increasing focus on security aspects of emerging computing technologies. He has supervised at least one PhD student to completion and teaches courses including Introduction to Programming and Operating System Kernel. His research interests align with NSERC topics in integrated circuits, microelectronics, computer systems organization, and VLSI systems.

François-Raymond Boyerمشاهده پروفایل

دانشیار

• Computer Architecture
• VLSI Systems
• Microelectronics
• +۴ مورد دیگر

François-Raymond Boyer is an Associate Professor in the Department of Computer Engineering and Software Engineering at Polytechnique Montréal. He holds a B.Sc. and Ph.D. from Université de Montréal and teaches courses in programming and digital audio. His research spans: Computer architecture and VLSI systems Network processing and traffic management Digital audio signal processing Hardware acceleration and optimization He is affiliated with ReSMiQ (Strategic Cluster for Microsystems) and OICRM (Music Research Observatory). Recent publications focus on 5G network processing, modular programming frameworks, and high-speed traffic management architectures, primarily in IEEE Access and IEEE Transactions on VLSI Systems. Professor Boyer has supervised 3 PhD and 6 Master's students, with research topics including network architecture, audio processing, and hardware design. No scientific awards are mentioned in the available records.