Find Academic Supervisors

Md. Zoheb HassanView profile

Assistant Professor

• Spectrum sharing and management
• Wireless communication systems
• Communications and network control and regulation systems
• +1 more

Md. Zoheb Hassan serves as an Assistant Professor in the Department of Electrical Engineering and Computer Engineering at Laval University, where he leads cutting-edge research in wireless communications and spectrum management. His academic role includes graduate recruitment and active participation in the university's research ecosystem, particularly through the Establishment of the Next Generation of Professors program funded by FRQNT. Dr. Hassan's research centers on spectrum sharing and management, wireless communication systems, and communications network control systems. He pioneers the integration of digital twin technology and machine learning to solve critical challenges in next-generation networks, including interference management in 5G/6G aerial corridors, Internet of Vehicles, and satellite-terrestrial integration. His work emphasizes practical implementations such as proof-of-concept demonstrations for tactical networks and proactive resource allocation in dynamic environments. Analysis of his 2024-2025 publications reveals a dominant trend toward AI-driven wireless resource optimization, with 12 of 15 recent papers featuring digital twins for interference management, spectrum sharing, and energy efficiency. Key thematic clusters include vehicular communications (4 papers), underwater IoT networks (2 papers), and hardware-impairment resilient designs (3 papers), demonstrating his focus on bridging theoretical advances with real-world deployment challenges across diverse network topologies. Dr. Hassan has secured significant competitive funding for his research initiatives: Digital Twin-Enhanced Interference Management for Next-Generation Radio Access Networks in the FR3 Band (FRQNT, 2025-2027) Center for Radio Frequency and Communications Systems, Technologies and Applications (FRQNT, 2024-2030) Context-Aware Spectrum Sharing and Management for Next Generation Wireless Networks (NSERC, 2024-2029) Development of innovative technologies for modeling predictive systems in urban mobility (MITACS, 2022-2026) Springboard to Discovery supplement for Context-Aware Spectrum Sharing (NSERC, 2024-2025) He actively mentors doctoral candidates, currently supervising Mahima Karim (PhD in Electrical Engineering, expected 2025) and Mohammadamin Parhizgar (PhD in Electrical Engineering, expected 2024). His supervisory approach combines theoretical rigor with practical problem-solving, focusing on spectrum management algorithms and digital twin implementations for next-generation networks. While specific laboratory affiliations aren't detailed in the source material, his projects indicate strong alignment with Laval University's wireless research infrastructure and the Center for Radio Frequency and Communications Systems.

Inna SharfView profile

Professor

• Dynamics and Control
• Space Robotics
• Unmanned Aerial Vehicles (UAVs)
• +3 more

Inna Sharf is a Professor at the Department of Mechanical Engineering, Faculty of Engineering, McGill University. She is affiliated with the Aerospace Mechatronics Laboratory, focusing on dynamics, control, and robotics. Her work spans space robotics, UAVs, forestry automation, and multibody systems. Ph.D., University of Toronto B.ASc., University of Toronto Her research interests include: Dynamics and control of robotic systems Space robotics for debris removal and on-orbit servicing Unmanned aerial vehicles (quadrotors, indoor airships) Forestry robotics for tree-harvesting automation Multibody dynamics and contact modeling Recent publications emphasize: Control algorithms for quadrotors and UAV swarms De-orbitation strategies using natural resonances Motion planning under dynamic constraints Thermalling and energy-efficient flight for gliders Collaborative payload transport and adaptive control Tether and net-based debris capture systems

Kangkang YinView profile

Associate Professor

• Computer Animation
• Computer Graphics
• Humanoid Robotics
• +3 more

Kangkang Yin is an Associate Professor in the School of Computing Science at Simon Fraser University (SFU). His research focuses on computer animation, computer graphics, humanoid robotics, machine learning, and multimedia analysis. He teaches courses such as Computer Animation and Scientific Computing, and holds a PhD from the University of British Columbia (2007), MSc from Zhejiang University (2000), and BSc from Zhejiang University (1997). His work bridges robotics and animation through projects like physics-based character controllers, motion diffusion models, and robotic manipulation. Key contributions include the SIMBICON biped locomotion framework and research into emotion-driven dance animation. Recent efforts emphasize reinforcement learning applications in motion synthesis and robust visual navigation for unmanned ground vehicles. Yin's publications span over two decades, addressing challenges in motion control, physics-based simulation, and machine learning applications. His lab contributes to both academic advancements and practical robotics solutions. Current research trends show strong emphasis on combining generative AI with traditional animation techniques, as seen in recent work on auto-regressive motion models (AAMDM) and physics-augmented reinforcement learning (PARC).

• Stochastic Optimization
• Chance Constrained Optimization
• Distributionally Robust Optimization
• +9 more

Professor Abdel Lisser is affiliated with CentraleSupélec, where he conducts research in Gif-sur-Yvette, France. His work spans multiple disciplines including stochastic optimization, game theory, and machine learning. Research Interests: Stochastic Optimization, Chance Constrained Optimization, Distributionally Robust Optimization, Stochastic Game Theory, Physics-Informed Neural Networks. His recent publications focus on integrating stochastic programming with deep learning frameworks to address complex optimization problems under uncertainty. Key areas include Markov Decision Processes, joint chance constraints, and applications in autonomous vehicle control and network design. In 2025, he published on single-controller stochastic games, convex approximations for Markov processes, and physics-informed neural networks for nonlinear equations. 2024 contributions include distributionally robust Markov decision processes, neurodynamic optimization, and CNN-based equilibrium prediction in games. Email: abdel.lisser@l2s.centralesupelec.fr Institution: L2S, CentraleSupélec Location: 3 rue Joliot Curie, 91190 Gif-sur-Yvette, France

George ShakerView profile

Adjunct Associate Professor

• Wireless Sensor Technologies
• Biomedical Engineering
• Antennas and Propagation
• +5 more

George Shaker is an Adjunct Associate Professor in the Department of Electrical and Computer Engineering at the University of Waterloo, Canada, and Lab Director of the Wireless Sensors and Devices Laboratory at the Schlegel-UW Research Institute for Aging. He is also Chief Scientist at Spark Technology Labs. His research focuses on wireless sensor technologies for healthcare, autonomous systems, and IoT. He earned his bachelor's from Cairo University and master's/PhD from the University of Waterloo. Education: Bachelor’s degree, Cairo University, Egypt Master’s degree, University of Waterloo, Canada PhD, University of Waterloo, Canada Research Interests: Dr. Shaker’s work spans advanced wireless sensor systems for healthcare monitoring, UAVs, and automotive applications. His lab developed the MIRADA initiative for aging populations and pioneered radar-based non-invasive glucose monitoring. Key areas include mm-wave radar, antenna design, bioelectromagnetics, and machine learning integration. He has co-authored over 200 publications and holds 35+ patents, collaborating with companies like Google, Apple, and Toyota. Recent Article Trends: His 2025 work emphasizes AI-driven radar systems for activity recognition, bio-sensing metasurfaces, and UAV classification using digital twins. Projects include 4D radar imaging, low-cost milk quality monitoring, and smart furniture for cardiac health. Awards: IEEE AP-S Best Paper Award IEEE MTT-S Graduate Fellowship arXiv Top Downloaded Medical Article URSI Young Scientist Award Multiple student awards (see full list above) Advising & Grants: He advises graduate students in ECE and has led projects funded by NSERC and industry partners. His students have won Velocity Fund, NASA Tech Briefs, and Canadian Space Agency awards. Collaborates with over 40 companies including Amazon, Microsoft, and Medella Health. Labs & Initiatives: Leads the Wireless Sensors & Devices Lab and co-founded MIRADA, a smart apartment for aging healthcare. Active in Spark Labs for wireless innovation.

Andreas K AthienitisView profile

Professor

• Solar Energy Engineering
• Energy Efficiency
• Building Simulation and Optimization
• +6 more

Andreas K Athienitis is a Professor at Concordia University in the Department of Building, Civil, and Environmental Engineering. He serves as Director of the Centre for Zero Energy Building Studies and has held prestigious roles including NSERC/Hydro Québec Industrial Research Chair (2006-2024) and Scientific Director of two NSERC strategic networks. Education: Ph.D. in Mechanical Engineering (University of Waterloo, 1985), B.Sc. in Mechanical Engineering (University of New Brunswick, 1981) Honors: Fellow of the Canadian Academy of Engineering, ASHRAE, and IBPSA His research focuses on energy-efficient buildings, solar energy integration, and predictive control systems. Key projects include Canada’s first net-zero energy institutional building (Varennes Library) and innovative BIPV/T systems. He has developed internationally unique facilities like the Solar Simulator and Environmental Chamber. Recent publications emphasize energy flexibility, predictive control, and renewable integration. His work bridges theoretical modeling with experimental validation, targeting climate resilience and decarbonization. Scientific Awards: Concordia Research Award (2010) NSERC-ADRIQ Celebrate Partnerships Award (2012) Willis H. Carrier Best Paper Award (1991) Multiple Fellowships and Scholarships Grants: Over $30M as P.I., including $123M CFREF grant (2022-2023)

Mikael EklundView profile

Professor

• Autonomous Systems
• Nonlinear System Identification and Control
• Health Informatics
• +3 more

Dr. Mikael Eklund is a Professor in the Department of Electrical, Computer and Software Engineering at Ontario Tech University, within the Faculty of Engineering and Applied Science. He holds a PhD (2003), MSc (1996), and BSc (1989) in Electrical and Computer Engineering from Queen’s University. His research focuses on Autonomous Systems , Nonlinear System Identification and Control , Health Informatics , and Pervasive and Mobile Computing . He has expertise in medical image processing, robotic vehicles, and smart sensors for assisted living. Education and Work Experience : - PhD (Electrical and Computer Engineering), Queen’s University (2003) - MSc and BSc from Queen’s University (1996, 1989) - Visiting Postdoctoral Scholar at UC Berkeley (2003–2006) - Adjunct Assistant Professor at Queen’s University (2003) - Former Teaching Fellow at Queen’s University (1996–2001) - Industrial experience in flight control system engineering (CAE Inc., 1989–1996) Research Contributions : - Developed SensorNet, a wireless infrastructure for assisted living. - Advanced methods for nonlinear system identification in chemical processes and aerospace systems. - Pioneered real-time UAV safety protocols and model predictive control algorithms for aerial pursuit-evasion games. - Explored EMG signal processing for hand force estimation and MEG signal source localization in neuroscience. Teaching and Outreach : - Teaches courses like Medical Image Processing and Electric Circuits. - Active in interdisciplinary projects like the ITALH initiative for elder tech integration. - Presented at conferences such as IEEE EMBC, ACC, and CDC, emphasizing healthcare IT and autonomous systems.

Alan WassyngView profile

Professor

• Software Engineering
• Formal Methods
• Safety-Critical Systems
• +6 more

Alan Wassyng is a Professor in the Department of Computing and Software at McMaster University's Faculty of Engineering. With over four decades of academic contributions, he specializes in formal methods, safety-critical systems, and software assurance cases. Key research intersections: Automotive software safety Medical device software certification Cyber-physical systems engineering Model-driven development with domain experts His scholarly work emphasizes rigorous methodologies for software verification, particularly through tabular expressions and Workflow+ models. Recent projects include a $2M GM Canada partnership to advance automotive safety systems. Teaching leadership spans interdisciplinary capstone projects in biomedical engineering, covering software design, safety-critical development, and mechatronics applications.

Joshua MarshallView profile

Associate Professor

• Robotics
• Field Robotics
• Mobile Robotics
• +5 more

Joshua Marshall is an Associate Professor in the Department of Electrical and Computer Engineering at Queen's University, cross-appointed to Mechanical and Materials Engineering. He serves as Interim Director of Ingenuity Labs Research Institute and leads the Offroad Robotics research group (formerly Mining Systems Laboratory). Previously, he held positions at Carleton University and MDA, Inc. Education: PhD in Electrical and Computer Engineering, University of Toronto (specializing in systems control) Research Interests: Dr. Marshall specializes in field robotics for mining, space, and industrial applications. His work integrates control systems engineering , localization and mapping , and mechatronics to develop autonomous solutions for harsh environments. Key focus areas include mobile robot navigation, sensor fusion, and real-world deployment challenges in underground and extraterrestrial settings. Publication Trends: His 2022-2025 publications reveal dominant themes in autonomous industrial vehicle control (motor graders, excavators), marine robotics (uncrewed surface vessels), and terrain/material classification . Work consistently combines model predictive control with machine learning (Gaussian processes, reinforcement learning) for dynamic environment adaptation. Multi-robot systems and simulation-to-real transfer represent emerging research directions. Professional Recognition: Senior Member of IEEE Associate Editor, IEEE Control Systems Society Conference Editorial Board Senior Editor, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Research Impact: Dr. Marshall's Offroad Robotics group develops technologies featured in the Canada Science and Technology Museum's 'From Earth to Us' exhibit. His work bridges academic research with industry applications through collaborations with MDA and international institutions like Örebro University, though specific grant details are not provided in source materials. Leadership: He directs both the Offroad Robotics research group and Ingenuity Labs Research Institute, fostering interdisciplinary innovation in robotics, autonomous systems, and intelligent technologies for real-world implementation in mining, space exploration, and environmental monitoring.

Walter LuciaView profile

Associate Professor

• Secure and Resilient Control of Cyber-Physical Systems
• Model Predictive Control for Autonomous Vehicles
• Cybersecurity in Control Systems
• +3 more

Dr. Walter Lucia is an Associate Professor at the Concordia Institute for Information Systems Engineering, Concordia University. His research focuses on secure and resilient control of cyber-physical systems and model predictive control strategies for autonomous vehicles. He supervises MASc and PhD students in programs such as Information Systems Security, Electrical and Computer Engineering, and Information and Systems Engineering. His research interests encompass cybersecurity in control systems, including strategies against false data injection and setpoint attacks. He develops resilient control architectures and applies model predictive control to autonomous systems like self-driving cars and mobile robots. Recent work emphasizes data-driven safety mechanisms, encrypted control systems, and collision-free platooning of mobile robots. No scientific awards or grants are explicitly mentioned in the provided text. Dr. Lucia's advising roles include overseeing multiple graduate programs, though specific student names are not listed. His publications reflect a strong focus on control theory applications, cyber-physical system security, and optimization techniques. Labs or collaborative teams are not explicitly detailed in the text, but his research themes suggest involvement in interdisciplinary projects at the intersection of engineering and cybersecurity.

Berker BilginView profile

Assistant Professor

• Electric Machines
• Power Electronics
• Energy Conversion Systems
• +4 more

Dr. Berker Bilgin is an Assistant Professor in the Department of Electrical & Computer Engineering at McMaster University. His research focuses on next-generation electric motor drive technologies, including acoustic noise reduction, power electronics, and sustainable electrification. He leads projects sponsored by Fiat Chrysler Automobiles (FCA) and Automotive Partnership Canada (APC), and co-founded a university spin-off company. He teaches courses such as Electric Motor Drives and Switched Reluctance Machine Design. Research Focus: Electric motor drives (46% of global electricity demand), hybrid-electric powertrains, and transportation electrification. His work emphasizes high-efficiency, low-cost solutions and acoustic noise modeling for high-power-density applications like traction motors. He has 10 patents and authored a textbook on Switched Reluctance Motor Drives. Publications Trends: Recent work spans advanced motor designs, acoustic noise mitigation, and thermal/structural modeling of electric machines. Key themes include switched reluctance motor optimization, PWM control strategies, and multi-physics design approaches. Awards: Patented inventions in switched reluctance technology, textbook authorship Grants: FCA/APC-funded hybrid-electric powertrain development Labs/Teams: McMaster University spin-off company for technology commercialization

• Generative Programming
• Model-Based Development
• Software System Families
• +7 more

Krzysztof Czarnecki is a Professor at the University of Waterloo's Department of Electrical and Computer Engineering, with a cross-appointment to the School of Computer Science. He serves as leader of the Waterloo Intelligent Systems Engineering Lab and holds the title of University Research Chair. His research focuses on generative software development, model-driven engineering, and autonomous systems, particularly in automotive cybersecurity and perception safety. Education: Doctorate in Computer Science, Technical University of Ilmenau (1999) Master of Science in Computer Science, Technical University of Ilmenau (1995) Bachelor of Science in Computer Science, California State University (1994) Research Interests: Dr. Czarnecki's work spans generative programming, software product lines, and safety-critical AI for autonomous vehicles. Recent projects address robust perception systems, uncertainty quantification in neural networks, and strategic driving behavior modeling. He co-authored Generative Programming (Addison-Wesley, 2000), a foundational text in the field. Publications Trends: Recent work emphasizes multimodal AI integration (e.g., LEO-MINI), 3D object detection improvements (OV-SCAN), and safety assurance frameworks for autonomous systems. His research bridges theoretical software engineering with applied robotics challenges. Awards: Premier’s Research Excellence Award (2004) British Computing Society’s Upper Canada Award (2008) University Research Chair, University of Waterloo (2023) Teaching & Leadership: Teaches courses like ECE 495 (Autonomous Vehicles) and ECE 651 (Software Engineering Foundations). Oversees WatCAR initiatives and collaborates on industry projects through the NSERC Bank of Nova Scotia Industrial Research Chair (previous). Labs & Teams: Directs the Waterloo Intelligent Systems Engineering Lab, focusing on AI-driven solutions for autonomous systems and safety-critical software. Active in cross-disciplinary collaborations with automotive and robotics partners.

Eunsik KimView profile

Professor

• Ergonomics
• Biomechanics
• Human Factors Engineering
• +5 more

Eunsik Kim is a Professor at the University of Windsor , holding a position in the Department of Mechanical, Automotive, and Materials Engineering within the Faculty of Engineering . His research focuses on ergonomics, occupational safety, and biomechanics, with applications in automotive design, workplace safety, and human-machine interaction. He leads the Occupational Safety and Ergonomics research lab , where students explore real-world solutions for challenges such as driver fatigue, musculoskeletal risks in manual labor, and automation in agriculture. Key research interests include: Ergonomics : Optimizing workstation designs, automotive seating, and anti-vibration tools Biomechanics : Analyzing human posture, musculoskeletal loading, and workplace ergonomics Machine Learning : Developing AI-driven systems for posture recognition, workload prediction, and task automation Autonomous Vehicles : Investigating human factors in driving automation and takeover scenarios Education Innovation : Gamification in engineering labs to enhance student motivation and learning Collaborations include projects with Ewha Womans University (South Korea) on autonomous vehicle comfort and a prototype robotic system for mushroom harvesting. His work often bridges theoretical research with practical applications, addressing both industry and academic challenges. Awards and Recognition: Students Ilfeoma Michael and Elnaz Akhavan Rezaee received accolades at the Association of Canadian Ergonomists conference for their lab research Advising and Grants: Professor Kim mentors students in interdisciplinary projects, focusing on ergonomics, robotics, and AI. His research has led to innovations in workplace safety and automated systems, supported by institutional and collaborative funding. Labs/Teams: The Occupational Safety and Ergonomics Lab and partnerships with South Korean institutions drive cutting-edge studies in automotive safety, robotics, and human factors engineering.

Kemal TepeView profile

Professor

• Vehicular Networks
• Cognitive Radio
• Wireless Communication
• +6 more

Professor Kemal Tepe is a faculty member in the Faculty of Engineering at the University of Windsor, specializing in wireless communication and information processing. His research focuses on vehicular networks, cognitive radio systems, and smart grid technologies. He leads the Wireless Communication and Information Processing Lab , where he develops solutions for autonomous driving systems, cybersecurity in vehicle-to-infrastructure communication, and spectrum sensing techniques. In 2016, he was awarded the Medal of Excellence by the Faculty of Engineering for his dedication and service. Tepe’s work bridges theoretical advancements and practical applications, addressing challenges in autonomous systems, machine learning for anomaly detection, and IoT security. His contributions include pioneering methods for detecting adversarial behavior in vehicular networks and improving spectrum utilization through probabilistic modeling. Collaborations with industry partners like Ford Motor Company and involvement in initiatives such as the Perspective Magazine automotive research highlight his industry-relevant research. His research interests span a wide range of domains including: Autonomous vehicle safety and communication protocols Cognitive radio networks and spectrum management Machine learning for network security and anomaly detection Wireless sensor networks and energy-efficient protocols Smart grid integration and communication architectures Tepe’s publications emphasize practical implementations, such as real-time routing protocols for wireless sensor networks and hardware designs for cognitive radio systems. His lab’s innovations have been showcased in industry-relevant platforms, demonstrating the real-world impact of his work.

George MannView profile

Professor

• Intelligent Control
• Robotics
• Machine Vision
• +6 more

George Mann is a Professor at Memorial University of Newfoundland's Faculty of Engineering and Applied Science. He holds a B.Sc. in Mechanical Engineering from the University of Moratuwa (Sri Lanka), an M.Sc. in Computer Integrated Manufacturing from Loughborough University (UK), and a Ph.D. in Intelligent Control from Memorial University. His research focuses on intelligent control systems, robotics, and machine vision, with significant contributions to autonomous navigation, sensor fusion, and UAV technologies. He leads the Intelligent Systems Laboratory (ISLAB) and has pioneered work on LiDAR-assisted radar enhancement, multi-robot localization, and exoskeleton control systems. **Education**: B.Sc., Mechanical Engineering, University of Moratuwa (Sri Lanka) M.Sc., Computer Integrated Manufacturing, Loughborough University (UK) Ph.D., Intelligent Control, Memorial University (Canada) **Research Interests**: Dr. Mann’s work spans autonomous systems, UAV navigation, sensor fusion (e.g., LiDAR, radar, INS), and robotics applications in mining, healthcare, and environmental monitoring. His recent projects include developing computationally efficient NMPC algorithms for UAVs and creating robust localization systems for heterogeneous multi-robot networks. **Publications**: His articles emphasize advancements in navigation algorithms, disturbance estimation for multi-rotor stability, and AI-driven sensor integration. Key themes include improving system robustness under uncertainty and optimizing computational efficiency in real-time control. **Labs & Teams**: Director of ISLAB, collaborating on exoskeleton development (e.g., Anthro-X) and UAV plume tracking for environmental sensing. Active in industry partnerships like C-CORE for mining automation.