جست‌وجوی استاد و پژوهشگر

Igor Ivkovicمشاهده پروفایل

استاد

• Information Systems
• Software Engineering
• Knowledge Engineering
• +۳ مورد دیگر

Igor Ivkovic was a Professor in the Department of Systems Design Engineering at the University of Waterloo, Canada. His work focused on integrating theory and practice in complex information systems, emphasizing system modeling, process modeling, and data modeling to bridge technical and business stakeholder needs. He taught courses such as Data Structures and Algorithms, Algorithms and Data Structures, and Digital Systems in recent years. Education: Holds a Doctorate in Electrical and Computer Engineering (2011), along with advanced certificates in university teaching (Certificate in University Teaching, 2011) and instructional skills (ISW, 2015). Earlier degrees include a Master of Mathematics in Computer Science (2003) and a Bachelor of Mathematics in Operations Research (2001), both from the University of Waterloo. Research Interests: Specialized in Information Systems, Software Engineering, and Knowledge Engineering. His work addressed challenges in model synchronization, software evolution, and architecture recovery, leveraging formal methods and model-driven approaches to enhance system consistency and interoperability. Notable Contributions: Authored influential papers on model synchronization for software evolution (2011) and improving the Gnutella protocol (2001), the latter earning a prize-winning award. He also pioneered educational innovations like Design Days Boot Camps (2017–2021), integrating remote learning and augmented reality into engineering education. Awards: Recognized for his 2001 research on the Gnutella protocol, which won a prestigious award through the LimeWire contest.

• Robotics
• Biomechanics
• Human-Machine Interaction
• +۳ مورد دیگر

Jonathan Lin is an Adjunct Assistant Professor at the University of Waterloo, specializing in robotics and biomechanics with a focus on human motion analysis and assistive technologies. His research spans rehabilitation engineering, human-robot interaction, and sensor systems for clinical and mobility applications. Key research areas include real-time pose estimation for assistive robots, motion segmentation for rehabilitation monitoring, and humanoid robotics learning from human demonstrations. He has contributed to projects like the SkyWalker mobility aid robot and Segway-riding humanoid systems. His work bridges robotics, biomechanics, and healthcare, emphasizing practical applications in aging populations and clinical settings. No scientific awards are listed, but his publications reflect interdisciplinary innovation in motion analysis and assistive technologies. Advising and grants details are not explicitly provided, though collaborations with robotics and biomedical engineering teams are implied through his research outputs. His lab or team affiliations remain unspecified in the provided texts.

Michael Fisherمشاهده پروفایل

استادیار

• Control Systems
• Nonlinear Dynamics
• Power Systems
• +۳ مورد دیگر

Michael Fisher is an Assistant Professor at the University of Waterloo, affiliated with the Faculty of Engineering. His research focuses on nonlinear systems theory, control systems design, and vulnerability assessment in power systems. He explores topics such as system-level synthesis, stability analysis under perturbations, and optimization techniques for distributed control. His work bridges applied mathematics and engineering applications, with a particular emphasis on resilience and safety margins in complex systems. Key research areas include trajectory sensitivity analysis, region of attraction boundary stability, and sparsity-promoting control design. He has contributed to advancements in H2/H∞ control, adaptive divide-and-conquer strategies for virtual power plants, and geometric programming approaches for natural gas networks. His publications often intersect nonlinear dynamics, optimization, and practical engineering challenges. Fisher’s recent studies emphasize parameterized system analysis, Hausdorff continuity in region of attraction boundaries, and approximation methods in Hardy spaces. His work addresses both theoretical control system advancements and real-world applications in power grids and distributed energy systems.

• CMOS Integrated Circuits
• Biosensors
• Imagers (Visible/IR/X-ray)
• +۳ مورد دیگر

Dr. Peter Levine is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Waterloo, where he also serves as a First Year Academic Advisor. His research focuses on developing CMOS integrated circuits that bridge biology and digital systems, with applications in biosensors and advanced imaging. He leads the Silicon Bioelectronics (SiBio) Laboratory and has been recognized with awards including the Teledyne DALSA Componentware/CAD Award and the IEEE Best Paper Award. Education: Ph.D. (Columbia University, 2009), M.Eng. (McGill University, 2004), B.Eng. (McGill University, 2002). Research interests include CMOS analog/mixed-signal ICs, electrochemical biosensors, and visible/IR/X-ray imagers. Recent work emphasizes monolithic amorphous-selenium/CMOS integration for high-resolution biomedical imaging and photon-counting detectors. His team innovates in sensor design, material integration, and signal processing. Teaching includes courses like ECE 340 (Electronic Circuits 2) and ECE 636 (Advanced Analog Integrated Circuits). He actively supervises graduate students and holds Sole-Supervisory Privilege Status (SSPS). Awards: 2016 Teledyne DALSA Award, 2015 IEEE MWSCAS Best Paper, 2005 Intel Ph.D. Fellowship. His lab collaborates on projects involving CMOS-based biosensors, X-ray detectors, and lab-on-a-chip systems. Over 20 patents and 40+ publications reflect his contributions to semiconductor-based biomedical engineering and electronics innovation.

Benjamin Ezeمشاهده پروفایل

استاد مدعو

• Big Data Analytics
• Cloud Data Warehousing
• Health Data Analytics and Integration
• +۸ مورد دیگر

Benjamin Eze is a part-time and adjunct professor at the School of Engineering Design and Teaching Innovation within the University of Ottawa . He holds a PhD in Digital Transformation and Innovation, an MSc in Electronic Business Technologies, and a BSc in Computer Engineering. Professionally, he serves as Lead Architect at Next Pathway Inc. and Business Intelligence Partner with Champlain Ontario Health at Home. Education: PhD – Digital Transformation and Innovation (University of Ottawa) MSc – Electronic Business Technologies (University of Ottawa) BSc – Computer Engineering Benjamin specializes in Big Data Analytics , Healthcare Data Privacy , Cloud Computing , and AI in Software Engineering . His work bridges technology and healthcare, focusing on secure data integration and digital transformation. Scientific Awards: Holds two patents in Canada and the United States Benjamin's research spans healthcare data governance, cloud infrastructure (DevOps, DevSecOps), and privacy-preserving technologies. His publications emphasize systematic approaches to data anonymization, cloud-based healthcare monitoring, and ethical AI frameworks. He teaches in upskilling programs at the University of Ottawa’s Professional Development Institute, FxInnovation, and CENGN CloudCampus DevOps programs, while collaborating with organizations like Cisco, Montfort Hospital, and Accreditation Canada.

Hanifeh Imanianمشاهده پروفایل

استاد مدعو

• Application of artificial intelligence in climate prediction
• Hydrodynamics
• Computational fluid dynamics
• +۳ مورد دیگر

Hanifeh Imanian is an Adjunct Professor of Water Resources Engineering at the Department of Civil Engineering, University of Ottawa, since 2022. She holds a PhD in Civil Engineering from Amirkabir University of Technology (Iran, 2012), focusing on numerical modeling of oil spill dispersion in marine environments. With over a decade of experience as a faculty member and department head in Iran, she conducted a sabbatical at the University of Ottawa in 2018, collaborating on AI-driven rail infrastructure monitoring with government partners. Her research interests span AI applications in climate prediction, computational fluid dynamics, hydro-environmental modeling, oil spill transport, and sediment dynamics. Over 20 peer-reviewed articles reflect her work on AI for soil moisture, soil temperature prediction, and spill modeling. Her 15+ years of teaching and research include supervising/co-supervising over 5 graduate students. Recent publications emphasize AI-driven environmental modeling, including soil temperature prediction under extreme conditions and oil spill dispersion analysis. Her collaborations bridge academic and industrial sectors, particularly in infrastructure and environmental monitoring systems.

François Bouffardمشاهده پروفایل

دانشیار

• Power Engineering
• Smart Grids
• Systems and Control
• +۳ مورد دیگر

François Bouffard is an Associate Professor at McGill University's Faculty of Engineering, specializing in Power Engineering and Systems Control. He holds the William Dawson Scholar title and serves as Associate Chair (Undergraduate Affairs). His research focuses on smart grids, renewable energy integration, and advanced control systems. Research interests include optimizing power systems through data-driven methods, demand response mechanisms, and energy storage solutions. He contributes to projects like the Group for Research in Decision Analysis (GERAD), emphasizing sustainable energy systems and grid resilience. Recent work explores flexibility in smart grid architectures, cold load management, and multi-agent reinforcement learning for energy systems. His publications highlight optimization techniques, stochastic modeling, and machine learning applications in energy control. Awarded the William Dawson Scholar distinction, his work bridges theoretical advancements with practical grid operations. He collaborates on interdisciplinary projects addressing energy transition challenges, such as hybrid storage systems and distributed energy resource coordination.

• Bioinformatics
• Health Informatics
• Affective Computing
• +۳ مورد دیگر

Dr. Stamos Katsigiannis is an Associate Professor in the Department of Computer Science at Durham University. His research focuses on bioinformatics, health informatics, affective computing, and GPU computing. He holds a BSc, MSc, and PhD in Computer Science from the University of Athens and the Athens University of Economics and Business. Before Durham, he was a Postdoctoral Research Fellow and Lecturer at the University of the West of Scotland (2016–2020). His work spans biometric identification via EEG signals, medical image analysis, and deep learning applications in healthcare. Education: BSc (Hons.) in Informatics and Telecommunications from National and Kapodistrian University of Athens MSc in Computer Science from Athens University of Economics and Business PhD in Computer Science from National and Kapodistrian University of Athens Research interests include bioinformatics (e.g., microarray analysis), health informatics (e.g., ECG-based emotion modeling), and GPU computing for real-time applications. He has pioneered studies on EEG-based biometrics and affect recognition in human-horse interaction. Recent articles explore chest X-ray classification using deep learning , AI-generated content detection , and trajectory prediction with graph networks . His research emphasizes interdisciplinary applications of machine learning in healthcare and education. He advises six postgraduate students and collaborates on UK parliamentary AI governance reports. Notable contributions include the BED EEG dataset and the DREAMER emotion recognition database.

Herbert H Tsangمشاهده پروفایل

استاد

• Bioinformatics
• Computational Intelligence
• Machine Learning
• +۷ مورد دیگر

Herbert H. Tsang is a Full Professor in Computing Science & Mathematics at Trinity Western University (TWU), British Columbia, Canada. He also serves as an Adjunct Professor at Simon Fraser University's School of Interactive Arts and Technology. His roles include Director of the Applied Research Lab, Undergraduate Research Academy, and Academy of STEAM at TWU. Dr. Tsang holds a PhD and completed an NSERC Postdoctoral Fellowship at the University of Calgary. His research focuses on computational intelligence, bioinformatics, mobile computing, and health technology applications. He has received notable awards, including the 2018 International E-Learning Award for Mobile Learning and the 2019 CNIE Partnership & Collaboration Award. His work spans grants from NSERC, SSHRC, CIHR, and private foundations. Active in professional societies, he is a Senior Member of IEEE and ACM. Recent projects include mobile application development and interdisciplinary research collaborations. Education: PhD in Engineering/Computer Science (exact program unspecified), NSERC Postdoctoral Fellow (2009–2011) Research Highlights: Phishing detection frameworks, HIV transmission modeling, and mobile learning applications. Grants: Funding from NSERC, SSHRC, CIHR, M.J. Murdock Charitable Trust, and Mitacs. Media & Outreach: Featured in articles on educational technology, including high school coding initiatives and SFU app development projects. Awards Overview: 2019 CNIE Innovation Award 2018 IELA Mobile Learning Award IEEE/ACM Review Service Contributor Advising & Mentorship: Supervises undergraduate/graduate research assistants. Former roles include engineering projects with the Canadian Space Agency and mentorship for Engineers and Geoscientists BC. Labs & Initiatives: Leads TWU's Applied Research Lab, fostering interdisciplinary projects in bioinformatics, computational creativity, and system design. Oversees the Undergraduate Research Academy, promoting student research engagement.

Nozomu Yachieمشاهده پروفایل

استاد

• Genome Editing
• Cell Engineering
• Synthetic Biology
• +۲ مورد دیگر

Professor Nozomu Yachie directs research at UBC's School of Biomedical Engineering, focusing on cellular/molecular engineering and computational biology. His lab develops DNA event-recording technologies to trace molecular dynamics using genome editing and high-performance computing. Key innovations include CloneSelect for retrospective cell isolation and computational tools like FRACTAL for large-scale lineage reconstruction.

Samira Sadaouiمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Data Science
• +۶ مورد دیگر

Dr. Samira Sadaoui is a Full Professor at the University of Regina's Department of Computer Science. She holds a PhD and MSc in Computer Science from the University of Nancy I, France. Her research is supported by NSERC and MITACS grants, focusing on artificial intelligence applications in real-world environments. Dr. Sadaoui's research spans: Adaptive machine learning systems for evolving data streams Fraud detection algorithms in financial and auction systems Evolutionary optimization methods for feature selection Dimensionality reduction techniques for high-dimensional data Reinforcement learning approaches for combinatorial problems Her recent publications demonstrate strong emphasis on: Concept drift detection in noisy environments (2022-2024) Evolutionary computation for feature engineering (2021-2023) Real-world applications in fraud detection and service monitoring (2017-2022) Teaching responsibilities include: CS115: Object-Oriented Design CS230: Fundamentals of Computer Science III CS372: Software Engineering Methodology CS476: Software Development Project CS872: Advanced Software Engineering

Natalia Nikolovaمشاهده پروفایل

استاد

• Microwave and millimeter-wave imaging and detection
• Inverse problems
• Computational electrodynamics
• +۶ مورد دیگر

Natalia K. Nikolova is a Professor and Canada Research Chair (Tier 2) in High-frequency Electromagnetics at the McMaster University Faculty of Engineering, Department of Electrical and Computer Engineering. Author of Introduction to Microwave Imaging (Cambridge University Press, 2017) Develops cognitive radar systems for concealed weapon detection and microwave scanners for breast cancer screening Commercialization with Patriot One Technologies Ltd. Education: Dipl. Eng. (Radioelectronics), Technical University of Varna, Bulgaria (1989) Ph.D. (Electrical Engineering), University of Electro-Communications, Tokyo, Japan (1997) NSERC Postdoctoral Fellowship (1998-1999) Research Focus: Microwave and millimeter-wave imaging systems for biomedical and security applications through computational electromagnetism and inverse scattering analysis. Her Electromagnetic Vision Laboratory (founded 1999) develops high-speed sensor arrays and computer-aided design tools. Scientific Contributions: Elevated to IEEE Fellow (2011) for sensitivity analysis methods Delivered 50+ international lectures as Distinguished Microwave Lecturer (2010-2013) Holder of 7 patents in microwave imaging technology

Yong Hoon Kimمشاهده پروفایل

دانشیار

• Connected and autonomous vehicles (CAVs)
• Intelligent transportation systems (ITS)
• Advanced traveler information systems
• +۲ مورد دیگر

Yong Hoon Kim is an Associate Professor in the Department of Civil and Environmental Engineering at the University of Windsor, Canada. He specializes in intelligent transportation systems with a focus on connected and autonomous vehicles (CAVs), traffic flow modeling, and cybersecurity in transportation networks. Education : BSc & MSc in Civil Engineering from University of Seoul, South Korea PhD in Civil Engineering from Purdue University, West Lafayette, IN, USA Research Interests : Connected and autonomous vehicles (CAVs) integration in urban environments Intelligent transportation systems (ITS) and traffic flow optimization Cybersecurity challenges in vehicle-to-vehicle communication networks Mobility data privacy and advanced traveler information systems Recent Publication Trends : His recent work (2023) explores vehicle malware modeling, collision-free traffic simulation, and mobility data analysis, while earlier studies focus on CAV infrastructure planning and V2V communication dynamics.

• Statistical Signal Processing
• Pattern Recognition
• Machine Learning
• +۳ مورد دیگر

Dr. Miroslaw Pawlak is a Professor in the Department of Electrical and Computer Engineering at the University of Manitoba’s Price Faculty of Engineering. He holds a Ph.D. and D.Sc. in Computer Engineering from Wrocław University of Technology, Poland. As a Professional Engineer registered in Manitoba, he has held visiting positions at multiple institutions worldwide, including the University of Ulm and University of Göttingen as an Alexander von Humboldt Foundation Fellow. His research focuses on statistical signal processing, machine learning, nonparametric modeling, and system identification. He authored/co-authored influential books like Nonparametric System Identification (Cambridge University Press, 2010) and over 100 peer-reviewed publications. Dr. Pawlak has served as an Associate Editor for journals such as Pattern Recognition and IEEE Transactions on Information Theory , and was recognized in Stanford University’s World’s Top 2% Scientists list. Education: 1985: Ph.D. in Computer Engineering, Wrocław University of Technology 1999: D.Sc. in Computer Engineering, Wrocław University of Technology Research Interests: Dr. Pawlak specializes in advanced signal processing techniques, including nonparametric system identification, statistical analysis of stochastic signals, and machine learning applications in engineering systems. His work bridges theoretical foundations (e.g., operator theory with Hermite polynomials) and practical implementations (e.g., wind farm modeling and power system stability prediction). Publications: His recent work emphasizes nonparametric methods for system testing (e.g., Hammerstein systems) and interdisciplinary applications like power grid oscillation prediction using LASSO algorithms. He frequently collaborates with international researchers to advance signal processing theory and energy systems modeling. Awards: World’s Top 2% Scientists (Stanford University, 2021/2022) Professional Contributions: Dr. Pawlak’s editorial roles and visiting fellowships demonstrate his global influence. He has advised numerous graduate students and contributed to key textbooks shaping the field of system identification.

Yuejian Chenمشاهده پروفایل

استادیار

• Dynamic Modelling
• Vibration Signal Processing
• Artificial Intelligence
• +۵ مورد دیگر

Dr. Yuejian Chen is an Assistant Professor in the Department of Mechanical Engineering at the University of Manitoba's Price Faculty of Engineering. His research focuses on dynamic modelling, vibration signal processing, artificial intelligence, and prognosis/health management for complex systems like railway vehicles, wind turbines, and steam turbines. He holds a PhD from the University of Alberta (2020) and was a postdoctoral fellow there until 2021. Prior to joining the University of Manitoba in 2024, he served as an Assistant Professor at Tongji University's Institute of Rail Transit in China from 2021 to 2024. His research integrates digital twins and advanced health management methodologies to ensure safe and cost-effective operation of mechanical systems. Key areas include non-stationary vibration analysis, fault detection via AI (e.g., LSTM networks), and physics-informed machine learning. He has authored/co-authored over 60 publications and serves on editorial boards for journals such as IEEE Sensors Journal , IEEE Transactions on Instrumentation and Measurement , and Smart and Resilient Transportation . Dr. Chen's work bridges theoretical advancements with practical applications, emphasizing railway transportation and energy systems. His recent publications (2021–2025) highlight contributions to gearbox fault detection under variable speed conditions, multi-camera metro monitoring systems, and data-driven load identification strategies. His research trends emphasize fusion of physical principles with AI for robust diagnostics and health management across mechanical systems. He is actively recruiting graduate students interested in dynamic systems, signal processing, and AI applications in mechanical engineering. His research group collaborates with industry partners to address real-world challenges in machinery safety and efficiency.