جست‌وجوی استاد و پژوهشگر

Douglas Downمشاهده پروفایل

استاد

• Performance Evaluation
• Stochastic Models
• Data Centres
• +۷ مورد دیگر

Dr. Douglas Down is a Professor in the Department of Computing and Software at McMaster University. His research focuses on performance evaluation, stochastic models, data centers, and scheduling algorithms. He is actively involved in the Digital & Smart Systems research cluster, addressing challenges in healthcare logistics, energy-efficient computing, and resource allocation. Dr. Down teaches CAS 736: Analysis of Stochastic Networks, exploring statistical modeling techniques and current research in stochastic networks. His work integrates machine learning and optimization to solve real-world problems, such as blood product inventory management and thermal-aware data center management. He has published extensively on topics including demand forecasting, inventory policies, and energy-aware workload assignment. While no specific awards are listed, his contributions to operations research and computing systems are evident through his prolific publication record. Dr. Down advises graduate students and collaborates on projects involving healthcare systems, cloud computing, and distributed systems. His research addresses both theoretical and applied challenges, with a focus on decision-making under uncertainty and system optimization.

Yossiri Adulyasakمشاهده پروفایل

استاد

• Supply Chain Analytics
• Optimization under Uncertainty
• Large-Scale Optimization
• +۴ مورد دیگر

Yossiri Adulyasak is a Full Professor in the Department of Logistics and Operations Management at HEC Montréal, holding the Canada Research Chair in Supply Chain Analytics. He is also an Adjunct Professor at the University of Montreal's Department of Computer Science and Operations Research and a scientific advisor at IVADO Labs. His research focuses on supply chain optimization, data-driven decision-making, and robust optimization under uncertainty, with applications in retail, transportation, and humanitarian logistics. Education: PhD in Operations and Logistics Management (HEC Montréal), Master of Civil Engineering in Transportation Engineering (Chulalongkorn University). Research Interests : Supply chain analytics, large-scale optimization algorithms, stochastic programming, machine learning integration, and resilient supply chain design. His work emphasizes practical applications in logistics networks, inventory management, and dynamic resource allocation under uncertainty. Recent Articles : Focus on AI-driven retail analytics, robust optimization for lot-sizing and facility location, and humanitarian logistics. Key topics include pandemic response strategies, electric vehicle routing, and drone delivery systems. Awards : Recipient of the 2021 Prix de recherche Chenelière Éducation/Gaëtan Morin for excellence in scientific publications. Supervision : Directed 3 PhD dissertations and over 40 master’s and project supervisions, collaborating with companies like Bombardier, Pratt & Whitney Canada, and JDA. Active in industrial partnerships for supply chain optimization solutions. Lab/Teams : Member of GERAD (Group for Research in Decision Analysis) and IVADO Labs, contributing to cross-disciplinary AI and operations research initiatives.

Jean-Guy Simonatoمشاهده پروفایل

استاد

• Finance
• Financial Engineering
• Derivative Products
• +۳ مورد دیگر

Jean-Guy Simonato is a Professor in the Department of Finance at HEC Montréal. He holds a M.Sc. from HEC Montréal and a Ph.D. in Finance from McGill University. His research focuses on financial engineering, derivative products, fixed income securities, and the application of econometrics to financial problems. He has published extensively in top journals such as the International Journal of Forecasting and Journal of Portfolio Management . His recent work explores dynamic portfolio allocation, goal-based wealth management, and volatility modeling. He supervises master's theses on topics like reinforcement learning in portfolio optimization and risk management. Teaching responsibilities include courses on derivatives pricing and financial instruments. Simonato's articles consistently address market risk, non-normal return distributions, and asset pricing under GARCH frameworks. His research bridges theoretical models with practical applications in finance, emphasizing empirical validation through econometric techniques.

Christopher Swartzمشاهده پروفایل

استاد

• Process Systems Engineering
• Operations Optimization
• Dynamic Optimization
• +۵ مورد دیگر

Christopher Swartz is a Professor in the Department of Chemical Engineering at McMaster University and Director of the McMaster Advanced Control Consortium (MACC). He specializes in process systems engineering, with a focus on operations optimization, dynamic modeling, and supply chain optimization. His work integrates advanced control strategies with real-time optimization to enhance industrial process efficiency under dynamic conditions. Education: B.Sc. (Eng.) Chemical Engineering, University of Cape Town Ph.D. Chemical Engineering, University of Wisconsin Professional Licenses: P.Eng. (Ontario), MAIChE, MCSChE Research Interests: Dynamic optimization of transient processes (e.g., electric arc furnaces, air separation units) Integration of design and control for plant operability Supply chain optimization under uncertainty Economic model predictive control and real-time optimization Large-scale dynamic optimization under uncertainty using parallel computing Teaching: Teaches CHEM ENG 3P04 (Process Control), covering transient process behavior, automatic control theory, and computer process control. MACC Leadership: Directs MACC, a research consortium advancing process automation through industry-academia collaboration. MACC focuses on cutting-edge control technologies, data analytics, and sustainable design.

Joseph Bennettمشاهده پروفایل

استاد

• Conservation Prioritization
• Threatened Species Conservation
• Invasion Ecology
• +۴ مورد دیگر

Joseph Bennett is a Professor at the Department of Biology and Institute of Environmental Science, Carleton University, and co-director of the Geomatics and Landscape Ecology Laboratory (GLEL). His research focuses on practical conservation decision-making, emphasizing biodiversity monitoring, invasive species management, threatened species protection, and evidence-informed environmental policy. His research interests span conservation prioritization, invasion ecology, spatial statistics, and community science applications. He develops tools to optimize monitoring programs and resource allocation for conservation agencies while integrating Indigenous knowledge into conservation frameworks. His work addresses temperate and boreal ecosystems, polar regions, and migratory species dynamics. Develops AI-driven knowledge synthesis tools (e.g., TReK) Advocates for community-engaged conservation Collaborates with Nature Conservancy of Canada and Indigenous communities Co-supervises interdisciplinary students across Canada and internationally His lab includes 14 graduate students and has produced 25+ peer-reviewed publications in 2024-2025, focusing on topics like citizen science efficacy, invasive species control, and policy reform for the Canadian Species at Risk Act. He also contributes to open science initiatives and evidence-based decision-making frameworks.

Roslyn Dakinمشاهده پروفایل

دانشیار

• Animal Behavior
• Ecology
• Evolutionary Biology
• +۳ مورد دیگر

Roslyn Dakin is an Associate Professor in the Department of Biology at Carleton University, part of the Faculty of Science. She holds degrees B.Sc., M.Sc., and Ph.D. from Queen's University. Her research focuses on animal behavior, particularly flight mechanics and social network dynamics, with applications to wildlife conservation and biomimetic engineering. She leads a lab investigating how behavioral control systems adapt to environmental challenges, emphasizing quantitative approaches to analyze behavioral dynamics. Education: B.Sc., M.Sc., Ph.D. (Queen's University). Research Interests: Animal flight biomechanics, cooperative behavior in social networks, and the intersection of behavior with ecological challenges. Recent work explores how hummingbirds optimize flight performance and how social interactions shape bird communities. Her studies also address collision risks for birds in urban environments and the role of social learning in avian species. Publications highlight her work on optic flow control in hummingbirds, testosterone-driven social networks in birds, and the biomechanics of avian displays. Her lab actively seeks graduate and undergraduate researchers, emphasizing interdisciplinary approaches combining fieldwork, experimental biology, and computational modeling. Contact details include roslyn.dakin@carleton.ca and roslyn.dakin@gmail.com. Notable research themes include: 1) Flight maneuverability and energy use; 2) Social structure and cooperation in animal groups; 3) Conservation implications of avian behavior in human-altered environments. Her studies bridge basic science and applied conservation, leveraging cutting-edge quantitative tools.

Xavier Fernandoمشاهده پروفایل

استاد

• Optical Communication
• Wireless Communication Systems
• Signal Processing
• +۴ مورد دیگر

Xavier Fernando is a Professor and Director of the TMU Intelligent Communication and Computing Laboratory at Toronto Metropolitan University's Department of Electrical and Computer Engineering. His academic career includes leadership roles such as Chair of IEEE Canada Humanitarian Initiatives (2017-18), General Chair of IEEE International Humanitarian Technology Conference (2017), and Board Member of Ryerson University (2011-12). He has authored over 200 research papers, three books, and holds multiple patents, with research focused on optical/wireless communication systems, cognitive radio, and vehicular visible light communications. Research interests span signal processing for underground communications, MAC layer protocols, and energy-efficient networks. Notable awards include IEEE Communications Society Distinguished Lecturer (2012-2013), Engineering Excellence Award (2016), and finalist for Top 25 Canadian Immigrants (2012). His lab, established since 2008, has secured $3.185 million in funding. Contributions include pioneering work in RF energy harvesting, smart grid technologies, and underground communication systems for mining safety. Professional service includes roles as IEEE Toronto Section Chair, member of IEEE Education Board, and evaluator for ABET. Key publications address heterogeneous networks, cognitive radio performance, and VLC vehicular applications. Students and alumni are tracked via LinkedIn groups, with notable projects winning IEEE MTT prizes and engineering accolades.

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.

Reza Faieghiمشاهده پروفایل

استادیار

• Robotics
• Machine Learning
• Virtual Reality
• +۶ مورد دیگر

Dr. Reza Faieghi is an Assistant Professor in the Department of Aerospace Engineering at Toronto Metropolitan University and serves as the Director of the Autonomous Vehicles Laboratory. He holds a PhD from the University of Western Ontario, an MSc from Iran University of Science and Technology, and a BSc from Hamedan University of Technology. His research focuses on robotics, machine learning, and virtual reality, with specific applications in uncrewed aerial/ground vehicles, motion control, and human-system interactions. His work integrates advanced control systems with human factors to enhance autonomous systems safety. Current projects include developing intelligent UAV control algorithms, biomechanical modeling for ergonomic design, and VR-based surgical training systems. His research spans aerospace engineering, control theory, biomechanics, and human-computer interaction. Dr. Faieghi teaches courses including Intro to Aerospace Engineering Design, Aerospace Sensors, and Introduction to Machine Learning. He directs the Autonomous Vehicles Laboratory, which focuses on developing intelligent systems for transportation and healthcare applications.

Alireza Bakhshaiمشاهده پروفایل

استاد

• Renewable Energy Systems
• Power Electronics
• Electrical Engineering
• +۷ مورد دیگر

Dr. Alireza Bakhshai is a Professor in the Department of Electrical and Computer Engineering at Queen's University, Canada. He holds a PhD from Concordia University (1997) and has served as faculty at Isfahan University of Technology and Queen's University. His research focuses on renewable energy systems, power electronics, control systems, and multilevel converter technologies. He has supervised 15 graduate students and currently advises/co-advises eight students. His work includes contributions to electric vehicle chargers, DC microgrid control, hybrid energy storage systems, and advanced inverter topologies. Education: PhD, Electrical Engineering (Concordia University, 1997); MSc and BSc (Isfahan University of Technology, 1986 and 1984). Research Interests: Renewable energy integration, multilevel converter design, reinforcement learning applications in power systems, and efficient energy management strategies. His recent publications emphasize AI-driven control methods for microgrids and electric vehicle systems. Awards: Not explicitly stated in provided materials. Advising & Grants: Supervised 15 graduate students, currently advising four and co-advising four. His research has addressed industrial challenges such as FACTS controllers for steel mills and unified power flow controllers. Lab/Teams: Active in power electronics and renewable energy research groups at Queen's, focusing on applied industrial solutions and academic-industry collaborations.

Jordan Morelliمشاهده پروفایل

استاد

• Non-automotive combustion engineering
• Fuel engineering
• Electrical energy systems
• +۵ مورد دیگر

Professor Jordan Morelli is a Professor in the Department of Physics, Engineering Physics and Astronomy at Queen's University, affiliated with the Faculty of Arts and Science. His research focuses on magnetic confinement fusion using the STOR-M tokamak, non-automotive combustion engineering, renewable energy systems, and electrical energy integration. He holds a Ph.D. (2003) and M.A.Sc. (1998) in Electrical and Electronics Engineering from the University of Saskatchewan and University of Windsor, respectively. Research interests include distributed generation (wind power), plasma dynamics in field-reversed configurations (FRCs), and eddy current-based non-destructive testing for nuclear reactor components. His work spans experimental plasma physics, fusion reactor design, and energy systems optimization. Notable affiliations include leadership roles in QUFA committees and collaborations with the University of Saskatchewan's Plasma Physics Laboratory. Recent publications emphasize FRC collisional merging, plasma diagnostics, and eddy current applications in fusion and nuclear engineering contexts. His contributions bridge fundamental plasma physics with practical energy solutions, including fusion reactor core modeling and advanced instrumentation development.

Il-Min Kimمشاهده پروفایل

استاد

• Wireless Artificial Intelligence
• Machine Learning
• Deep Learning
• +۹ مورد دیگر

Professor Il-Min Kim is a Full Professor in the Department of Electrical and Computer Engineering at Queen's University (Smith Engineering). He leads the Wireless Artificial Intelligence Laboratory (WAI Lab), focusing on AI-driven wireless systems, IoT/IoE/IIoT, federated learning, edge computing, and 6G/V2X communications. His work integrates machine learning, signal processing, and cybersecurity with wireless infrastructure. Education: B.S. (Yonsei University, 1996), M.S./Ph.D. (KAIST, 2001). Postdoctoral research at MIT (2001-2002) and Harvard (2002-2003) preceded his faculty role at Queen's since 2003. Promoted to Associate Professor (2009) and Full Professor (2014). Research emphasizes Wireless AI , including on-device AI, federated learning, geoscience AI (Geo-AI), and secure communication protocols. Key areas: AI for 6G/V2X, energy-efficient edge computing, and robust spectrum sensing. His lab develops frameworks for distributed systems, compressive sensing, and nonlinear energy harvesting. Notable contributions include hybrid replay mechanisms for incremental learning, diffusion models for industrial IoT, and deep learning-based channel estimation. His work addresses challenges in data security, model robustness, and real-time inference under resource constraints.

Martin Guayمشاهده پروفایل

استاد

• Nonlinear control systems
• Data-driven control and optimization
• Extremum-seeking control
• +۵ مورد دیگر

Martin Guay is a Professor in the Department of Chemical Engineering at Queen's University, affiliated with Smith Engineering. He holds a cross-appointment in the Department of Mathematics and Statistics, Faculty of Arts and Science. His research focuses on data-driven control methods, model-free control, extremum-seeking control, and distributed optimization. He has contributed to nonlinear control systems, adaptive estimation, and geometric control. Education: Ph.D. in Control Engineering (Queen's University, 1996). Research interests include process control in chemical engineering, networked control systems, and systems theory. He serves as Editor-in-Chief of the Journal of Process Control and Senior Editor of IEEE Control Systems Letters , alongside editorial roles at Automatica , IEEE Transactions on Automatic Control , and the Canadian Journal of Chemical Engineering . Awards include the Syncrude Innovation Award and D.G. Fisher Award. His work emphasizes bridging theoretical control advancements with practical industrial applications.

• Algorithms
• Big data analytics
• Blockchain
• +۱۲ مورد دیگر

Dr. Wojciech Golab is a Professor in the Department of Electrical and Computer Engineering at the University of Waterloo. His research focuses on distributed systems, concurrency control, and persistent memory algorithms. He has received recognition for his work on shared memory algorithms from ACM Computing Reviews. His academic career includes teaching courses like ECE 252, ECE 356, and ECE 454 in the past five years. Education: PhD in Computer Science, University of Toronto (2010) M.Math in Computer Science, University of Waterloo (2004) BSc in Computer Science, University of Toronto (2002) Dr. Golab's research interests span algorithms, blockchain, distributed systems, fault tolerance, and scalable storage solutions. His work emphasizes practical applications of theoretical computer science, such as optimizing transaction processing and ensuring consistency in distributed environments. His recent publications explore topics like detectable synchronization objects for persistent memory, blockchain sharding protocols, and efficient mutual exclusion algorithms under system failures. These contributions highlight advancements in both theoretical foundations and real-world distributed system design. Awards: ACM Computing Reviews 'Notable Computing Items' recognition (2012) Dr. Golab has collaborated with industry partners like Hewlett-Packard Labs, Google, and Cisco to advance research in distributed computing and cloud systems. He currently oversees graduate studies in his department and welcomes applications from prospective students.

Michael Godfreyمشاهده پروفایل

استاد

• Software Engineering
• Software Evolution
• Empirical Studies
• +۵ مورد دیگر

Michael Godfrey is a Professor at the University of Waterloo's David R. Cheriton School of Computer Science, affiliated with the Department of Electrical and Computer Engineering. His work focuses on software engineering, empirical studies of software systems, code review practices, and open-source software ecosystems. He holds a Ph.D., M.Sc., and B.Sc. from the University of Toronto (1997, 1988, 1986). Research interests include software evolution, mining software repositories, provenance tracking, code duplication analysis, and program comprehension. He actively explores how developers interact with code reviews, documentation systems, and modern CI/CD pipelines. Recent work investigates app store software ecosystems, Bash scripting vulnerabilities, and deep learning API testing. Publications span empirical studies of developer communities (e.g., Stack Overflow analysis), architectural teaching methods, and automated testing techniques like documentation-guided fuzzing. His work bridges theory and practice, addressing challenges in large-scale systems maintenance and developer productivity. Leverages tools like Elasticsearch for repository mining and explores anomaly detection in software development. Engaged in curriculum development for software architecture education and has contributed to conferences like MSR and ICSE.