جستجوی استاد راهنمای دانشگاهی

• Reinforcement Learning
• Robotics
• Deep Learning
• +۳ مورد دیگر

Glen Berseth is an Associate Professor in the Department of Computer Science and Operations Research at the University of Montreal and a Senior Academic Fellow at Mila – Quebec Institute for Artificial Intelligence. He is also a Canada CIFAR Chair in AI and Co-Director of the Montreal Robotics and Integrative AI Laboratory (REAL). His work focuses on reinforcement learning, robotics, and deep learning applied to autonomous systems. He holds a postdoctoral background from Berkeley Artificial Intelligence Research (BAIR), working under Sergey Levine. His research emphasizes real-world applications, including human-robot collaboration, continual learning, and multi-agent systems. He teaches courses on robot learning at the University of Montreal and Mila, covering cutting-edge techniques for general-purpose robots. Key research interests include reinforcement learning for robotics, adaptive interfaces, and sim-to-real transfer. His recent work addresses challenges in autonomous learning systems, such as robust locomotion control and efficient exploration strategies. Notable awards include the Canada CIFAR AI Chair. He has supervised numerous students, including PhD candidates Ozgur Aslan and Siddarth Venkatraman, and Master’s students like Roger Creus-Castanyer and Léa Demeule, focusing on topics like reinforcement learning and robotic control. Berseth leads research projects funded by organizations like the CRSNG, FCI, and MITACS, addressing topics such as modular lifelong learning and generalization in robotics. His lab, REAL, explores embodied AI and robotics integration.

• Blockchain
• Internet of Things (IoT)
• Edge computing
• +۹ مورد دیگر

Abdelhakim HAFID is a Full Professor at the University of Montreal , affiliated with the Faculty of Arts and Science and the Department of Computer Science and Operations Research . He leads the LRC — Laboratoire de recherche en réseaux de communication and is a member of several research centers including CIRRELT (interuniversity research center on enterprise networks, logistics, and transportation), the Cyberjustice Lab , and talents (AI for cybersecurity lab). His research focuses on Blockchain security , IoT , edge and fog computing , intelligent transport systems , and network resource management . He has supervised over 30 graduate students and led/co-led numerous research projects funded by agencies like NSERC , FRQNT , and MITACS . Notable projects include Blockchain Evolution: Quantum-Resistant Security (2025–2031) and Design and Management of Fog Networks (2019–2026). His work spans vehicular networks , mobile cloud computing , and machine learning for network optimization . He actively contributes to cybersecurity initiatives, including IoT authentication frameworks and AI-driven solutions for judicial systems (e.g., Cyberjustice ). Key Projects : Quantum-Resistant Blockchain Security (2025–2031) IoT Authentication via Blockchain and Intelligent SIM (2022–2026) Fog Network Design (2019–2026) Grants : NSERC Discovery Grants MITACS Acceleration Fellowships FRQNT Team Research Grants His lab collaborations include CIRRELT (logistics & transport) and Cyberjustice (digital law), reflecting interdisciplinary strengths in both technical and societal domains.

Biniam Kebedeمشاهده پروفایل

استادیار

• Food Bioprocessing
• Data Science
• Fermentation Technology
• +۹ مورد دیگر

Dr. Biniam Kebede is an Assistant Professor in the Department of Food Science at the University of Guelph. His research focuses on integrating bioprocessing, food analytics, and data science to enhance food functionality and sustainability. He leads the Food Bioprocessing and Data Science Research Group, which explores fermentation, enzymatic treatments, and machine learning for food innovation. Academic History: B.Sc. in Food and Biochemical Technology, Bahir Dar University (Ethiopia) M.Sc. in Food Technology, Ghent University (Belgium) Ph.D. in Bioscience Engineering, KU Leuven (Belgium) Research Interests: Dr. Kebede's work addresses sustainable food systems through: Optimizing fermentation to unlock bioactive compounds from plant-based sources Mitigating off-flavors in pulses via value-chain analysis Engineering food structures to improve nutrient bioaccessibility Developing portable machine learning tools for food authenticity Valuing indigenous food ingredients and traditional processing methods His approach combines multi-omics, imaging, and AI to create predictive models for food innovation. Awards & Affiliations: 2022 IUFoST Young Scientist Award 2014 EFFoST PhD Student of the Year Award Member of IFT, CIFST, and IUFoST Honorary affiliation with University of Otago (New Zealand) Training Philosophy: Dr. Kebede emphasizes personalized mentoring through Individual Development Plans (IDPs), biweekly lab meetings, and interdisciplinary collaboration. Students engage in all research phases, including conference presentations and industry partnerships to build technical and professional skills.

Fred Popowichمشاهده پروفایل

استاد

• Natural Language Processing
• Artificial Intelligence
• Big Data
• +۴ مورد دیگر

Fred Popowich is a Professor in the School of Computing Science at Simon Fraser University (SFU), Canada. He holds adjunct positions at Dalhousie University's Faculty of Graduate Studies and is an Associate Member of SFU's Department of Linguistics and Cognitive Science Program. His academic career began post-PhD (Cognitive Science/Artificial Intelligence, University of Edinburgh, 1989) and has spanned over three decades at SFU. Education: PhD in Cognitive Science/Artificial Intelligence (University of Edinburgh, 1989); M.Sc. and B.Sc. in Computing Science (Simon Fraser University and University of Alberta, 1985/1982). Research focuses on natural language processing (NLP), machine translation, intelligent systems, and big data applications. He directs SFU’s Big Data Initiative and leads the Natural Language Laboratory, supervising MSc/PhD students in computing science. His work includes developing systems for smart homes, toxic language detection in social media, and energy grid analysis. Industry roles include co-founding Axonwave Software (as CTO/President) and contributing to technology commercialization. Current projects address EV charging impacts, personalized learning systems, and real-time load monitoring. Publications span machine translation, sentiment analysis, and NLP applications in education and energy systems. His work bridges theoretical computer science with practical applications in healthcare, smart cities, and education.

Michael Zurelمشاهده پروفایل

پژوهشگر ارشد

• Quantum Information
• Quantum Computation
• Quantum Contextuality
• +۷ مورد دیگر

Michael Zurel is a NSERC Postdoctoral Fellow in the Department of Mathematics at Simon Fraser University, working under Dr. Nadish de Silva, Canada Research Chair in the Mathematics of Quantum Computation. His research focuses on foundational aspects of quantum computation, quantum information, and nonclassical physics. Key interests include quantum contextuality, negativity in quasiprobability representations, and classical simulation algorithms for quantum systems. He holds a PhD, MSc, and BSc in Physics and Mathematics from the University of British Columbia (2024, 2020, 2019), all supervised by Dr. Robert Raussendorf. His doctoral work explored classical descriptions of quantum computations via hidden variable models and quasiprobability representations. His master’s thesis addressed hidden variable models and classical simulation algorithms for quantum computation with magic states on qubits. Research interests emphasize bridging quantum foundations with computational efficiency, particularly how nonclassical features like contextuality enable quantum advantage. Collaborators include prominent figures such as Robert Raussendorf, Juani Bermejo-Vega, and Cihan Okay. His scientific achievements include the NSERC Postdoctoral Fellowship. Advising and grants are not explicitly detailed, but his work is supported by foundational research grants. He collaborates actively within quantum information theory and computational physics communities.

Arash Habibi Lashkariمشاهده پروفایل

دانشیار

• Cybersecurity
• Network Security
• Threat Hunting
• +۷ مورد دیگر

Dr. Arash Habibi Lashkari is an Associate Professor and Canada Research Chair in Cybersecurity at York University's School of Information Technology. He holds a PhD from the University of Technology Malaysia and completed a Post-Doc at the University of New Brunswick. With over 25 years of teaching experience, he specializes in cybersecurity risk management, malware analysis, and threat hunting. He pioneered Canada’s first cybersecurity Capture the Flag (CTF) competition for post-secondary students and has authored 10 books and over 110 academic articles. Research Interests: Cybersecurity, Network Security, Threat Hunting, Malware Analysis, Cybersecurity Risk Management, and Blockchain Security. He leads the Behaciour-Centric Cybersecurity Center (BCCC), focusing on vulnerability detection technologies and cybersecurity dataset generation. Awards: Mitacs 150 Top Researchers (2017), University of New Brunswick Teaching Innovation Award (2020), Gold Medal at 2020 Canadian Online Publishing Awards, and multiple international security competition awards. His work has been featured in CBC, CIC, and global cybersecurity conferences. Key Projects: Development of intrusion detection datasets (e.g., CIRA-CIC-DoHBrw-2020), malware analysis frameworks, and AI-driven cybersecurity tools. He actively collaborates with organizations like Aviva and NICT on cybersecurity resilience strategies. Teaching: Offers courses in Digital Forensics, Network Security, and Cybersecurity Management. His 'Think-Que-Cussion' teaching methodology emphasizes interactive learning.

Kemal Tepeمشاهده پروفایل

استاد

• Vehicular Networks
• Cognitive Radio
• Wireless Communication
• +۶ مورد دیگر

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.

Jana Levisonمشاهده پروفایل

دانشیار

• Groundwater flow
• Contaminant transport
• Fractured geologic media
• +۵ مورد دیگر

Jana Levison is an Associate Professor in the School of Engineering at the University of Guelph, specializing in Water Resources Engineering. She holds the inaugural Doody Family Chair for Women in Engineering (2022-2027) and is affiliated with the Morwick G360 Groundwater Research Institute. Her research focuses on groundwater quality and quantity, particularly examining agricultural and climate change impacts on hydrological systems. Dr. Levison earned her Bachelor's and Ph.D. in Civil Engineering from Queen's University, with her doctoral research focusing on anthropogenic impacts on fractured bedrock aquifers. Prior to her position at Guelph, she completed a postdoctoral fellowship at the Université du Québec à Montréal, worked with the Cataraqui Region Conservation Authority on Drinking Water Source Protection, and served as Junior Fellow and Acting Executive Director of the Ontario Centre for Engineering and Public Policy. Her research program addresses critical water resource challenges through multiple funded projects examining agricultural nutrient transport, groundwater-surface water interactions, climate change impacts, and source water protection for Indigenous communities. Dr. Levison's work spans field investigations, advanced modeling techniques, and policy-relevant analysis to protect water resources in the Great Lakes Basin and beyond. Analysis of Dr. Levison's recent publications reveals a strong focus on nutrient transport dynamics in agricultural watersheds, particularly examining nitrogen and phosphorus movement through various hydrological pathways. Her research increasingly incorporates machine learning approaches for water quality prediction and integrates climate change scenarios into groundwater modeling. A significant portion of her work addresses source water protection challenges for First Nations communities and examines the impacts of road salt and neonicotinoids on groundwater quality. Dr. Levison has received notable recognition for her contributions to hydrogeology: IAH-CNC Early Career Hydrogeologist Award (2020) Dr. Levison has supervised over 20 graduate students and numerous undergraduate researchers, with current projects funded by MECP, OMAFRA, and NSERC. Her research group conducts field investigations in southern Ontario watersheds to understand nutrient transport mechanisms, groundwater-surface water interactions, and climate change impacts on water resources. She has established collaborative projects with multiple conservation authorities, government agencies, and Indigenous communities to address practical water resource challenges. As part of the Morwick G360 Groundwater Research Institute, Dr. Levison's team operates advanced hydrogeological monitoring equipment and employs innovative techniques for groundwater quality assessment. Her research group maintains instrumented field sites in agricultural watersheds throughout southern Ontario, with particular focus on clay plain systems in the Great Lakes Basin.

Mohamed Atiaمشاهده پروفایل

دانشیار

• Sensor Fusion
• Autonomous Systems
• Embedded Systems
• +۱۲ مورد دیگر

Mohamed Atia is an Associate Professor in the Department of Systems and Computer Engineering at Carleton University's Faculty of Engineering and Design. He conducts research in sensor fusion for autonomous systems, including robotics, autonomous vehicles, and the Internet of Things, with an emphasis on real-time embedded implementation. PhD, Electrical and Computer Engineering, Queen’s University (2013) M.Sc., Computer Systems, Ain Shams University (2006) B.S., Computer Systems, Ain Shams University (2000) His research focuses on sensor fusion , integrating data from heterogeneous sensors such as GNSS, IMU, Vision, Radar, and LiDAR under real-time constraints on embedded platforms like FPGAs and microcontrollers. He applies advanced signal processing, estimation theory, machine learning, and AI to solve challenges in state estimation, observability, fault tolerance, and concurrency management. Dr. Atia’s work has applications in intelligent vehicles, indoor navigation, mobile robotics, smart buildings, medical devices, and remote sensing . He leads a research lab focused on embedded multi-sensor systems, where students develop practical solutions for autonomous navigation and SLAM. His teaching emphasizes hands-on learning through labs and projects. He teaches undergraduate courses in computer systems, embedded systems, and signal processing, and a graduate course (SYSC 5807) on Advanced Topics in Computer Systems, specifically Sensor Fusion Systems . Scientific Awards: Alberta Innovate Association Award (2011) IEEE Excellence in PhD Research (2013) Mitacs Elevate Industrial Postdoc Award (2014) NSERC PDF Award (2015) Queen’s University Teaching Award (2016) Dr. Atia has advised graduate students such as Hamza Sadruddin and Alan Zhang , who have presented at IEEE Sensors and ION GNSS+ conferences, with Zhang winning Best Presentation. He has no listed grants in the provided text but has received prestigious fellowships. His research lab supports innovation in real-time embedded sensor fusion with links to industry and open-source tools.

• Magmatic Processes
• Hydrothermal Alteration
• Porphyry Systems
• +۳ مورد دیگر

Shaun Barker is an Associate Professor in the Department of Earth, Ocean & Atmospheric Sciences at the University of British Columbia. His research focuses on magmatic processes, hydrothermal alteration, and porphyry systems, particularly studying postsubduction magmatism and its economic implications. He supervises postdoctoral researchers such as Maria Alejandra Rodriguez Mustafa and has advised graduate theses on topics like the Dawson Range district's Late Cretaceous magmatism. Research interests include tectonomagmatic frameworks, fluid-rock interaction, and exploration methodologies using geochemical datasets and advanced analytical techniques. His work integrates field observations, geochemical analyses, and isotopic studies to unravel the genesis of ore deposits and geothermal systems. Key contributions include defining trace-element haloes around deposits, developing mineral mapping via µXRF, and applying machine learning to geological modeling. His studies span global regions like the Yukon, British Columbia, Nevada, and Peru, with a focus on Carlin-type gold, porphyry copper, and skarn systems.

Michael Friedlanderمشاهده پروفایل

استاد

• Convex Optimization
• Machine Learning
• First-Order Methods
• +۳ مورد دیگر

Michael Friedlander is a Professor of Computational Mathematics at the University of British Columbia (UBC), holding joint appointments in the Departments of Computer Science and Mathematics. He serves as Director of the UBC Institute of Applied Mathematics and is a Sauder School Distinguished Scholar. His research focuses on optimization theory, algorithms, and applications, particularly in convex optimization, first-order methods, and machine learning. Friedlander is a SIAM Fellow (2024) and has received multiple teaching awards, including the 2013 UBC CS Teaching Award. Education: PhD (2002) in Operations Research from Stanford University; BA (1993) in Physics from Cornell University. Research Interests: Friedlander’s work spans computational optimization, including first-order methods, gauge duality, federated learning, and applications in signal processing and quantum computing. His contributions include SPGL1, a widely used convex optimization solver, and foundational work on atomic decomposition and polar alignment in structured optimization. Key Contributions: His research bridges optimization with practical applications, such as compressed sensing and data science. Notable areas include dual methods for federated learning, low-rank spectral optimization, and algorithms for sparse recovery. He has advised numerous PhD students, including work on topics like gauge duality and federated learning contribution valuation. Awards & Honors: SIAM Fellow (2024) 2013 UBC CS Department Teaching Award CACS Outstanding Young Researcher Prize AI & Statistics 2009 Best Paper Award Advising & Grants: Supervised over 20 graduate students and postdocs. Active in grant-funded research, including projects on optimization algorithms and their industrial applications. Collaborates with institutions like Pacific Institute for Mathematical Sciences (PIMS) and the Data Science Institute at UBC. Labs & Affiliations: Affiliated with the Institute for Computing, Information and Cognitive Systems (ICICS), Data Science Institute, and Quantum Computing Research Cluster at UBC. Leads interdisciplinary efforts in applied mathematics and computational science.

David Slompمشاهده پروفایل

استاد

• Writing Assessment
• Literacy Education
• Classroom Assessment
• +۳ مورد دیگر

Dr. David Slomp serves as Associate Dean of Graduate Studies and Research and Professor in the Faculty of Education at the University of Lethbridge. Previously holding positions at the University of Ottawa and University of Alberta, he specializes in writing assessment and literacy education across educational levels. His leadership includes co-directing the MEd General program in Curriculum and Assessment and serving as Co-Editor-in-Chief of Assessing Writing . His educational background features a Master's degree in Teaching English as a Second Language and a PhD in Secondary Education focused on writing assessment. Key research interests include principled assessment design, ethics and validity in writing evaluation, and writing development across the lifespan. His work critically examines justice, fairness, and equity in literacy assessment practices. Recent publications (2019-2025) demonstrate consistent focus on workplace communication assessment, digital literacy frameworks, and dismantling anti-Black assessment practices. Key trends include sociocognitive construct development, equity-centered design, and big data implications for formative assessment. His scholarship bridges theoretical rigor with practical classroom applications. Dr. Slomp's scientific contributions have been recognized through prestigious awards: Graduate Student Teaching Award, University of Alberta Writing Program Certificate of Excellence, Conference on College Composition and Communication President's Achievement Award, University of Alberta Issak Walton Killam Memorial Scholarship Board of Governor's Teaching Chair, University of Lethbridge As Associate Dean and MEd program co-director, he mentors graduate students and shapes curriculum development. His editorial leadership at Assessing Writing significantly influences global assessment scholarship. Current projects address workplace English communication frameworks and equity-centered design principles through major collaborative research initiatives. Dr. Slomp actively contributes to scholarly communities through editorial work and professional organizations, advancing writing assessment theory and practice globally while addressing contemporary challenges in digital literacy and assessment justice.

Gilles Peslherbeمشاهده پروفایل

استاد

• Computational Chemistry
• Molecular and Reaction Dynamics
• Nanomaterials and Materials Engineering
• +۸ مورد دیگر

Gilles Peslherbe is a Professor at Concordia University, cross-appointed in the departments of Chemistry and Biochemistry , Physics , and Chemical and Materials Engineering . He leads the Centre for Research in Molecular Modeling (CERMM) and supervises graduate students in programs spanning Chemical Engineering, Chemistry, Physics, and Nanoscience. PhD in Physical Chemistry with Minor in Computer Engineering (Wayne State University, USA) Diplôme d'Ingénieur Chimiste (Ecole Supérieure de Chimie Industrielle de Lyon, France) His research integrates computational chemistry , quantum mechanics , and machine learning to model chemical processes in extreme conditions, drug delivery systems, and environmental impact assessments. Collaborative projects include studies on spin catalysis , nanostructured materials , and RNA structure fundamentals . Recent publications highlight applications of artificial intelligence in therapeutics development , density-functional theory in nanomaterials , and ultrasfast spectroscopy in electron solvation . His work bridges quantum computing and biological simulations . Teaching includes courses on quantum theory , computational chemistry , and statistical mechanics . He actively seeks students for ongoing projects in chemical interactions in extreme conditions and environmental remediation .

W. Kendal Busheمشاهده پروفایل

دانشیار

• Combustion
• Turbulence
• Numerical Simulation
• +۳ مورد دیگر

W. Kendal Bushe is an Associate Professor at the Faculty of Applied Science , University of British Columbia , within the Department of Mechanical Engineering . His research focuses on turbulent combustion, numerical simulation, and computational fluid dynamics (CFD) with applications to internal combustion engines and thermal power generation. Developed the Conditional Source-term Estimation (CSE) method for turbulent combustion modeling. Conducted experimental studies on methane/natural gas ignition in engines. Expertise in Reynolds-Averaged Navier-Stokes (RANS) and Large Eddy Simulation (LES) for reacting flows. Current projects involve autoignition modeling in HCCI engines using Stochastic Particle Models . Teaching Activities : Courses on heat transfer, energy conversion systems, computational fluid dynamics, combustion, and turbulent shear flows. Scientific Recognition : Fellow of the Combustion Institute.

Rajeev Jaimanمشاهده پروفایل

استاد

• Fluid-structure interaction
• Computational mechanics
• Intelligent ocean systems
• +۳ مورد دیگر

Rajeev Jaiman is a Professor in the Department of Mechanical Engineering at the University of British Columbia's Faculty of Applied Science. A graduate of IIT Bombay (B.Tech) and the University of Illinois at Urbana-Champaign (M.S., Ph.D. in Aerospace Engineering), he holds the NSERC/Seaspan Industrial Research Chair in Intelligent and Green Marine Vessels (IGMVs) and is recognized as a SNAME Fellow. PhD in Aerospace Engineering from University of Illinois, Urbana-Champaign Senior Member of AIAA and member of APS, ASME, SNAME, and USACM His research focuses on fluid-structure interaction , computational mechanics , and data-driven modeling for marine/aerospace applications. Current work includes: High-fidelity multiphysics simulations Machine learning integration for fluid dynamics Phase-field methods for interface capturing Bio-inspired structural optimization Flow control techniques for vortex-induced vibration Recent publications emphasize graph neural networks for fluid dynamics prediction, phase-field modeling of complex interactions, and machine learning applications in multiphase flows. Research trends show strong interdisciplinary connections between computational mechanics, ocean engineering, and data science. Scientific awards include: NSERC/Seaspan Industrial Research Chair Fellow of The Society of Naval Architects and Marine Engineers (SNAME) As director of the Computational Multiphysics Laboratory, he develops high-performance computing frameworks for marine , aerospace , and biomechanics applications. His work spans numerical algorithms, HPC-based solvers, and bio-inspired design optimization.