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Dr. Tarek Sayed is a Professor at the University of British Columbia's Department of Civil Engineering within the Faculty of Applied Science. He specializes in Transportation Engineering, focusing on road safety analysis, traffic operations, and Intelligent Transportation Systems (ITS). He serves as the Director of the Bureau of Intelligent Transportation Systems and Freight Security (BITSAFS-Engineering) and Editor of the Canadian Journal of Civil Engineering . His research addresses three core areas: improving road safety evaluation techniques, enhancing safety through traffic operations and highway design analysis, and advancing ITS technologies. Notable contributions include frameworks for safety-audits of infrastructure projects like the Sea to Sky Highway and methodologies for evaluating transit signal priority systems in Vancouver. He has authored/co-authored over 250 publications and supervised 60 graduate students. Key Roles: Professor, BITSAFS Director, Journal Editor Awards: Tier 1 Canada Research Chair, Wilbur Smith Award, Sandford Fleming Award, Prince Michael International Road Safety Award Consulting: Global projects in traffic safety and ITS for agencies like ICBC, FHWA, and Ashghal His research integrates Bayesian statistical methods, extreme value theory, and machine learning to model traffic conflicts, pedestrian behavior, and safety interventions. Current projects include real-time safety optimization using autonomous vehicle data and analyzing shared space interactions between cyclists and pedestrians. Dr. Sayed chairs national/international committees, including the U.S. Transportation Research Board’s safety data committee. His work bridges academia and practice, influencing policy and infrastructure investment decisions worldwide.

• Transportation Engineering
• Traffic Safety Analysis
• Intelligent Transportation Systems (ITS)
• +4 more

Dr. Saiedeh Razavi is an Associate Professor and the inaugural Chair in Heavy Construction at McMaster University's Department of Civil Engineering, directing the McMaster Institute for Transportation and Logistics (MITL). She holds a multidisciplinary background with degrees in Computer Engineering (B.Sc., Sharif University), Artificial Intelligence (M.Sc., Iran), and Civil Engineering (Ph.D., Waterloo). Her research focuses on smart infrastructure, connected mobility, and construction safety, funded by NSERC and the Ontario Ministry of Transportation. Key areas include transforming construction management through AI, autonomous vehicles, and smart work zones. Education: B.Sc. (Sharif), M.Sc. (Iran), Ph.D. (Waterloo) Research Interests: Smart cities, connected vehicle systems, data fusion, risk analysis, and sustainable logistics Leadership Roles: Director of MITL, Associate Chair (Research), and lead of national/international multidisciplinary projects Her work bridges academia, government, and industry to enhance mobility and safety. Notable grants include NSERC funding for transformative transportation systems. Awards include teaching excellence and innovation in team-based projects. Grants & Projects: NSERC, Ontario Ministry of Transportation, and industry collaborations Labs/Teams: MITL, CPS-based construction safety initiatives, and autonomous vehicle research groups

• Smart Infrastructure
• Intelligent Transportation Systems
• Construction Management Automation
• +5 more

Waël Jaafar is a Professor in the Department of Software Engineering and IT at École de technologie supérieure (ETS), a constituent school of the Université du Québec system in Montreal, Canada. His research spans multiple critical domains in modern communications and computing infrastructure, with a particular focus on next-generation wireless networks and intelligent systems. Dr. Jaafar holds a B.Eng. from Sup'Com Tunisie, and both M.Sc.A. and Ph.D. degrees from Polytechnique Montréal. His academic background provides a strong foundation for his interdisciplinary research that bridges theoretical concepts with practical engineering solutions. His research interests center around wireless communications systems, with particular emphasis on 5G/6G networks, UAV communications, space telecommunications, and machine learning applications for networking. He has developed significant expertise in federated learning techniques for distributed networks, cybersecurity applications for next-generation mobile systems, and edge computing architectures. His work frequently explores the intersection of communication theory, artificial intelligence, and network security, with applications ranging from industrial IoT to public safety communications. Analysis of his recent publications reveals a strong trend toward integrating artificial intelligence with wireless networking infrastructure, particularly focusing on UAV-assisted communications, federated learning approaches for distributed networks, and security enhancements for 5G/6G systems. His research demonstrates increasing emphasis on practical implementation challenges including energy efficiency, communication overhead reduction, and reliability in non-ideal network conditions. As an academic supervisor, Dr. Jaafar actively mentors numerous graduate students across various projects. He currently supervises doctoral candidates working on blockchain-enhanced security for 5G networks, green network slice orchestration, and federated learning approaches for Open RAN architecture. His master's students are engaged in diverse topics including LiDAR-based power line monitoring, multimodal behavioral authentication, and 5G/6G security using AI techniques. Dr. Jaafar is affiliated with two prominent research laboratories at ETS: LASI (Computer System Architecture Research Laboratory) and LACIME (Communications and Microelectronic Integration Laboratory). At LASI, he contributes to research in AI-based systems engineering, resource orchestration in edge/cloud environments, and intelligent network design. Through LACIME, he engages with broader communications research spanning from microelectronic components to complex communication systems, with particular focus on wireless networks and signal processing applications.

• Wireless Communications
• 5G/6G Networks
• Space Telecommunications
• +7 more

Tae J. Kwon is an Associate Professor in the Department of Civil and Environmental Engineering at the University of Alberta . His research spans Winter Transportation Engineering , Intelligent Transportation Systems (ITS) , Traffic Optimization , and Geospatial Information Science . Developed LoRWIS , a web-based decision support system for road weather sensor optimization Recipient of multiple awards including ITS Canada Excellence in Research and Development Award (2024) , KOFST Scientist of the Year (2024) , and Early Career Research Award (University of Alberta, 3 times) Active in professional committees like the TRB Surface Transportation Weather Research Group (2016–present) Research Highlights : Winter Road Maintenance : Advanced geostatistical and deep learning techniques for road condition monitoring Location Optimization : Pioneered models for RWIS sensor placement using hybrid geostatistical methods Intelligent Transportation Systems : Focused on big data applications for traffic safety and connected vehicles Climate Resilience : Integrated ecological vulnerability into fire hazard modeling Scientific Awards : ITS Canada Excellence in Research (2024) KOFST Scientist of the Year (2024) Donald Stanley Best Paper Award (2023) AKCSE Early Achievement Award (2021) University of Alberta Early Career Research Award (2020) Great Supervisor Award (2019) Teaching & Leadership : Teaches courses like CIV E 419 (Transportation Engineering: Highway Planning and Design) and CIV E 612 (Transportation Planning: Methodology and Techniques) Leads the Geospatial Transportation System & Sensing Solutions Lab (GeoTrans) , mentoring PhD students Juan Cuellar and Jiehao Bi Collaborates with agencies including Alberta Transportation , NSERC , and Iowa DOT

• Transportation Engineering
• Location Optimization
• Geospatial Information Science
• +4 more

Professor Chris Lee is a faculty member in the Department of Transportation Science and Engineering at the University of Windsor's Faculty of Engineering. His research focuses on advancing transportation safety through the analysis of driver behavior, traffic flow dynamics, and the integration of emerging technologies like autonomous vehicles and machine learning. Key areas include collision risk prediction, driver vigilance assessment, and the development of advanced car-following models. He has contributed to initiatives such as the Transportation Science and Engineering scholarship program, supporting student research in innovative technologies like driving simulators for lane change behavior studies. His work bridges engineering and human factors, addressing challenges such as driver response to autonomous systems, heavy vehicle traffic management, and cross-cultural automotive design. Lee's interdisciplinary approach leverages data analytics, physiological signals, and machine learning to solve real-world transportation problems. His research has implications for policy-making, infrastructure design, and vehicle safety standards. Lee has collaborated extensively on projects analyzing crash precursors, variable speed limits, and the impact of ITS (Intelligent Transportation Systems) on safety. His publications span over two decades, demonstrating a commitment to both academic rigor and practical applications in transportation engineering. Notable contributions include refining car-following models, studying driver aggression, and evaluating the effectiveness of traffic management strategies.

• Transportation Engineering
• Traffic Safety
• Driver Behavior Analysis
• +5 more

Robson E. De Grande is an Associate Professor in the Department of Computer Science at Brock University, Canada. He holds a PhD from the University of Ottawa (2012) and BSc/MSc degrees from the Federal University of São Carlos, Brazil. His research focuses on vehicular networks, intelligent transportation systems, distributed systems, and cloud computing. He serves on program committees for conferences like DS-RT, MobiWac, and MSWiM, and has organized multiple workshops and special sessions. Education: PhD in Computer Science, University of Ottawa, Canada (2012) MSc and BSc in Computer Science, Federal University of São Carlos, Brazil (2006, 2004) Research Interests: Vehicular Networks (5G, Handover Management) Edge Computing and IoT Performance Modeling/Simulation High-Performance Distributed Systems Intelligent Transportation Systems Publications: Over 100 peer-reviewed articles across journals like IEEE Transactions on ITS, Elsevier Internet of Things, and conferences like IEEE ICC and ACM MobiWac. Recent work emphasizes ML-driven vehicular network optimization and distributed simulation frameworks. Teaching: Teaches Advanced Computer Networks (COSC 4P14), Parallel Computing (COSC 3P93), and graduate-level Mobile Cloud Computing courses. Research Team: Supervises PhD/MSc students and undergraduate researchers in topics like vehicular edge computing, traffic prediction, and simulation systems.

• Vehicular Networks
• Intelligent Transportation Systems
• Cloud Computing and Networking
• +5 more

Alessandro Lameiras Koerich is a Professor in the Department of Software Engineering and IT at École de technologie supérieure (ÉTS), part of the Université du Québec network in Montreal, Canada. He is affiliated with the LIVIA (Imaging, Vision and Artificial Intelligence Laboratory), where he conducts research in machine learning, computer vision, and pattern recognition. His work focuses on developing AI solutions for real-world applications in healthcare, security, and multimedia analysis. His research interests span multiple domains of artificial intelligence, with particular emphasis on multimodal machine learning, affective computing, and trusted machine learning systems. Dr. Koerich's work explores how AI can interpret human emotions through facial expressions and audio analysis, develop robust models resistant to adversarial attacks, and create efficient learning systems that can adapt to changing data streams. His research bridges theoretical advances with practical applications in healthcare monitoring, security systems, and multimedia content analysis. Analysis of his recent publications reveals a strong focus on multimodal emotion recognition, with increasing emphasis on transformer architectures, knowledge distillation techniques, and addressing challenges in real-world settings (in-the-wild recognition). His work consistently combines computer vision with audio processing, demonstrating expertise in both visual and auditory modalities for affective computing applications. Recent trends show growing interest in large language models for audio classification and addressing challenges of concept drift in text stream mining. Dr. Koerich actively supervises numerous graduate students across various research projects, with a particular focus on multimodal expression recognition, music genre classification, and robust machine learning systems. His collaborations span multiple institutions and research groups, reflecting the interdisciplinary nature of his work in artificial intelligence. He is a key member of the LIVIA laboratory, which has established ÉTS as a leading institution in computer vision research in Canada (ranked 6th according to CSRankings). The laboratory focuses on solving real-life problems through AI engineering, particularly in developing complex deep learning models with massive amounts of data that have incomplete annotations.

• Machine Learning
• Computer Vision
• Pattern Recognition
• +6 more

Eric D. Hildebrand is a Professor of Civil Engineering at the University of New Brunswick (UNB), specializing in Highway Safety, Transportation Planning, and Traffic Engineering. He holds a PhD from the University of Waterloo and BScE/MScE degrees from UNB. His research focuses on road safety engineering, traffic simulation, accident reconstruction, and elderly driver mobility. Education: PhD in Civil Engineering (University of Waterloo), BScE and MScE (University of New Brunswick). Research interests include: Road Safety Audits and Reviews Microsimulation for Transportation Planning Climate Change impacts on Highway Design Intelligent Transportation Systems (ITS) GIS-based Travel Demand Modeling Publications span topics like roundabout safety, traffic signal optimization, and driver adaptation to infrastructure changes. Recent awards include the 2023 Lifetime Achievement Award (CARSP) and the Sanford Fleming Award (2017). He chairs or participates in key organizations: Past President, Canadian Transportation Research Forum Transportation Association of Canada (Road Safety Standing Committee) Canadian Association of Road Safety Professionals Teaching includes courses on Transportation Engineering, Traffic Engineering, and Road Safety Engineering.

• Highway Safety
• Transportation Planning
• Traffic Engineering
• +5 more

Dr. Ali Dehghantanha is a Professor and Canada Research Chair in Cybersecurity and Threat Intelligence (Tier 2) at the University of Guelph's School of Computer Science. He founded the Cyber Science Lab, the Master of Cybersecurity and Threat Intelligence (MCTI) program, and the Canada Cyber Foundry. His expertise spans cybersecurity, AI, and critical infrastructure protection, with a focus on federated learning, threat intelligence, and enterprise risk management. Research Interests: Cybersecurity & AI Integration Federated Learning Security IoT and Industrial Cyber-Physical Systems Adversarial Machine Learning Cyber Threat Intelligence Automation His research emphasizes practical applications, such as securing agri-food systems, blockchain-enabled frameworks, and autonomous cybersecurity solutions. Notable achievements include the IEEE Outstanding Leadership Award (2021) and leadership in national cybersecurity initiatives. Recent Contributions: Recent work explores federated learning for privacy-preserving threat detection in IoT, AI-driven malware hunting, and autonomous systems for intrusion detection. His publications highlight interdisciplinary approaches to cybersecurity challenges in critical sectors like agriculture and transportation. Awards: Canada Research Chair (2020–present), IEEE Outstanding Leadership Award (2021). Labs & Initiatives: Cyber Science Lab: Pioneering research in AI-driven cybersecurity Canada Cyber Foundry: Bridging academic and industry cybersecurity innovation MCTI Program: Training next-generation cybersecurity professionals

• Cybersecurity
• Artificial Intelligence
• Machine Learning
• +7 more

Anjali Awasthi is a Professor at the Concordia Institute for Information Systems Engineering, Concordia University. She specializes in research areas including Sustainable Mobility, City Logistics, Intelligent Transportation Systems, and Supply Chain Management. Her work integrates cybernetics and IT-driven decision-making frameworks to address urban and logistical challenges. Dr. Awasthi supervises Master’s (MASc) and PhD programs in Quality Systems Engineering, Industrial Engineering, and Information and Systems Engineering. Her research focuses on optimizing transportation systems, reducing congestion, and enhancing sustainability through technology and systemic approaches. No specific awards, grants, or laboratory affiliations are detailed in the provided information.

• Sustainable Mobility
• City Logistics
• Intelligent Transportation Systems
• +6 more

Animesh Animesh is an Associate Professor and Area Coordinator of Information Systems at McGill University's Desautels Faculty of Management. His research examines the economic and strategic impacts of digital technologies, with focus areas including online advertising, social media analytics, platform ecosystems, and sustainable business models. Animesh's work combines econometric analysis with large-scale data to investigate how digital innovations transform business practices. Recent studies explore AI hallucination detection, open government data economics, and sustainability communication strategies. His research on software patents has influenced understanding of innovation management in competitive IT markets. Animesh maintains industry partnerships through the McGill Dobson Centre for Entrepreneurship.

• Online Advertising
• Social Media Analytics
• Digital Commerce
• +2 more

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.

• Connected and autonomous vehicles (CAVs)
• Intelligent transportation systems (ITS)
• Advanced traveler information systems
• +2 more

Dr. Akramul Azim is an Associate Professor in the Department of Electrical, Computer and Software Engineering at Ontario Tech University, Faculty of Engineering and Applied Science. His research focuses on real-time systems, embedded software, safety-critical systems, IoT, software verification/validation, and applied machine learning. He leads the Real-Time Embedded Software Research (RTEMSOFT) Lab and has contributed to over 50 peer-reviewed publications. His work spans cybersecurity for automotive systems, edge computing optimization, and AI-driven software testing. Education: PhD (Electrical and Computer Engineering), University of Waterloo (2014) MSc (Computer Science and Engineering) (2009) BSc (Computer Science and Information Technology) (2006) Research Interests: Dr. Azim explores the intersection of real-time systems and machine learning, particularly in embedded environments. Key areas include: Autonomous vehicle safety Edge/IoT security Optimized task scheduling ML-enhanced software testing FPGA vulnerability mitigation Recent Research Trends: His publications (2023-2025) highlight advancements in LLM-based code optimization, lock contention mitigation in Java, energy-efficient vehicular networks, and safety-critical AI applications. Notable contributions include frameworks for situation-aware adaptation in ITS and reinforcement learning for edge task scheduling. Labs/Teams: Directs the RTEMSOFT Lab, collaborating on projects like AD-CGAN for anomaly detection and ESOps agile pipeline development.

• Real-Time Systems
• Embedded Software
• Safety-Critical Systems
• +5 more

Pooneh Maghoul is a Full Professor in the Department of Civil, Geological and Mining Engineering at Polytechnique Montréal. She founded and directs the Sustainable Infrastructure and Geoengineering Laboratory (SIGLab), and is a member of Astrolith (Lunar Research Unit) and the Geotechnical Research Group (GRG). With over 14 years of academic and industrial experience in Canada and France, she chairs the Education Committee of the Canadian Geotechnical Society (CGS) and serves on its Board of Directors, as well as the Canadian Permafrost Association (CPA). Ph.D. (2007–2010), M.Sc. (2006–2007) - École des Ponts ParisTech Postdoc (2010–2012) - Université Laval B.Sc. (2002–2006) - University of Tehran Her research focuses on poromechanics of complex porous media and subsurface systems under multi-hazard conditions, including climate change , earthquakes , and lunar environments . Key areas include permafrost stability , bio-inspired drilling , non-destructive testing , and lunar subsurface exploration . Recent publications highlight her work on ultrasonic characterization of frozen soils , climate-resilient Arctic infrastructure , and AI-driven permafrost thaw prediction . She has pioneered waterless drilling technology adaptable for lunar regolith exploration and developed geothermal energy solutions for cold regions. 2023 : Canada's Outstanding Young Geotechnical Engineer 2022 : Canadian Geotechnical Society Recognition Multiple : Best Paper Awards in International Journals She has supervised 2 Ph.D. and Master’s students, including Cui, S. (2023) and Afsharipour, M. (2023). Her work bridges earthquake engineering , computational mechanics , and space geotechnics , with recent grants from the Canada Foundation for Innovation and Fonds de recherche du Québec.

• Geotechnical Engineering
• Earthquake Engineering
• Solid Mechanics
• +11 more

Ryad Titah is a Professor and Chair of the Department of Information Technologies at HEC Montréal. His academic roles include editorial board memberships (Organization Studies, European Journal of Information Systems) and leadership positions such as Past President of the Administrative Sciences Association of Canada. He holds a Ph.D. in Administration from HEC Montréal, an M.Sc. in Information Technology from École de technologie supérieure (ÉTS), and a Bachelor's in Economics from Université d'Alger. His research expertise spans Digital Cities, AI ethics, Electronic Government, Cybersecurity, and NeuroIS. Recent work explores AI's societal impacts, cloud computing adoption biases, and IT's role in organizational performance. He has published extensively in journals like International Journal of Human-Computer Studies and MIT Sloan Management Review. Ryad supervises PhD and Master’s students, including Zoubeir Tkiouat (PhD 2025) and 7 MSc graduates. He is affiliated with research groups like GReSI, Tech3Lab, and Cyberjustice Technologies. Current projects focus on smart city apps, cybersecurity in public services, and AI ethics in criminal justice.

• Digital Cities
• Societal impacts of artificial intelligence and digital technologies
• Electronic Government
• +7 more