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Mohammed AbuibaidView profile

Adjunct Professor

• Hyper-Reliable and Low-Latency Communications
• Industrial Automation Networks
• 5G Networks and Beyond
• +7 more

Dr. Mohammed Abuibaid is an Adjunct Research Professor at Carleton University's School of Information Technology and a Radio Virtual Distributed Unit (vDU) System Designer at Ericsson Canada. As a Senior IEEE Member, he contributes significantly to standards development through IEEE 802 Plenary Sessions and ITU-T Study Group 15 initiatives. His expertise lies in wireless communications with a focus on industrial applications, where he bridges academic research and industry implementation. Dr. Abuibaid earned his Ph.D. from Carleton University, Canada, where he has continued his academic contributions. His educational background has positioned him as a leading expert in next-generation wireless communication systems. Dr. Abuibaid specializes in Hyper-Reliable and Low-Latency Communications (HRLLC) for industrial automation, with research spanning 5G networks and beyond, Time-Sensitive Networking (TSN), Deterministic Networking (DetNet), Massive MIMO systems, and Edge Computing. His innovative approach integrates machine learning techniques to optimize network performance, particularly in balancing reliability with bandwidth utilization in industrial settings. His work addresses critical requirements for Industry 5.0, focusing on resilient networks that can support advanced manufacturing and automation systems. His publication record demonstrates a consistent focus on integrating wireless communication standards with industrial networking requirements. Dr. Abuibaid's research trajectory shows increasing sophistication in addressing the reliability-bandwidth tradeoff through machine learning frameworks and novel system designs that optimize resource utilization while maintaining critical performance metrics for industrial applications. Dr. Abuibaid has received notable recognition for his contributions: Best Industry Paper Award at the 2024 IEEE 10th World Forum on Internet of Things Senior Member of IEEE (since April 2024) As an academic mentor, Dr. Abuibaid supervises student research at Carleton University, focusing on next-generation wireless communication systems. His industry-academic partnership with Ericsson has resulted in significant research funding, including support from the Ericsson-Carleton Partnership Fund and MITACS Canada for the 5G-TSN for Industry 4.0 project. These collaborations have produced innovative solutions that address real-world challenges in industrial networking. Dr. Abuibaid has contributed to establishing the 6G Non-Terrestrial Networks Research Center, collaborating with global technology leaders like Keysight Technologies. His work spans both terrestrial and satellite communication systems, reflecting his comprehensive approach to next-generation network design. He actively participates in standards development through IEEE and ITU-T, ensuring his research has practical impact on emerging communication technologies.

Olav LianView profile

Adjunct Professor

• Quaternary stratigraphy
• glacial geology
• luminescence dating
• +3 more

Olav Lian is an Adjunct Professor at the Department of Earth Sciences , University of the Fraser Valley . His research focuses on Quaternary stratigraphy , glacial geology , and luminescence dating , supported by NSERC funding . He collaborates with experts in geomorphology, physics, and biology. His work spans environmental change analysis in western Canada, the Canadian Arctic, Australia, Patagonia, New Zealand, Russia, and Indonesia. The research integrates interdisciplinary approaches and advanced geochronological methods. Recent Publications highlight innovations in learned image compression , privacy-preserving computing , and computer vision , featuring techniques like Swin Transformers , Wavelet-Domain Convolution , and Entropy-Based Distillation . Contact: olav.lian@ufv.ca

• Blockchain Technology
• Cryptography
• Big Data
• +5 more

Gautam Srivastava is a Professor in the Department of Mathematics & Computer Science at Brandon University (BU), holding concurrent roles as Visiting Professor at Lebanese American University and Adjunct Associate Professor at Lakehead University. His research focuses on Blockchain Technology, Cryptography, Big Data, and Privacy-Preserving Systems. He actively supervises graduate students requiring strong academic credentials. Education: Ph.D. (Computer Science, University of Victoria, 2012), M.Sc. (Computer Science, University of Victoria, 2007), B.Sc. (Mathematics & Computer Science, Briar Cliff University, 2004) Roles: Holds visiting appointments at institutions in Lebanon, Taiwan, and China, and leads research in Cyber-Physical Systems and IoT Security. His research interests emphasize secure communication protocols, federated learning frameworks, and applications of AI in healthcare and industrial systems. Notable work includes blockchain-enhanced IoT security and privacy-preserving machine learning models. Awards: Best Oral Presentation at Fuzzy Systems and Data Mining (FSDM 2017) Grants: Over $200K in funding from NSERC, MITACS, and CIRA for projects on IoT security, federated learning, and edge computing. Dr. Srivastava’s current projects explore quantum-resistant MQTT protocols, federated learning for healthcare diagnostics, and smart city sensor systems.

Ahmed Refaey HusseinView profile

Associate Professor

• Edge Computing
• Network Security
• Blockchain
• +2 more

Dr. Ahmed Refaey Hussein is an Associate Professor in the School of Engineering at the University of Guelph, specializing in Computer Engineering. His research focuses on distributed edge computing, network security, and blockchain applications for next-generation communication systems. He teaches advanced courses in computer architecture and VLSI design while leading research on secure software-defined systems, industrial IoT, and autonomous networking solutions. His work targets practical implementations in smart communities and critical infrastructure protection.

Dan WuView profile

Associate Professor

• Machine Learning
• Uncertain Reasoning
• Robotics
• +3 more

Dr. Dan Wu is an Associate Professor at the School of Computer Science, University of Windsor. His research focuses on uncertain reasoning, machine learning, knowledge representation, and robotics. He holds a PhD from the University of Regina (2003). His work bridges theoretical advancements and practical applications in robotics, traffic systems, and probabilistic inference. Education: PhD in Computer Science, University of Regina, 2003 Research Interests: Machine Learning: Focused on deep learning models for traffic prediction and robotics. Uncertain Reasoning: Developing probabilistic methods for cooperative robotic systems. Robotics: Multi-robot coordination, navigation, and obstacle avoidance. Knowledge Representation: Applications in distributed Bayesian networks and graph-based systems. Publications Trends: Recent work emphasizes urban traffic management (reinforcement learning for signal control), vehicular networks (task offloading in 5G), and privacy-preserving federated learning. Earlier studies addressed multi-robot coverage algorithms and probabilistic localization techniques. Lab/Teams: Active in AI-driven robotics and intelligent transportation systems research, though specific lab names are not explicitly mentioned in the provided texts.

Samuel A. AjilaView profile

Associate Professor

• Software Requirements Engineering
• Micro-Service Architecture
• Cloud Resource Provisioning
• +3 more

Dr. Samuel A. Ajila is an Associate Professor and Associate Dean in the Faculty of Engineering and Design at Carleton University, Canada. He holds a Ph.D. in Software Engineering and Knowledge-based Systems from the Université de Lorraine, France. His academic roles include teaching courses such as SYSC 5703 (Integrated Database and Cloud Systems) and SYSC 4120 (Software Architecture and Design). He is a P.Eng. in Ontario and a Senior Member of both IEEE and ACM. His research focuses on Software Requirements Engineering, Cloud Resource Provisioning, and Machine Learning applications in Data Mining. He has co-authored over 50 publications in journals and conferences, emphasizing topics like federated learning for forest fire prediction and deep learning for air pollution forecasting. His work often bridges theoretical computer science with practical applications in cloud computing and environmental informatics. Education: B.Sc. (Computer Science) - University of Ibadan, Nigeria M.Sc. (Computational Mathematics) - Obafemi Awolowo University Ph.D. (Software Engineering) - Université de Lorraine Dr. Ajila’s research trends span from foundational studies on software impact analysis (1990s) to modern applications of federated learning and spatio-temporal modeling. His recent work highlights collaborations on wildfire prediction using multi-source data and DDoS detection via time series transformers. He has been recognized for contributions to software engineering and cloud computing through IEEE and ACM fellowships. Grants & Advising: Active in collaborative research projects, though specific grant details are not listed here. Supervises graduate students in machine learning and cloud systems. Labs/Teams: Involved in the Carleton Systems and Computer Engineering (SCE) research group, focusing on cloud infrastructure and data-driven solutions.

Youmin ZhangView profile

Professor

• Fault Diagnosis and Tolerant Control
• Avionics and Flight Control
• UAV Systems and Autonomous Vehicles
• +5 more

Youmin Zhang is a Professor in the Department of Mechanical, Industrial and Aerospace Engineering at Concordia University, affiliated with the Concordia Institute of Aerospace Design & Innovation. His research focuses on advanced control strategies for safety-critical systems, including fault diagnosis, fault-tolerant control, and autonomous vehicle systems. His work spans aerospace, industrial, and mechatronic domains, with applications in UAV navigation, spacecraft formation flying, and real-time environmental monitoring. Research interests include: Fault-tolerant control for safety-critical systems Avionics and flight control systems UAV trajectory planning and swarm coordination Modeling and simulation of physical systems Signal processing for diagnostics Recent publications emphasize resilient control architectures, cybersecurity in autonomous systems, and AI-driven solutions for fault detection in industrial processes. His work bridges theoretical control frameworks with practical applications in aerospace, energy, and environmental systems. He holds an academic position at Concordia’s Sir George Williams and Loyola campuses, and his research contributes to advancing autonomous systems and smart manufacturing technologies.

Abdolreza AbhariView profile

Professor

• Artificial Intelligence
• Agent Systems
• Data Science
• +5 more

Dr. Abdolreza Abhari is a Professor and Undergraduate Program Director in the Department of Computer Science at Toronto Metropolitan University. His research focuses on Artificial Intelligence, Agent Systems, Data Science, Distributed Systems, and Network Simulation. He holds a PhD from Carleton University (2003) and has received notable grants including CFI, NSERC, and OGS funding. His professional roles include serving as Conference/Track Chair for Spring Simulation Conference and as an IEEE Senior Member. He leads the Data Science research group and the Distributed and Multimedia Processing (DSMP) lab. Awards include the Nortel Network Scholarship for Ph.D. studies and industry grants from AutoDesk Inc. His work spans simulation modeling, edge computing, and social network analysis. Education: PhD in Computer Science, Carleton University (2003). Research Interests: Dr. Abhari’s expertise includes developing simulation frameworks for distributed systems, optimizing network architectures, and applying machine learning to social networks. His work integrates theoretical models with practical applications in smart cities, video streaming, and fault-tolerant systems. Awards & Grants: Recipient of major research grants (CFI, NSERC) and industry partnerships. His contributions to simulation methodologies have been recognized through scholarships and collaborative projects. Advising & Labs: Leads the Data Science group and DSMP lab, focusing on edge computing, video analytics, and scalable data management. His research addresses real-world challenges in distributed systems and AI-driven solutions.

Sazia MahfuzView profile

Assistant Professor

• Streaming IoT data analytics
• Lifelong machine learning
• Medical image analytics

Dr. Sazia Mahfuz is an Assistant Professor at the Jodrey School of Computer Science, Acadia University. She holds a Ph.D. from Queen’s University, an M.Sc. from Acadia University, and a B.Sc. from the University of Dhaka, Bangladesh. Her research focuses on Streaming IoT Data Analytics, Lifelong Machine Learning, and Medical Image Analytics, addressing challenges in real-time data processing, adaptive learning systems, and healthcare technology. Dr. Mahfuz’s work spans interdisciplinary applications including human activity recognition, vehicular sensor data classification, and diabetic retinopathy detection using deep learning. Her recent contributions emphasize hybrid architectures (CNN-RNN), transformer-based models, and frameworks for multi-level data analytics. She has published extensively on topics ranging from wearable sensor optimization to distributed data stream processing. Her research trends highlight a strong emphasis on IoT-enabled healthcare solutions and lifelong machine learning algorithms that generate synthetic examples to improve model adaptability. While no awards are listed, her articles reflect significant engagement with both theoretical and applied computer science domains. No advising or grant information is provided in the text.

Ekram HossainView profile

Professor

• Wireless Communications
• 6G and Beyond Cellular Networks
• AI/Machine Learning
• +5 more

Dr. Ekram Hossain is a Professor in the Department of Electrical and Computer Engineering at the University of Manitoba, serving as Associate Chair (Graduate Studies). He is a Fellow of the Canadian Academy of Engineering and the Engineering Institute of Canada, and an IEEE Fellow (2015). His research focuses on wireless communication networks, AI-driven 6G systems, and resource management. He leads the WiCoNS research group and holds editorial roles in top journals like IEEE Transactions on Mobile Computing. Education: Ph.D. in Electrical Engineering (University of Victoria, 2001) Professional Roles: IEEE Distinguished Lecturer (2012-2020), Board Member of IEEE Communications Society Research Interests span 6G networks, reconfigurable intelligent surfaces, non-orthogonal multiple access, and green radio. Notable contributions include over 20 books and numerous award-winning papers. Awards include the 2024 IEEE Education Award and Clarivate Highly Cited Researcher recognition (2017-2024). Awards & Recognition: Multiple IEEE awards, Royal Society of Canada membership, and leadership in professional organizations like IEEE Canada. Advising & Grants: Supervised over 30 graduate students. Secured funding from NSERC and industry partners for projects on heterogeneous networks and 5G/6G technologies. Active in global initiatives like the Next G Alliance Research Council. Labs/Teams: WiCoNS group focuses on AI-driven wireless systems, edge computing, and network virtualization.

Shengrong BuView profile

Associate Professor

• Smart Grids
• Wireless Network Security
• Deep Reinforcement Learning
• +3 more

Shengrong Bu is an Associate Professor at the Department of Engineering, Brock University, Canada. She holds a Ph.D. in Electrical and Computer Engineering from Carleton University and has held academic positions at the University of Glasgow and industrial roles at Huawei Technologies. Her research bridges smart grid communications, wireless network security, and deep reinforcement learning applications. Ph.D., Electrical & Computer Engineering, Carleton University MEng by Research, Electrical Engineering, University of Wollongong BEng, Mechanical Engineering & Automation, Huazhong University Research focuses on: Multi-vector energy microgrids and smart grid communications Deep reinforcement learning for network optimization Game theory applications in energy systems Big data analytics for grid resilience Articles show expertise in P2P energy trading, fog computing resource allocation, and wireless security in smart grid environments, with funding from EPSRC and NSERC. Awards include multiple IEEE best papers and prestigious research fellowships. She supervises Ph.D. and MSc students in energy systems research.

Jianbing NiView profile

Assistant Professor

• Mobile Network Security
• Trustworthy Artificial Intelligence
• Cloud Computing Security
• +2 more

Dr. Jianbing Ni serves as Assistant Professor and Chair of Undergraduate Studies for Computer Engineering in the Department of Electrical and Computer Engineering at Queen's University, holding the Tier-2 Canada Research Chair in Intelligent System Security and Privacy. He maintains affiliations with Ingenuity Labs Research Institute and co-chairs the IEEE Blockchain Canada Chapter. Education: PhD in Electrical and Computing Engineering, University of Waterloo (2018), supervised by Prof. Sherman Shen and Prof. Xiaodong Lin Research Focus: Dr. Ni pioneers research in mobile network security , trustworthy AI systems , cloud/edge computing security , and blockchain technology . His work develops privacy-preserving frameworks for intelligent distributed systems, emphasizing real-world applications in vehicular networks and scalable computing environments. Scientific Recognition: 9 best paper awards from premier conferences (IEEE GLOBECOM, ICC, SECURECOMM) Best Paper Award for IEEE Transactions on Mobile Computing (2022) IEEE Vehicular Technology Society Early Career Award (2022) IEEE Scalable Computing Award for Excellence (2023) IEEE ComSoc CISTC Early Career Award (2024) Leadership & Mentorship: As Symposium Chair for IEEE ICC 2024 and associate editor for IEEE Transactions on Information Forensics and Security, Dr. Ni actively recruits postdoctoral fellows and graduate students. His research group focuses on security challenges in AI-driven systems, with current openings for PhD and Master's candidates in security, privacy, and blockchain domains.

• Internet architecture and protocols
• Multimedia content distribution and processing
• Wireless mobile networking
• +5 more

Prof. Jiangchuan Liu is a Professor in the School of Computing Science at Simon Fraser University (SFU), holding prestigious fellowships from the Canadian Academy of Engineering, IEEE, and NSERC. His research focuses on Internet architecture, wireless networks, cloud computing, and multimedia systems. He teaches courses in data communications and multimedia computing. Education: Ph.D. Computer Science, The Hong Kong University of Science & Technology, 2003 B.Eng. (Cum Laude), Tsinghua University, Beijing, 1999 Research Interests: His work spans energy-efficient networking, pervasive backscatter systems, edge computing, and 5G/6G mobile vision analytics. He emphasizes practical IoT applications, including wearable health monitoring and smart grid management. Article Trends: Recent publications address satellite networking (e.g., Starlink performance), battery-free wearables, and AI-driven multimedia systems. A key theme is integrating energy-efficient communication with emerging technologies like 6G and edge intelligence. Awards: Canadian Academy of Engineering Fellow, IEEE Fellow, NSERC E.W.R. Steacie Memorial Fellow Labs & Teams: Active in the Tangent Lab , exploring edge-assisted analytics and immersive media systems. Collaborates on projects like PupilHeart for mobile health monitoring and Apollo for battery-free wearables.

Trung Q. DuongView profile

Professor

• Wireless Communications
• Quantum Communications
• Quantum Machine Learning
• +8 more

Trung Q. Duong is a Canada Excellence Research Chair and Full Professor at Memorial University of Newfoundland, Canada. He specializes in wireless and quantum communications, with a focus on 5G/6G networks, IoT applications, and quantum machine learning. His research addresses challenges in network optimization, digital twin integration, and UAV-based communication systems. Education: PhD in Telecommunications Systems from Blekinge Institute of Technology, Sweden. Research Interests: Quantum machine learning, real-time optimization for UAVs, integrated satellite-terrestrial networks, and security in communications. His work spans applications in healthcare, disaster management, and smart cities. Key Achievements: Over 500 publications (20,000+ citations, h-index 76), $54M+ in grants, and prestigious awards like the Newton Prize and IEEE Fellowship. He serves as an editor for top journals such as IEEE Trans. on Wireless Communications and IEEE Wireless Communications Letters. Global Collaborations: Visiting Professorships at National Chung Cheng University (Taiwan), Kyung Hee University (South Korea), and Thuyloi University (Vietnam). Active in international grant review panels across 20+ countries.

Gabriel A. WainerView profile

Professor

• Discrete-Event Modeling and Simulation
• Real-Time Systems
• Cellular Models
• +4 more

Professor Gabriel A. Wainer holds a Ph.D. from the Universidad de Buenos Aires and is a Full Professor at Carleton University's Department of Systems and Computer Engineering, Faculty of Engineering and Design. His research focuses on Discrete-Event Modeling and Simulation (DEVS), Real-Time Systems, and Parallel/Distributed Simulation. He leads the Advanced Real-Time Simulation (ARS) Lab at Carleton's V-Sim Centre, collaborating with industry partners like Ericsson Canada on projects such as channel reconstruction for wireless networks and AI-driven spectrum sharing. Wainer is a Fellow of the Society for Modeling and Simulation International (SCS) and an ACM Distinguished Speaker, with over 450 publications and significant grant funding. He has mentored numerous students and researchers, contributing to Carleton's academic and research excellence. Education: Ph.D. (Computer Science, Universidad de Buenos Aires, 1998), M.C.S. (Universidad de Buenos Aires, 1993). He has held visiting roles at institutions worldwide, including INRIA and the University of Nice. Research interests include DEVS formalism, cellular models, and real-time operating systems. His work bridges theory and application, addressing challenges in embedded systems, IoT, and pandemic modeling. Awards include the McLeod Founder Award (2022), SCS Outstanding Professional Achievement (2020), and IEEE Outstanding Engineering Award (2019). Labs/Teams: Advanced Real-Time Simulation Lab (ARS), part of Carleton's V-Sim Centre. Grants: Over $4.3M as PI and $1.2M as co-applicant, totaling $30M+ in collaborative funding. Advising: Supervised 12 postdocs, 19 PhDs, 16 RAs, 71 MSc students, and 150+ undergrads since 1997.