Dr. Hatem Abou-Zeid, PhD
Schulich School of Engineering, Department of Electrical and Software Engineering
Adjunct Assistant Professor
School of Computing, Queen's University, Canada
Adjunct Assistant Research Professor
Department of Computer Science, Carleton University, Canada
PhD Electrical and Computer Engineering, Queens University,
I am an Assistant Professor in the Department of Electrical and Software Engineering at the University of Calgary. My research expertise is in communication networks, artificial intelligence (AI), and beyond 5G applications. Within these areas, I currently focus on accelerated learning and safe AI, reliable low-latency communications, extended reality and digital twins, brain-computer interfaces, and Industrial IoT.
I worked in industry for 7 years at Ericsson and Cisco before joining the University of Calgary. My industry roles encompassed both the research of novel communication methods and the development of production grade software implementations of networking solutions. I was fortunate to see many of these techniques deployed in service provider networks worldwide. I also led long-term R&D projects that resulted in 19 patent filings and guidance to the product teams for future networking innovations. Some of these are intelligent scheduling for virtual reality, reinforcement learning algorithms for interference mitigation, 4G/5G spectrum sharing management, RF power control, and link adaptation.
I am an avid supporter of industry-university partnerships and applied research. While at Ericsson, I served on the Ericsson Government Industry Relations and Talent Development Committees where I led and contributed in creating collaborative research projects involving over 25 students and valued at more than $3.5 Million. For more information about my research and interests, please visit my Projects page and Google Scholar pages.
Areas of Research
- Semantic Communications
- Low Latency Communications & Edge Networking
- Joint Sensing and Communications
- Space and Non-Terrestrial Networking
- Application of AI in networks, extended reality, and brain computer interfaces with a focus on:
- Efficient and Interpretable AI
- Safe Reinforcement Learning Algorithms
- Transfer-learning, Online Learning, Meta-learning
- Distributed and Federated Learning
- Application areas: Extended Reality, Digital Twins & Brain Computer Interfaces
- Cross-stack Network Innovations and Efficient Algorithms
- Testbed Prototyping & Evaluation
|Course number||Course title||Semester|
|ENDG 511||Industrial Internet of Things Systems and Data Analytics||Winter 2023|
|ENEL 680||Applied Optimization for Sustainable Design||Fall 2022|
|ENEL 594||Accelerated Low-Latency Machine Learning for Wireless Communication Functions||Winter 2023|
Investigating novel methods for reliable extended reality (XR) experiences and digital twins over wireless networks. This project is in collaboration with a leading 5G wireless network service provider and an XR content creator.
The research objectives of this project are to:
- design robust artificial intelligence techniques for future networks that enable reliable 6G services without compromising operational safety.
- model and explore traffic & user QoE of 6G services such as extended reality, critical IoT, multi-sensory communications.
- invent novel 6G architectures and protocols using methods from predictive communications, cross-layer and joint user-network-aware designs, joint sensing and communication, semantics etc.
Topics of research include design of low-latency aerial communication techniques, interference mitigation, drone positioning algorithms, and latency-aware drone control.
Topics of research include anticipatory scheduling for autonomous vehicles, microscopic vehicle mobility and maneuver prediction.
Topics of research include adaptive configured grant scheduling for factory automation, joint communication and path planning of UAVs.
Topics of research include network traffic prediction using real network data, hybrid deep learning architectures for spatiotemporal mobility modeling, anticipatory network slicing using reinforcement learning, predictive mobility-aware hand-overs.
- Ahmad Nagib, Hatem Abou-Zeid, Hossam Hassanein. IEEE Network. (2022)
- Roghayeh Joda, Medhat Elsayed, Hatem Abou-zeid, Ramy Atawia, Akram Bin Sediq, Gary Boudreau, Melike Erol-Kantarci, Lajos Hanzo. IEEE Network. (2022)
- Sihao Zhao, Hatem Abou-zeid, Ramy Atawia, Yoga Suhas Kuruba Manjunath, Akram Bin Sediq, Xiao-Ping Zhang. IEEE GLOBECOM 2021. (2021)
- Ahmad M Nagib, Hatem Abou-Zeid, Hossam S Hassanein. IEEE LCN 2021. (2021)
- Jie Mei, Xianbin Wang, Kan Zheng, Gary Boudreau, Akram Bin Sediq, Hatem Abou-Zeid. IEEE Transactions on Communications. (2021)
- Roghayeh Joda, Medhat Elsayed, Hatem Abou-Zeid, Ramy Atawia, Akram Bin Sediq, Gary Boudreau, Melike Erol-Kantarci. IEEE Networking Letters. (2021)
- Ahmad M Nagib, Hatem Abou-Zeid, Hossam S Hassanein, Akram Bin Sediq, Gary Boudreau. IEEE ICC, 2021. (2021)
If you are interested in working with me, please send me an email with the subject "Research Supervision" and the following information:
- A short statement indicating which of my research areas/projects you are interested in.
- Your most relevant experiences in either wireless networks, machine learning or VR/AR/Drones/IoT/prototyping.
- Your CV.
- Whether you have/plan to apply for funding.
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