Dr. Hatem Abou-Zeid, PhD
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Assistant Professor
Schulich School of Engineering, Department of Electrical and Software Engineering
Media contacts
Joe McFarland
Media Relations and Communications Specialist
Cell: +1.403.671.2710
Email: Joe.Mcfarland@ucalgary.ca
Phone number
Office: 403.220.7151
Location
Office: ICT252
Background
Educational Background
PhD Electrical and Computer Engineering, Queens University, 2014
Biography
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 with a focus on developing intelligent methods to design and optimize future networks and enable low latency and immersive communication experiences.
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 - and 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 15 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, 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.
Research
Areas of Research
- 6G Architectures, Protocols, and Techniques that enable AI, Cross-layer & Semantics-based Communication
- Joint Sensing & Communications using 6G
- Radio Resource Management (RRM) for Low Latency Communications
- UAV, Non-Terrestrial Communications
- Traffic Modeling and Characterization of 6G Applications
- Predictive RRM & Cross-Layer Designs
- Testbed Prototyping & Development of Multi-Sensory Communications
- Interpretable, Scalable AI for Networks
- Robust Reinforcement Learning Algorithms
- Multi-Agent and Federated Learning
- Low-Overhead Online Learning, Meta-learning
Participation in university strategic initiatives
Courses
| Course number | Course title | Semester |
|---|---|---|
| ENSF 511 | Industrial Internet of Things Systems and Data Analytics | Winter 2022 |
Projects
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.
Publications
- Virtual Reality Gaming on the Cloud: A Reality Check. Sihao Zhao, Hatem Abou-zeid, Ramy Atawia, Yoga Suhas Kuruba Manjunath, Akram Bin Sediq, Xiao-Ping Zhang. IEEE GLOBECOM 2021. (2021)
- Transfer Learning-Based Accelerated Deep Reinforcement Learning for 5G RAN Slicing. Ahmad M Nagib, Hatem Abou-Zeid, Hossam S Hassanein. IEEE LCN 2021. (2021)
- Intelligent Radio Access Network Slicing for Service Provisioning in 6G: A Hierarchical Deep Reinforcement Learning Approach. Jie Mei, Xianbin Wang, Kan Zheng, Gary Boudreau, Akram Bin Sediq, Hatem Abou-Zeid. IEEE Transactions on Communications. (2021)
- Carrier Aggregation With Optimized UE Power Consumption in 5G. Roghayeh Joda, Medhat Elsayed, Hatem Abou-Zeid, Ramy Atawia, Akram Bin Sediq, Gary Boudreau, Melike Erol-Kantarci. IEEE Networking Letters. (2021)
- Deep Learning-Based Forecasting of Cellular Network Utilization at Millisecond Resolutions. Ahmad M Nagib, Hatem Abou-Zeid, Hossam S Hassanein, Akram Bin Sediq, Gary Boudreau. IEEE ICC, 2021. (2021)
More Information
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.