Dr Mona Jaber
Lecturer in Internet of Things
Email: firstname.lastname@example.orgRoom Number: Engineering, Eng 212
Dr Mona Jaber is a Lecturer on the Internet of Things at Queen Mary University of London. She is a leading expert in mobile communication with a specialisation in radio and backhaul design of cellular networks; a topic in which she published multiple articles including the top 75 most cited paper in IEEE Access. Since joining QMUL in 2019, she started a new research group that examines the intersection between IoT and machine learning in the context of sustainable living. Three fast evolving research directions have emerged where the first investigates multi-modal data in the modelling of urban mobility, the second examines data privacy-preserving machine learning for smart energy and health, and the third elaborates the digital twin paradigm as a simulation platform for IoT-enabled sustainable living.
Before joining QMUL, she led the IoT Research Group, at Fujitsu Laboratories of Europe, from 2017 to 2019, where she researched IoT-driven solutions for the automotive industry. She earned Ph.D. in Electronic Engineering in 2017 (5GIC, University of Surrey, UK), Master’s in Electrical and Communications Engineering in 2014 (American University of Beirut, Lebanon) and B.E. in Computer and Communication Engineering in 1996 (American University of Beirut, Lebanon).
Microprocessor Systems Design (BUPT joint programme)
The course examines the structure, programming and applications of microprocessor and microcontroller devices. There will be practical design and development using microcontroller as part of the module.
Signals and Systems (BUPT joint programme)
Signals and Systems is an introduction to Signal Theory, a discipline that forms an integral part of many engineering systems, including Internet of Things systems. The concepts of continuous-time and discrete-time signals and systems will be introduced, both in the time and in the frequency domains. Fourier approaches will be presented to connect the time and frequency domains and sampling theory will be presented to connect continuous-time to discrete-time signals and systems. Analytical and computational tools will be discussed throughout the module.
I am broadly interested in machine learning applications for network data analytics with focus on network automation and IoT applications. In particular, my current research interests are shaped by the emerging intersection between smart city and transport applications leading to smart urban mobility. In this context, my research explores the role machine learning and IoT data to model the interaction between the urban planning, traffic control, and urban mobility.
Similarly, my continuing research on network data analytics investigates the application of machine learning techniques to manage the performance of wireless networks and enable an agile user-centric service-provisioning scheme, dubbed as network elasticity.
Salcedo, E., Jaber, M., & Requena Carrión, J. (2022). A Novel Road Maintenance Prioritisation System Based on Computer Vision and Crowdsourced Reporting. Journal of Sensor and Actuator Networks, 11(1). doi:10.3390/jsan11010015
Ozturk, M., Abubakar, A. I., Rais, R. N. B., Jaber, M., Hussain, S., & Imran, M. A. (2022). Context-Aware Wireless Connectivity and Processing Unit Optimization for IoT Networks. IEEE Internet of Things Journal. doi:10.1109/JIOT.2022.3152381
Rizwan, A., Jaber, M., Filali, F., Imran, A., & Abu-Dayya, A. (2021). A Zero-touch Network Service Management Approach using AI-enabled CDR Analysis. IEEE Access. doi:10.1109/ACCESS.2021.3129281
Alrubayyi, H., Goteng, G., Jaber, M., & Kelly, J. (2021). Challenges of malware detection in the IoT and a review of artificial immune system approaches. Journal of Sensor and Actuator Networks, 10(4). doi:10.3390/jsan10040061
Fathy, Y., Jaber, M., & Nadeem, Z. (2021). Digital twin-driven decision making and planning for energy consumption. Journal of Sensor and Actuator Networks, 10(2). doi:10.3390/JSAN10020037
Alrubayyi, H., Goteng, G., Jaber, M., & Kelly, J. (2021). A novel negative and positive selection algorithm to detect unknown malware in the IoT. In IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2021. doi:10.1109/INFOCOMWKSHPS51825.2021.9484483
Bassoy, S., Jaber, M., Onireti, O., & Imran, M. A. (2021). Radio &amp; Backhaul Load Aware Multi-Objective Clustering in Multi-cell MIMO Cooperative Networks. IEEE Transactions on Vehicular Technology. doi:10.1109/TVT.2021.3070992
Fathy, Y., Jaber, M., & Brintrup, A. (2020). Learning with Imbalanced Data in Smart Manufacturing: A Comparative Analysis. IEEE Access, 2734-2757. doi:10.1109/ACCESS.2020.3047838
Jaber, M., & Alam, A. S. (2020). A reinforcement learning approach for wireless backhaul spectrum sharing in IoE HetNets. In IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC Vol. 2020-August. doi:10.1109/PIMRC48278.2020.9217340
Nadas, J., Jaber, M., Van Berghe, S. D., & Imran, M. A. (2020). Towards Continuous Subject Identification Using Wearable Devices and Deep CNNs. In IEEE International Conference on Communications Vol. 2020-June. Virtual conference. doi:10.1109/ICC40277.2020.9149260
- Chia-Yen Chang, "Mobility monitoring system in a smart city", Started Jan 2021
- Zunaira Nadeem, "Energy theft detection", Started Jan 2021
- Moudy Alshareef, "Privacy in IoT-driven e-health", Started Apr 2021
- Yuqin Liu, "Machine learning for next generation multiple access", Started Sep 2021
- Ammar Naich, "Robust Multi-Object Tracking (MOT) in scattered medium for autonomous vehicles", Started Jun 2019
- Hadeel Arubayyi, "Artificial Immune System Advances for Detecting Unknown Malware Detection in the IoT" Started Jan 2019
- Kishan Sthankiya, "Energy efficiency in the Open RAN", Started Sep 2021
Senior IEEE Member