Senior Lecturer of Computer Science (Data Science)
I am a Senior Lecturer in Data Science in the School of Computer Science. I am a member of the University Academic Board (the highest level academic authority). I am leading the University Research Excellence Framework for 11 unit of assessment. I am also a member of the EPSRC funding peer review college.
My research expertise lies in the field of AI, data science, time-series forecasting, wireless communication, the Internet of Things, mathematical modelling, and the application of machine learning solutions to real-world challenges in sustainability and healthcare.
I have been recognised through several prestigious awards, including the TOP10 2021 MDPI Future Internet High Cited Series paper for my work on 6G, the Champion of Champions Award from the Royal Academy of Engineering, and an award for the best MSc project.
I obtained my BSc, MSc, and PhD degrees from the University of Greenwich in 2013, 2014, and 2019, respectively. I completed a postgraduate certificate in Learning, Teaching, and Assessment Practice in Higher Education from Edinburgh Napier University in 2022, and consequently a Fellowship to the Higher Education Academy (FHEA).
Prior to joining University of Sunderland, I held a lecturer position in the School of Engineering and Built Environment at Edinburgh Napier University.
My earlier career experience includes working as a research assistant at the University of Greenwich, focusing on machine learning algorithms for non-destructive flaw detection in pipes. Notably, my doctoral studies involved a visiting scholar appointment at the University of Cambridge. Additionally, in 2014, I served as a Research Fellow at the University of Greenwich, collaborating with British Telecom (BT) on a project titled 'Towards 5G: Air Interface Techniques.'
Teaching and supervision
MSc modules:
- Data Science Fundamentals
- Technology Management for Organisations
BSc modules:
- Artificial Intelligence
- Internet of Things and Robotics
- Programming Virtual Networks
Research interests for potential research students
I am currently accepting self-funded PhD students to work on Machine Learning, Artificial Intelligent energy systems, wireless communication, 5/6 G wireless networks, Internet of Things.
Current PhD Students:
- Bamidele Ajayi, Project title: 'Preserving the integrity of binary programs Using Deep Neural Networks'.
- Marek Sviderski, Project title: 'Novel framework combining multiple models to detect Alzheimer’s Dementia using Deep Learning'.
Research
- Data science
- Real-time communication
- Information freshness
- Computer vision
- Forecasting algorithms
Publications
Article
Kahwash, F., Barakat, Basel and Maheri, A. (2023) Coupled thermo-electrical dispatch strategy with AI forecasting for optimal sizing of grid-connected hybrid renewable energy systems. Energy Conversion and Management, 293. p. 117460. ISSN 0196-8904
Taha, Ahmad, Barakat, Basel, Taha, Mohammad M. A., Shawky, Mahmoud A., Lai, Chun Sing, Hussain, Sajjad, Abideen, Muhammad Zainul and Abbasi, Qammer H. (2023) A Comparative Study of Single and Multi-Stage Forecasting Algorithms for the Prediction of Electricity Consumption Using a UK-National Health Service (NHS) Hospital Dataset. Future Internet, 15 (4). p. 134. ISSN 1999-5903
Bendiek, Paula, Taha, Ahmad, Abbasi, Qammer H. and Barakat, Basel (2021) Solar Irradiance Forecasting Using a Data-Driven Algorithm and Contextual Optimisation. Applied Sciences, 12 (1). p. 134. ISSN 2076-3417
Taha, Ahmad, Taha, Mohammad M.A. and Barakat, Basel (2021) AI-Based Fall Detection Using Contactless Sensing. 2021 IEEE Sensors. ISSN 2168-9229
Kahwash, Fadi, Barakat, Basel, Taha, Ahmad, Abbasi, Qammer H. and Imran, Muhammad Ali (2021) Optimising Electrical Power Supply Sustainability Using a Grid-Connected Hybrid Renewable Energy System—An NHS Hospital Case Study. Energies, 14 (21). p. 7084. ISSN 1996-1073
Barakat, Basel, Taha, Ahmad, Samson, Ryan, Steponenaite, Aiste, Ansari, Shuja, Langdon, Patrick M., Wassell, Ian J., Abbasi, Qammer H., Imran, Muhammad Ali and Keates, Simeon (2021) 6G Opportunities Arising from Internet of Things Use Cases: A Review Paper. Future Internet, 13 (6). p. 159. ISSN 1999-5903
KINKIRI, Saritha, BAKARAT, Basel and KEATES, Simeon (2020) Identification of a Speaker from Characteristics of a Voice. Sensors & Transducers, 244 (5). pp. 7-12. ISSN 2306-8515
Barakat, Basel, Keates, Simeon, Wassell, Ian J. and Arshad, Kamran (2019) Modelling IoT devices communication employing representative operation modes to reveal traffic generation characteristics. International Journal of Parallel, Emergent and Distributed Systems, 36 (2). pp. 117-129. ISSN 1744-5760
Barakat, Basel, Keates, Simeon, Wassell, Ian and Arshad, Kamran (2019) Is the Zero-Wait Policy Always Optimum for Information Freshness (Peak Age) or Throughput? IEEE Communications Letters, 23 (6). pp. 987-990. ISSN 1089-7798
Book Section
Sviderski, Marek, Barakat, Basel and Allen, Becky (2024) Acoustic Emotion Analysis for Novel Detection of Alzheimer’s Dementia. In: 2024 29th International Conference on Automation and Computing (ICAC). IEEE, pp. 1-6. ISBN 979-8-3503-6088-2
Hassan, Mohamed, Barakat, Basel, Ibrahim, Mona Mohamed, Kamel, Ahmed M. and Abukeshek, Mays (2024) Assessment of Inertial Measurement Units for Estimating Kinematic Data in Gait Analysis. In: 2024 29th International Conference on Automation and Computing (ICAC). IEEE, pp. 1-5. ISBN 979-8-3503-6088-2
Abukeshek, Mays, Barakat, Basel and Ajayi, Bamidele (2024) Elevating Cybersecurity for Smart Grid Systems—A Container-Based Approach Enhanced by Machine Learning. In: 2024 29th International Conference on Automation and Computing (ICAC). IEEE, pp. 1-6. ISBN 979-8-3503-6088-2
Ajayi, Bamidele, Barakat, Basel, McGarry, Kenneth and Abukeshek, Mays (2024) Exploring the Application of Transfer Learning in Malware Detection by Fine-tuning Pre-Trained Models on Binary Classification to New Datasets on Multi-class Classification. In: 2024 29th International Conference on Automation and Computing (ICAC). IEEE, pp. 1-6. ISBN 979-8-3503-6088-2
Sviderski, Marek, Barakat, Basel, Allen, Becky and MacFarlane, Kate (2024) Multi-Task Learning with Acoustic Features for Alzheimer’s Disease Detection. In: 2024 29th International Conference on Automation and Computing (ICAC). IEEE, pp. 1-6. ISBN 979-8-3503-6088-2
Wells, Alec, Dajnowski, Norbert, Usman, Aminu Bello, Murray, John and Barakat, Basel (2024) Privacy-Enhanced One-to-Many Biometric System Using Smart Contracts: A New Framework. In: 2024 29th International Conference on Automation and Computing (ICAC). IEEE, pp. 1-6. ISBN 979-8-3503-6088-2
Barakat, Basel and Huang, Qiang (2023) Enhancing Transfer Learning Reliability via Block-wise Fine-tuning. In: 22nd IEEE International Conference on Machine Learning and Applications ICMLA 2023. IEEE, pp. 414-421. ISBN 979-8-3503-4534-6
Barakat, Basel, Steponenaite, Aiste, Lall, Gurprit S., Arshad, Kamran, Wassell, Ian J. and Keates, Simeon (2020) Assistive Technology for the Visually Impaired: Optimizing Frame Rate (Freshness) to Improve the Performance of Real-Time Objects Detection Application. In: Universal Access in Human-Computer Interaction. Applications and Practice. Springer, pp. 479-492. ISBN 9783030491079
Kinkiri, Saritha, Barakat, Basel and Keates, Simeon (2020) Phonemes: An Explanatory Study Applied to Identify a Speaker. In: Machine Learning, Image Processing, Network Security and Data Sciences. Springer, pp. 58-68. ISBN 9789811563171
Barakat, Basel, Keates, Simeon, Wassell, Ian and Arshad, Kamran (2019) Adaptive Status Arrivals Policy (ASAP) Delivering Fresh Information (Minimise Peak Age) in Real World Scenarios. In: Universal Access in Human-Computer Interaction. Multimodality and Assistive Environments. Springer, pp. 419-430. ISBN 9783030235628
Conference or Workshop Item
Barakat, Basel and Huang, Qiang (2023) Improving Reliability of Fine-tuning with Block-wise Optimisation. In: 22nd International Conference on Machine Learning and Applications, 15-17 Dec 2023, Florida, USA. (In Press)
Steponenaite, Aiste and Barakat, Basel (2023) Plagiarism in AI empowered world. In: 25TH INTERNATIONAL CONFERENCE ON HUMAN-COMPUTER INTERACTION, 23-28 July, Copenhagen, Denmark. (Submitted)
Barakat, Basel, Hall, Lynne and Keates, Simeon (2022) Integrating Machine Learning with Augmented Reality for Accessible Assistive Technologies. In: Universal Access in Human-Computer Interaction. User and Context Diversity.
Barakat, Basel, Steponenaite, Aiste, Lall, Gurprit S., Arshad, Kamran, Wassell, Ian J. and Keates, Simeon (2020) Assistive Technology for the Visually Impaired: Optimizing Frame Rate (Freshness) to Improve the Performance of Real-Time Objects Detection Application. In: International Conference on Human-Computer Interaction, 19-24 Jul 2020, Copenhagen, Denmark.
Aramide, Samuel O., Barakat, Basel, Wang, Yi, Keates, Simeon and Arshad, Kamran (2019) Generalized proportional fair (GPF) scheduler for LTE-A. In: 2017 9th Computer Science and Electronic Engineering (CEEC).
Barakat, Basel, Yassine, Hachem, Keates, Simeon, Wassell, Ian and Arshad, Kamran (2019) How to Measure the Average and Peak Age of Information in Real Networks? In: European Wireless 2019; 25th European Wireless Conference.
Barakat, Basel, Keates, Simeon, Arshad, Kamran and Wassell, Ian J (2019) Deriving machine to machine (M2M) traffic model from communication model. In: 2018 Fifth International Symposium on Innovation in Information and Communication Technology (ISIICT).
Sharsheer, Mohammad, Barakat, Basel and Arshad, Kamran (2016) Coverage and capacity Self-Optimisation in LTE-Advanced using Active Antenna Systems. In: 2016 IEEE Wireless Communications and Networking Conference Workshops (WCNCW).
Barakat, Basel and Arshad, Kamran (2015) Energy efficient scheduling in LTE-advanced for Machine Type Communication. In: 2015 International Conference and Workshop on Computing and Communication (IEMCON).
Barakat, Basel and Arshad, Kamran (2015) An adaptive hybrid scheduling algorithm for LTE-Advanced. In: 2015 22nd International Conference on Telecommunications (ICT).
Barakat, Basel and Arshad, Kamran (2015) Energy efficient carrier aggregation for LTE-Advanced. In: 2015 IEEE 8th GCC Conference Exhibition.
- Machine learning
- Forecasting algorithms
- Internet of Things
- Information freshness