- Optimising Electrical Power Supply Sustainability Using a Grid-Connected Hybrid Renewable Energy System—An NHS Hospital Case Study 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), 7084. ISSN 1996-1073
- 6G Opportunities Arising from Internet of Things Use Cases: A Review Paper 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), 159. ISSN 1999-5903
- Modelling IoT devices communication employing representative operation modes to reveal traffic generation characteristics Barakat, Basel; Keates, Simeon; Wassell, Ian J. and Arshad, Kamran. 2021. 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
- Is the Zero-Wait Policy Always Optimum for Information Freshness (Peak Age) or Throughput? 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
Basel Barakat
Dr. Basel is specialised in Artificial Intelligence, Machine Learning, Internet of Things, and Wireless Communication
Staff details
Dr. Basel Barakat
Lecturer at Goldsmiths, University of London | PhD, MSc, BSc, FHEA
Dr. Basel is a researcher in Artificial Intelligence (AI), Machine Learning, IoT (Internet of Things), and real-time systems, dedicated to solving global challenges in healthcare, renewable energy. His work includes AI-driven healthcare tools, renewable energy optimisation, and ethical Large Language Model (LLM) applications.
As an educator, Dr. Barakat leads modules in AI, data science, and IoT, supervises PhD and MSc students, and champions initiatives to inspire future STEM leaders. An active member of the academic community, he reviews for top journals and shapes institutional policies to foster research excellence.
Awarded the Royal Academy of Engineers’ Lord Sainsbury Award, he secures funding from the NHS (UK National Health Service), EU, and EPSRC for translational projects that bridge research and real-world applications.
Dr. Barakat’s mission: Technology that transforms lives.
Academic qualifications
- PhD Real-time Communication Systems from University of Greenwich in collaboration with the University of Cambridge 2019
- PgCert in Learning, Teaching & Assessment Practice in Higher Education from Edinburgh Napier University 2022
- MSc Wireless Mobile Communication Systems Engineering from University of Greenwich 2014
Research interests
Dr. Barakat's research interests:
- Artificial Intelligence and Machine Learning applications
- LLMs Applications
- Time-series Forecasting Algorithms
- Internet of Things (IoT) systems
- Real-time Communication Systems
- Mathematical Modelling
- Healthcare Technology Innovation
- Natural Language Processing
- Sustainable Energy Systems
Grants and awards
2024:
AI-powered Carbon Intensity Forecasting for Electric Vehicle Charging Optimisation
(PI) Northern Accelerator funded by the Department of Levelling Up and Communities’ UK Shared Prosperity Fund, supported by Sunderland City Council.
2024:
Machine learning for predicting the optimal prescription for renal patents
(CO-PI) Seed Funded by NHS innovate to improve the prescription for renal patents
2023:
Harnessing the power of machine learning for forecasting demand and performance of health care services.
(PI) Highly competitive Faculty of Technology fully funded PhD studentship. The work is in collaboration with the University of Kent, and Graham Care.
2023:
University of Sunderland Individual Research funding
The funding covers 10% of academic time over two years, a GPU card, and two international conference expenses.
2022:
Enhancing and developing the interactions of an Internet of Things system
(PI) European Regional Development Fund, European Union.
Publications and research outputs
Article
- Coupled thermo-electrical dispatch strategy with AI forecasting for optimal sizing of grid-connected hybrid renewable energy systems 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, 117460. ISSN 0196-8904
- 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 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), 134. ISSN 1999-5903
- Solar Irradiance Forecasting Using a Data-Driven Algorithm and Contextual Optimisation 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), 134. ISSN 2076-3417
Book Section
- Phonemes: An Explanatory Study Applied to Identify a Speaker Kinkiri, Saritha; Barakat, Basel and Keates, Simeon. 2020. Phonemes: An Explanatory Study Applied to Identify a Speaker. In: Arup Bhattacharjee; Samir Kr. Borgohain; Badal Soni; Gyanendra Verma and Xiao-Zhi Gao, eds. Machine Learning, Image Processing, Network Security and Data Sciences. Singapore: Springer, pp. 58-68. ISBN 9789811563171
Conference or Workshop Item
- 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 Ajayi, Bamidele; Barakat, Basel; McGarry, Ken 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: 29th International Conference on Automation and Computing (ICAC). Sunderland, United Kingdom 28 - 30 August 2024.
- Elevating Cybersecurity for Smart Grid Systems—A Container-Based Approach Enhanced by Machine Learning 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). Sunderland, United Kingdom 28 - 30 August 2024.
- Privacy-Enhanced One-to-Many Biometric System Using Smart Contracts: A New Framework 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). Sunderland, United Kingdom 28 - 30 August 2024.
Other
- Improving Reliability of Fine-tuning with Block-wise Optimisation Barakat, Basel and Huang, Qiang. 2023. Improving Reliability of Fine-tuning with Block-wise Optimisation. arXiv, New York.
Awards
Jul. 24 First Place in DataThon titled ‘Quantifying Heterogeneity and Variability in Human Daily Rhythms’ for Category 1: The Best Overall Model
Nov. 22 Elected as an Academic Board member representing the Faculty of Technology.
Jun. 23 & Jun. 22 Nominee in the category: The Most Inspirational Member of University Staff Outstanding Doctoral/PhD Supervisor for 2 consecutive years
Dec. 21 TOP10 2021 MDPI Future Internet High Cited Series paper for my work on 6G
Nov. 19 Royal Academy of Engineers: Lord Sainsbury Award “Champion of champions for engineers in business”
May. 19 Best teamwork from the University of Greenwich
Jan. 15 Best MSc Project from the University of Greenwich