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

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

Other

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