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Computer science research

Intelligent computing research cluster

Our research cluster studies intelligent computing from various viewpoints.

Artificial intelligence

Cluster lead


Professor Grigorios Antoniou staff profile image

Professor Grigorios Antoniou

Professor / School of Built Environment, Engineering and Computing

Professor Grigoris Antoniou is a professor in computer science working on explainable and responsible artificial intelligence and its applications in domains such as health. He is Fellow of IEEE and the European Association for AI and member of the European Academy of Sciences and Arts. 

Email Professor Grigorios Antoniou

Knowledge Transfer Partnership (KTP) Leeds Beckett University and Riverside Greetings

  • The Computer Vision and Robotics research group completed a KTP project with Riverside Greetings Ltd. on asset management using RFIDs. This project has been rated Outstanding by Innovate UK. Riverside Greetings, a Wakefield-based SME with 23 employees, has benefited from a collaboration with LBS/BEEC (Nick Halafihi, Esther Pugh, and Akbar Sheikh-Akbari) to develop RFID technology for tracking sales of greeting cards and improving sales pipeline and operations. Check out the case study here.
  • We are excited to see our paper published: Mehta, R., Sheikh-Akbari, A., and Singh, K. K. (2024). Ensemble-based hybrid transfer approach for an effective 2D ear recognition system. IEEE Access, doi: 10.1109/ACCESS.2024.3485514.
  • We are happy to have entered a collaboration with South-West Yorkshire NHS Foundation Trust on using AI for the diagnosis of ADHD and autism
  • Grigoris Antoniou delivered a keynote speech on AI diagnostics for mental health conditions
  • We are excited to see our paper published: Fakieh, B., & Saleem, F. (2024). COVID-19 from symptoms to prediction: A statistical and machine learning approach. Computers in Biology and Medicine, 182, 109211.

Contact us

If you want to reach out, please contact the cluster lead Grigoris Antoniou.

Intelligent and Control Systems research group

The research interests of the Intelligent and Control Systems research group lie in applying are big data, artificial intelligence, Natural Language processing, digital twin technologies and control engineering to address complex real-world challenges. We are also interested in how the integration of AI, big data and control system can predict system performance and failures before they occur, optimize control strategies, and improve operational efficiency. We aim to develop intelligent algorithms that can make better prediction, and better performance and reliability improvement of systems.

Researchers

PhD students

  • Layan Sawalha
  • Anh Pham Tuan
  • Lewis Shaw
  • Amine Naimi
  • BIM-enabled Generative AI Platform for Productivity and Accuracy Enhancement of Construction Cost Planning (BIM-GAIcost). Funder: Innovate UK (UKRI), 2024-2025.
  • Generative AI-enabled Interim Valuations and Payments through mixed-reality data capture for Quantity Surveying Services (QS-GAI). Funder: Innovate UK (UKRI), 2024-2025.
  • Generative AI Prototype Platform for Diffusing Circular Construction Procurement Practices for SMEs in the UK and Turkey through Stakeholder Co-creation approach (GAI-COP). Funder: British Council-International Science Partnership Fund, 2024-2026.
  • Research Network Initiative for AI-Driven Building Information Modelling Integration for Circularity in Construction between the UK and Turkey (CIREN-AI). Funder: British Council, 2023-2025.
  • Feasibility of BIM-enabled Generative AI platform for Data-Driven Incremental Productivity Enhancement of Construction Cost Management (BIM-GAI). Funder Innovate UK (Application number: 10079600).
  • Leading three linked projects (EP/M018717/1, EP/M018709/1, EP/M018415/1), Smart on-line monitoring for nuclear power plants (SMART), EPSRC, 2015-2018. This project used data science and artificial intelligence to generate monitoring tools for nuclear power plants.
  • Fault tolerant control for increased safety and security of nuclear power plants, EPSRC, 2018-2023. This project has been using data science, artificial intelligence, and control theory to design an integrated module for increased safety and security of nuclear power plants.
  • Smart Meter Research Portal, EPSRC, 2017-2023.

Computer Vision and Robotics research group

The Computer Vision and Robotics research group provides a platform for the development of tools, techniques and systems used for the acquisition, analysis, and extraction of information from images, videos and sensor data. Research themes include: hyperspectral image processing; thermal imaging and its applications in home security; asset management using RFID tags; assisted living technologies and monitoring people at their home; computer control applications in agricultural technology; biometric identification techniques (ear, face, and iris); drone detection and recognition techniques; Image/video camera source identification; colour constancy adjustment methods; standard and non-standard image/video codecs, e.g., H.264 and HEVC; image resolution enhancement (super-resolution); medical image processing; autonomous systems and reinforcement learning; automation of engineering design processes; robotics and automation; and smart solutions in healthcare.

Researchers

PhD students

  • Chijioke Nwokeji
  • Henry Nnamdi Ndu
  • Hrishi Rakshit
  • Augusta Nneka Ndu
  • Kazi Nabiul Alam
  • Abu Md Obaidullah
  • Fathers Farm Foods Ltd: Developing novel hyper-spectral imaging capability to screen for aflatoxins in pistachios. Innovate UK KTP.
  • Riverside Greetings Ltd: Asset management using RFIDs. Innovate UK mKTP.
  • Omega Security Systems Ltd: Research, develop and implement a scalable and modular system which monitors and analyses individual behavioural patterns and movements in a range of environments. Innovate UK KTP.
  • CITU: Machine Learning Approaches for the Analysis and Prediction of Risk of Excess Weight in Young People. Innovate UK KTP.
  • Aquatrust Water & Ventilation: Custom remote monitoring for legionella control over geographically dispersed sites. Innovate UK KTP.
  • Aber Instruments: Reduction in development risk and time-to-market for complex sensors used in the pharmaceutical and related industries. Innovate UK KTP.

AI and Data Science research group

In the AI and data science research group, we study a variety of AI methods and their application in key application domains. From a technical perspective, we study machine learning and deep learning methods, hybrid AI and neurosymbolic approaches, responsible AI, knowledge graphs and large language models. And we seek to apply these technologies in multidisciplinary research efforts addressing important societal issues, with an emphasis on: health and wellbeing; financial analysis and engineering; and crime analysis and prevention.

Researchers

  • Innovate UK KTP with Quality Bearings Online Ltd (QBOL): reduce the company’s carbon footprint.
  • South-West Yorkshire NHS Foundation Trust: AI-based for adult ADHD diagnostics, 2020-2025.

Sustainable IT research group

The Sustainable IT research group has an established research track record in IT energy measurement, audit, management and energy efficiency which forms the basis for the group’s IT sustainability-related research focus. It supports GESI’s Smarter2030 initiative and the UN’s Sustainable Development Goals to contribute to a sustainable future. It is closely aligned to the following UN 2030 SDGs: SDG7 (Affordable and Clean Energy: smart grid, smart microgrid, and smart renewable energy management systems); SDG 9 (Industry, Innovation and Infrastructure: smart technologies to support Industry 4.0); SDG11 (Sustainable Cities and Communities: smart sustainable cities and infrastructure); SDG12 Responsible Consumption and Production: smart technologies for resource optimization, energy efficiency, and waste reduction); and SDG13 (Climate Action: via Low Carbon Growth: smart technologies to reduce energy, as well as resource consumption and waste emissions).

Researchers