This era of Data and Internet of Things (IoT) is giving new impetus to the application of AI and Machine learning techniques in that with sufficient data, science can be carried out by directly analysing and learning from data and a lot of knowledge discovery can be driven by exploiting the availability of the massive amount of data.
Our Data Science and AI research investigates a wide-ranging developments and applications of Data Analytics and recent intelligent computing paradigms, such as nature, Big data and IoT inspired Intelligence and Computing. Our applications of Data Science and Machine learning include e-health and smart living, smart cities, video codecs and engineering and robotics.
- Data Science and Machine learning applications for weight management (Prof. Hissam Tawfik)
- Predictive Analytics for Adult Social Care. (Dr Anna Palczewska)
- Generalized TD-Replay with reinforcement learning algorithms (Dr Abdurrahman Altahhan)
- Empathic and Emphatic Interactive Companion (Dr Abdurrahman Altahhan)
- Software Engineering Framework for Cloud Computing (Dr Muthu Ramachandran)
- Interpreting Neural Network via Pedagogical Approach using Feature Contributions.(Dr Anna Palczewska)
- Software Engineering Analytics with Machine Learning (Dr Muthu Ramachandran)
- Image/video colour constancy adjustment techniques (Dr Akbar Sheikh Akbari)
- Application of HEVC for stereo/multi-view video coding. (Dr Akbar Sheikh Akbari)
- Application of ear and iris for biometric security (Dr Akbar Sheikh Akbari)
- Machine learning applications for the prediction of Obesity risk (Mr Bal Singh)
- Financial Time Series Prediction Using Spiking Neural Networks (Prof. Hissam Tawfik)
- A ‘General Aviation’ Flight Simulation Environment for the analysis of pilot performance under ‘startle’ conditions. (Prof. Hissam Tawfik)
Alani, M.M., Tawfik, H., Saeed, M. and Anya, O. (2018) Applications of Big Data Analytics Trends, Issues, and Challenges. Springer.
Palczewska, A., Kovarich, S., Ciacci, A., Fioravanzo, E., Basan, A. and Neagu, D. (2019) Ranking strategies to support toxicity prediction: a case study on potential LXR binders. Computational Toxicology., (in press).
Hussain, A.J., Liatsis, P., Khalaf, M., Tawfik, H. and Al-Asker, H. (2018) A Dynamic Neural Network Architecture with Immunology Inspired Optimization for Weather Data Forecasting. Big Data Research.
Ruiz-Garcia, A., Elshaw, M., Altahhan, A. and Palade, V. (2018) A hybrid deep learning neural approach for emotion recognition from facial expressions for socially assistive robots. Neural Computing and Applications, 29 (7) February, pp. 359-373.
Hussain, MA and Sheikh Akbari, A (2018) Color Constancy Adjustment using Sub-blocks of the Image. IEEE Access, 6. ISSN 2169-3536.
Hussain, MDA and Sheikh Akbari, A (2018) Color Constancy Algorithm for Mixed-illuminant Scene Images. IEEE Access. ISSN 2169-3536.
Tian D., Deng J., Vinod G., Santhosh T. V., Hissam, H. (2018) A Constraint-based Genetic Algorithm for Optimizing Neural Network Architectures for Detection of Loss of Coolant Accidents of Nuclear Power Plants, Neurocomputing, 322(17), Pages 102-119.
Mallik, B and Sheikh Akbari, A and Kor, A (2018) HEVC based Mixed-Resolution Stereo Video Codec. IEEE Access. ISSN 2169-3536.
Mallik, B and Sheikh Akbari, A and Kor, A (2018) Mixed-Resolution HEVC based multiview video codec for low bitrate transmission. Multimedia Tools and Applications. pp. 1-20. ISSN 1380-7501.
Baker, T., Aldawsari, B., Asim, M., Tawfik, H., Maamar, Z. and Buyya, R. (2018) Cloud-SEnergy: A bin-packing based multi-cloud service broker for energy efficient composition and execution of data-intensive applications. Sustainable Computing: Informatics and Systems.
Events and Activities
Special Journal Issues
- Journal of Reliable Intelligent Environments (Springer) - A special Issue on ‘Security, Usability and Sustainability of Smart Cities’
MDPI Sensors - A Special Issue on "Robotics, Sensors and Industry 4.0"
Special Conference Session
- "ARTIFICIAL INTELLIGENCE IN HEALTH AND MEDICINE: FROM THEORY TO APPLICATIONS"; International Joint Conference on Neural Networks 2019