Data Science is an interdisciplinary field that utilises computing technology to derive obvious and non-obvious relationships in data by developing the appropriate scientific algorithms and implementation of these methods to extract useful knowledge or insights from the data.
The focus of the Data Science Research Group at Kent is to apply the techniques such as signal processing, machine learning, security and statistics in an impactful manner to benefit the wider public.
Members are engaged in the following areas of research:
- Biomedical signal analysis for applications such as affective and brain-computer-interfacing, biometrics, cardiovascular diagnosis, mental disorders (minimally conscious, Parkinson etc) and virtual reality
- Financial econometrics and time-series modelling and forecasting such as the estimation of declining social discount rate for intergenerational cost-benefit analysis
- Speech and audio signal processing with embedded system designs for applications related to hearing and communications
- Computational intelligence techniques (like ant colony optimisation, evolutionary algorithms and artificial neural networks) for business-related problems such as weather derivative and algorithmic trading
- Supervised machine learning algorithms to analyse biological data such as the biology of ageing and pharmacokinetics
- Computational creativity, semantic web, and natural language processing for applications such as music informatics, digital humanities and knowledge modelling
- Memristor technology for data storage, cloud and green computing
- Parallel and stream data processing
- Cryptology, steganography and steganalysis
- Text mining and machine learning, intelligent information retrieval, web mining, reasoning under uncertainty.