My research interests focus on developing innovative neural network-based solutions to problem domains such as bioinformatics, text analytics/NLP, time-series processing of financial and sports markets, and learning design patterns. I am currently investigating time sensitive self-learning in multi-recurrent networks (MRNs) and complex feature selection and knowledge extraction methods from MRNs and deep feedforward nets for problem domains such health/bionformatics and financial/sports markets.

I have taught artificial intelligence and machine learning at a UK University for the last 17 years as well as leading the development of HPC infrastructure and a new MSc Data Analytics for Business course. I am heavily involved in data science consultancy.

I am a strong advocate of CRISP-DM, Agile/SCRUM and Marr's SMART Dashboard as methodologies for realising high quality business innovation from big data and machine learning technologies. My preferred languages/tools for professional data mining, are C++, Python (incl sci-kit learn, Pytorch) and Java-based machine learning tools such as Weka to manipulate, transform and model data and Tableau Desktop for data visualisation.