My research interests are in Machine Learning, Natural Language Processing in the aspects of text and medical data analysis.
Daniel Onah is a Senior Teaching Associate for the Institute of Coding in the School of Computing and Communications at Lancaster University. He is co-affiliated with the Data Science, Software Engineering and NLP groups. Previously, he was a Postdoctoral Research Software Developer at UCL Institute of Neurology. At UCL, he developed a web-based Machine Learning Gene Prediction software application for predicting and analysing over 1126 mutated genes associated to 26 subtypes of Mendelian neurological diseases. The research review the likelihood that a gene when mutated will cause neurological phenotype. He completed a PhD at the University of Warwick, Department of Computer Science in 2017. His doctoral research was focused on technology enhance learning, where he developed and facilitated a standalone e-learning MOOC platform known as eLDaMOOC (currently being used as the outreach CPD programme for teachers of computer science in the UK by his former department at Warwick University). His current research interests are in NLP, Machine Learning, Deep Learning, Bioinformatics and Data Science. He develops text analysis and classification methods to solve problems in other scientific areas such as medical science and predictive analysis for scientific research.