Prof Mahesan Niranjan
PhD
Professor of Electronics and Computer Science
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Mahesan Niranjan received his BSc from the University of Peradeniya, Sri Lanka (1982), MEE from Eindhoven, The Netherlands (1985) and PhD from Cambridge, UK (1990). He joined the University of Southampton in 2008. Prior to that he had been professor of Computer Science at the University of Sheffield, and Lecturer in Information Engineering at the University of Cambridge.
He has over 35 years of research and teaching experience in machine learning, the subject of extracting useful information from large and complex datasets, a subject in which he has worked both on the theoretical/ algorithmic and applied aspects. His current research focuses on biomedical applications of machine learning.
Landmark publications:
SVB Aiyer, M Niranjan & F Fallside (1990) A theoretical investigation into the performance of the Hopfield model, IEEE Transactions on Neural Networks 1(2), 204-215.
V Kadirkamanathan & M Niranjan (1993) A function estimation approach to sequential learning with neural networks, Neural Computation 5(6), 954-975.
Y Gunawardana & M Niranjan (2013) Bridging the gap between transcriptome and proteome measurements identifies post-translationally regulated genes, Bioinformatics 29 (23), 3060-3066.
ES Marquez, JS Hare & M Niranjan (2018) Deep cascade learning, IEEE Transactions on Neural Networks and Learning Systems 29(11), 5475-5485.
A Heinson, Y Gunawardana, B Moesker, CC Hume, E Vataga, Y Hall, E Stylianou, H McShane, A Williams, M Niranjan & CH Woelk (2017) Enhancing the Biological Relevance of Machine Learning Classifiers for Reverse Vaccinology, International Journal of Molecular Sciences 18(2), 312.
RT Martinez-Nunez, H Rupani, M Plat´e, M Niranjan, RC Chambers, PH Howarth & T Sanchez-Elsner (2018) Genome-Wide Posttranscriptional Dysregulation by MicroRNAs in Human Asthma as Revealed by Frac-seq, The Journal of Immunology: ji1701798.
Major grants:
2019-2023 EPSRC; Early detection of contact distress for enhanced performance monitoring and predictive inspection of machines; £1.1M.
2019-2021 Innovate UK; Knowledge Transfer Partnership project (KTP) with The ai Corporation on fraud detection; 150K.
2018-2022 EPSRC; Network of Excellence in Artificial and Augmented Intelligence for Automated Scientific Discovery; £1.0M.