Niall Adams is Professor of Statistics at Imperial College London. In addition to a variety of undergraduate and postgraduate teaching, he conducts research in classification, data mining, streaming data analysis and spatial statistics. Applications for this research are diverse, including bioinformatics, cyber-security and retail finance.
Dr Niall Adams' personal web page can be found at http://stats.ma.ic.ac.uk/~nadams
Other Significant Activities
Editorial panel for Applied Statistics, Journal of the Royal Statistical Society Series C (2008-2012)
Editorial panel for Statistical Analysis and Data Mining (2009-2014)
Ed: Big Data in Cyber-Security: Host-Based IP Flow Monitoring using Adaptive Estimation”, (invited keynote) SITA 13, 8th International Conference on Intelligent Systems: Theories and Applications, Rabat, Morocco, (2013)
“Efficient streaming classification methods”, (invited), German Classification Society, Karlshrue, Germany (2010).
“Temporally-adaptive linear classification for handling population drift in credit scoring”, (invited), COMPSTAT 2010, Paris, France (2010).
Lu X, Adams N, Kantas N, 2019, On adaptive estimation for dynamic Bernoulli bandits, Foundations of Data Science, Vol:1, ISSN:2639-8001, Pages:197-225
Bakoben M, Bellotti A, Adams N, Identification of credit risk based on cluster analysis of account behaviours, Journal of the Operational Research Society, ISSN:0160-5682
Lau D-H, Adams NM, The importance of analysing data from instrumented infrastructure, International Conference on Smart Infrastructure and Construction
et al., Unsupervised deep learning for instrumented infrastructure: a case study, International Conference on Smart Infrastructure and Construction
Ward S, Cohen E, Adams N, 2019, Fusing multimodal microscopy data for improved cell boundary estimation and fluorophore localization of Pseudomonas aeruginosa, Asilomar Conference on Signals, Systems and Computers, IEEE