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).
et al., Real-time Statistical Modelling of Data Generated from Self-Sensing Bridges, Proceedings of the Institution of Civil Engineers - Civil Engineering, ISSN:0965-089X
et al., 2018, The role of statistics in data-centric engineering, Statistics & Probability Letters, Vol:136, ISSN:0167-7152, Pages:58-62
Noble J, Adams NM, 2018, Real-Time Dynamic Network Anomaly Detection, Ieee Intelligent Systems, Vol:33, ISSN:1541-1672, Pages:5-18
Evans LPG, adams N, anagnostopoulos C, When Does Active Learning Work?, Advances in Intelligent Data Analysis XII, ISSN:0302-9743
Riddle-Workman E, Evangelou M, Adams N, Adaptive Anomaly Detection on Network Data Streams, IEEE Conference on Intelligence and Security Informatics