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).
Bodenham DA, Adams NM, 2017, Continuous monitoring for changepoints in data streams using adaptive estimation, Statistics and Computing, Vol:27, ISSN:0960-3174, Pages:1257-1270
Bakoben M, Bellotti A, Adams N, 2016, Improving clustering performance by incorporating uncertainty, Pattern Recognition Letters, Vol:77, ISSN:0167-8655, Pages:28-34
Bodenham DA, Adams NM, 2016, A comparison of efficient approximations for a weighted sum of chi-squared random variables, Statistics and Computing, Vol:26, ISSN:0960-3174, Pages:917-928
Evans LPG, adams N, anagnostopoulos C, When Does Active Learning Work?, Advances in Intelligent Data Analysis XII, ISSN:0302-9743
Evangelou M, Adams NM, 2016, Predictability of NetFlow data, 14th IEEE International Conference on Intelligence and Security Informatics - Cybersecurity and Big Data (IEEE ISI), IEEE, Pages:67-72