Imperial College London


Faculty of Natural SciencesDepartment of Mathematics

Professor of Statistics



+44 (0)20 7594 8837n.adams Website




544Huxley BuildingSouth Kensington Campus





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




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)

Plenary Lectures

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

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