Imperial College London

ProfessorNiallAdams

Faculty of Natural SciencesDepartment of Mathematics

Professor of Statistics
 
 
 
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Contact

 

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

 
 
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Location

 

544Huxley BuildingSouth Kensington Campus

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Summary

 

Summary

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)

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). 

Publications

Journals

Shlomovich L, Cohen E, Adams N, et al., 2022, Parameter estimation of binned Hawkes processes, Journal of Computational and Graphical Statistics, ISSN:1061-8600

Yahze L, Adams N, Bellotti A, 2022, A relabeling approach to handling the class imbalance problem for logistic regression, Journal of Computational and Graphical Statistics, Vol:31, ISSN:1061-8600, Pages:241-253

Holtegebaum H, Adams N, Lau D-H, 2021, Unsupervised streaming anomaly detection for instrumented infrastructure, Annals of Applied Statistics, Vol:15, ISSN:1932-6157, Pages:1101-1125

Adams N, Riddle-Workman E, Evangelou M, 2021, Multi-Type relational clustering for enterprise cyber-security networks, Pattern Recognition Letters, Vol:149, ISSN:0167-8655, Pages:172-178

Plasse J, Helfer Hoeltgebaum H, Adams N, 2021, Streaming changepoint detection for transition matrices, Data Mining and Knowledge Discovery, Vol:35, ISSN:1384-5810, Pages:1287-1316

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