Website: 

www.timeseriesclassification.com

I joined CMP as a part time MRes student/part time teaching assistant in 1993 having finished my BSc in Mathematics and Statistics at the University of Hertfordshire. After completing my Masters by research in 1995 I began a PhD titled "Modelling the UK electricity market with autonomous adaptive agents". After a brief period as a research assistant on a data mining project sponsored by Master Foods and Centrica, in 2000 I completed my PhD and was appointed as a Lecturer in Statistics for Data Mining jointly in the schools of Computer Science and Mathematics. Statistics moved into CMP in 2003 and since then I have been a full member of the school. In 2007 I was promoted to senior lecturer and in 2018 I was made professor.

I have been involved in researching areas of optimization, machine learning, agent systems, statistics and data mining. Since 2005, my primary research area has been time series data mining and machine learning, with a specific focus on time series classification. I publish under the name Anthony Bagnall

I am a great believer in reproducable science and transparent evaluation of algorithms. Since 2019 I have been heavily involved with the open source machine learning toolkit sktime whose source code is on github

PhD Projects 

I would welcome applications from students who have secured their own funding and I am currently advertising a self funded studentship but I would welcome enquiries about working in any areas of time series data mining. If you would like to discuss research projects in more detail, please contact me directly ([email protected]). 

I am interested in the design and evaluation of algorithms for time series data mining and the development of novel time series application areas.

Selected Recent Publications:

HIVE-COTE 2.0: a new meta ensemble for time series classification
Matthew Middlehurst, James Large, Michael Flynn, Jason Lines, Aaron Bostrom & Anthony Bagnall, Machine Learning volume 110, pages 3211–3243 (2021)

The great multivariate time series classification bake off: a review and experimental evaluation of recent algorithmic advances
Alejandro Pasos Ruiz, Michael Flynn, James Large, Matthew Middlehurst & Anthony Bagnall, Data Mining and Knowledge Discovery volume 35, pages 401–449 (2021)

The UCR Time Series Archive
Hoang Anh Dau, Anthony Bagnall, Kaveh Kamgar, Chin-Chia Michael Yeh, Yan Zhu, Shaghayegh Gharghabi, Chotirat Ann Ratanamahatana and Eamonn Keogh,  IEEE/CAA J. Autom. Sinica, vol. 6, no. 6, pp. 1293-1305, Nov. 2019

The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances
Anthony Bagnall, Jason Lines, Aaron Bostrom, James Large & Eamonn Keogh, Data Mining and Knowledge Discovery volume 31, pages 606–660 (2017)

Course Director for Computing Science, Master of Computing Science and Computing Science with a year in industry

Tony currently teaches programming, data structures and algorithms and machine learning. Previously he has taught on numerous mathematics, statistics and computing courses.

Programming 1

Data Structures and Algorithms

Programming 2 

Machine Learning