|Machine learning, big data analytics, data stream processing, imbalanced learning problems, applications of machine learning & A.I., time domain data processing.||Dr. Robert Lyon
Department of Computer Science
Edge Hill University
Phone: 01695 656478
Email: Robert Lyon
Rob is a Lecturer in the Department of Computer Science at Edge Hill University. His research interests include the development of new machine learning algorithms for imbalanced learning problems, real-time data processing, image analysis, robotics, and the ethics of A.I.
Rob holds a PhD in machine learning gained during his time at The University of Manchester. He also holds a Masters degree in Advanced Computer Science, and an undergraduate degree in Software Development, both from the University of Liverpool. The latter was put to good use during the time Rob spent as a Software Engineer in industry. Prior to joining Edge Hill University, he spent four years as a Research Associate at the University of Manchester. Here he helped design the analytic pipeline for the world’s largest and most advanced radio telescope, the Square Kilometre Array.
See also: www.scienceguyrob.com
External Academic Activities
- Reviewer for the Genetic and Evolutionary Computation Conference (GECCO), Evolutionary Machine Learning track.
- Regular reviewer for the Monthly Notices of the Royal Astronomical Society.
- Principal investigator for the STFC funded Radiotherapy Machine Learning Network Project: http://radiotherapymlnetwork.co.uk/.
- Award Amazon AstroCompute Grant
- Currently supervising PhD student Zafiirah Hosenie, a recipient of a DARA Big Data studentship.
- Z. Hosenie, R. J. Lyon, B. W. Stappers, A. Mootoovaloo, “Comparing Multiclass, Binary, and Hierarchical Machine Learning Classification schemes for variable stars”, Monthly Notices of the Royal Astronomical Society (MNRAS), Volume 488 (4):4858–4872, 2019. DOI: 10.1093/mnras/stz1999.
- R. J. Lyon, B. W. Stappers, L. Levin, M. B. Mickaliger, A. Scaife, “A Big Data Pipeline for High Volume Scientific Data Streams”, Astronomy & Computing, Volume 28, 2019. DOI: 10.1016/j.ascom.2019.100291.
- R. J. Lyon, “Imbalanced Learning In Astronomy”, European Week of Astronomy and Space Science (EWASS), April 4-6, 2018.
- D. Michilli, J. W. T. Hessels, R. J. Lyon, C. M. Tan, C. Bassa, S. Cooper, V. I. Kondratiev, S. Sanidas, B. W. Stappers, J. van Leeuwen, “Single-pulse classifier for the LOFAR Tied-Array All-sky Survey”, Monthly Notices of the Royal Astronomical Society (MNRAS), Volume 480 (3): 3457-3467, 2018. DOI: doi.org/10.1093/mnras/sty2072.
- C. M. Tan, R. J. Lyon, B. W. Stappers, S. Cooper, J. W. T. Hessels, V. I. Kondratiev, D. Michilli, S. Sanidas, “Ensemble candidate classification for the LOTAAS pulsar survey”, Monthly Notices of the Royal Astronomical Society (MNRAS), Volume 474 (4): 4571–4583, 2017. DOI:10.1093/mnras/stx3047.
- L. Levin, W. Armour, C. Baffa, E. Barr, S. Cooper, R. Eatough, A. Ensor, E. Giani, A. Karastergiou, R. Karuppusamy, M. Keith, M. Kramer, R. Lyon, M. Mackintosh, M. Mickaliger, R van Nieuwpoort, M. Pearson, T. Prabu, J. Roy, O. Sinnen, L. Spitler, H. Spreeuw, B. W. Stappers, W. van Straten, C. Williams, H. Wang, K. Wiesner, “Pulsar Searches with the SKA”, International Astronomical Union Symposium (IAU) 337, Manchester, 4-8th September, 2017, Arxiv Pre-print.
- R. J. Lyon, B. W. Stappers, S. Cooper, J. M. Brooke, J. D. Knowles, “Fifty Years of Pulsar Candidate Selection: From simple filters to a new principled real-time classification approach”, Monthly Notices of the Royal Astronomical Society (MNRAS), 459 (1): 1104-1123, 2016. Arxiv Pre-print, MNRAS, DOI:10.1093/mnras/stw656.
- R. J. Lyon, “50 Years of Candidate Pulsar Selection – What next?”, International Astronomical Union Symposium (IAU) 337, Manchester, 4-8th September, 2017, Arxiv Pre-print. Note that the supporting material can be found here, and the talk slides are here. The supporting material also has a unique identifier, see DOI: 10.5281/zenodo.883844.
- R. J. Lyon, J. M. Brooke, J. D. Knowles, B. W. Stappers, “Hellinger Distance Trees for Imbalanced Streams”, in 22nd International Conference on Pattern Recognition, pp.1969-1974, 2014. Arxiv Pre-print, DOI: 10.1109/ICPR.2014.344.
- R. J. Lyon, J. M. Brooke, J. D. Knowles, B. W. Stappers, “A Study on Classification in Imbalanced and Partially-Labelled Data Streams”, in Simple and Effective Machine Learning for Big Data, Special Session, IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2013. Arxiv Pre-print, DOI: 10.1109/SMC.2013.260.
- R. J. Lyon, “Why Are Pulsars Hard To Find?”, PhD Thesis, School Of Computer Science, University of Manchester, 2016.
- Machine Learning & Science Data Processing @ SKA Delivering the Science, Cambridge, 12-13 April 2016
- 50 Years of Candidate Pulsar Selection – What next? @ International Astronomical Union Symposium (IAU) 337, Manchester, 4-8 September 2017
- Imbalanced Learning in Astronomy @ EWASS, 3-6 April 2018
- Astron Hackathon @ Astron, 23-24 April 2018
- Time-domain Machine Learning – Opportunities and Challenges for the SKA @ Third ASTERICS-OBELICS Workshop : New paths in data analysis and open data provision in Astronomy and Astroparticle Physics 23rd-26th October 2018, Cambridge, UK
- Time-domain Machine Learning – Opportunities and Challenges for the SKA @ AI at SKA and CERN, 17th-18th September 2018, Alan Turing Institute, London, UK
- Data processing with the SKA – Machine learning at scale @ University of Southampton Physics Seminar, 20th November 2018