Steve Roberts

Professor of Engineering Science, Department of Engineering Science, University of Oxford

Steve Roberts is Professor of Information Engineering at the University of Oxford. He studied physics, completed a PhD in Signal Processing and was appointed to the faculty at Imperial College London, before taking up his post in Oxford in 1999.

He heads the Pattern Analysis and Machine Learning Research Group in the Department of Engineering Science at Oxford.

His main area of research lies in machine learning approaches to data analysis. He has particular interests in the development of machine learning theory for problems in time series analysis and decision theory.

Current research applies Bayesian statistics, graphical models and information theory to diverse problem domains including mathematical biology, finance and sensor fusion.

He has been awarded two medals by the IEE for papers on Bayesian signal analysis.

His current research focuses on statistical models for sequential change-point analysis, forecasting and decision making and decentralised multi-agent co-ordination.

Related Research: Data Analysis and Patterns in Data, Electronic Trading

Personal Website

Working Paper

Lee, S.M. and Roberts, S.J. (2009). Multivariate Time Series Forecasting in Incomplete Environments.

Published Research

Roberts, S., Yoon, J.W., Dyson, M. and Gan, J. (2011) Bayesian Inference for an adaptive Ordered Probit model: an application to Brain Computer Interfacing. Neural Networks, 24 (7), 726-734.

Roberts, S., Karastergiou, A., Johnston, S., Lee, H., Weltevrede, P. and Kramer, M. (2011) A transient component in the pulse profile of PSR J0738-4042. Monthly Notices of the Royal Astronomical Society, 415 (1), 251-256.

Roberts, S. and Ebden, M. (2011) Graph marginalization for rapid assignment in widearea surveillance. Ad Hoc Networks, 9 (2), 180-188.

Roberts, S., Psorakis I. and Ebden, M (2011). Roberts, S., Psorakis I. and Ebden, M (2011) Overlapping Community Detection using Bayesian Non-negative Matrix Factorization. Physical Review E, 83 (6).. Physical Review E.

Roberts, S. and Fox, C. (2011) A Tutorial on Variational Bayesian Inference. In: Robertson, D., Artificial Intelligence Review. Springer.

Roberts, S., Reece, S., Nicholson D. and Lloyd, C. (2011) Determining intent using hard/soft data and Gaussian process classifiers. 2011 Proceedings of the 14th International Conference on Information Fusion, 1-8.

Pickup, L., Capel, D., Roberts, S. and Zisserman A. (2011) Multiframe Super-Resolution from a Bayesian Perspective. In: Milanfar, P., Super-Resolution Imaging. CRC Press.

Roberts, S. and Reece, S. (2010). Roberts, S. and Reece, S. (2010) The Near Constant Acceleration Gaussian Process Kernel for Tracking. IEEE Signal Processing Letters, 17 (8), 707-710.. IEEE Signal Processing Letters.

Ebden, M., Stranjak, A. and Roberts, S. (2010) Visualizing Uncertainty in Reliability Functions with Application to Aero Engine Overhaul. Journal of the Royal Statistical Society C. 59 (1), 163-173.

Roberts, S., Garnett, R., Osborne, M.A., Reece, S. and Rogers, A. (2010). Roberts, S., Garnett, R., Osborne, M.A., Reece, S. and Rogers, A. (2010) Sequential Bayesian Prediction in the Presence of Changepoints and Faults. The Computer Journal. 53 (9), 1430-1446.. The Computer Journal.

Roberts, S. and Yoon, J. W. (2010). Roberts, S. and Yoon, J. W. (2010) Robust Measurement Validation in Target Tracking using Geometric Structure. IEEE Signal Processing Letters. 17 (5), 493-496.. IEEE Signal Processing Letters.

Roberts, S. and Lee, S. M. (2010). Roberts, S. and Lee, S. M. (2010) Sequential Dynamic Classification Using Latent Variable Models. The Computer Journal, 53 (9), 1415-1429.. The Computer Journal.

Roberts, S., Lowne, D. and Garnett, R. (2010) Sequential Non-stationary Dynamic Classification with Sparse Feedback. Pattern Recognition. 43 (3), 897-905.

Psorakis, I., Roberts S. and Sheldon B. (2010) Soft Partitioning in Networks via Bayesian Non-negative Matrix Factorization. Proceedings of NIPS 2010 workshop on community detection.

Reece, S., Mann, R., Rezek I. and Roberts S. (2010) Gaussian Process Segmentation of Co-Moving Animals. 30th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering.

Kaufman M. and Roberts S. (2010) Coordination vs. Information in Multi-agent Decision Processes. Proceedings of Autonomous Agents and Multiagent Systems.

Roberts, S. and Reece, S. (2010) An Introduction to Gaussian Processes for the Kalman Filter Expert. 2010 Proceedings of the 13th Conference on Information Fusion, 1-9.

Roberts, S., Garnett, R. and Osborne, M.A. (2010) Bayesian Optimization for Sensor Set Selection. Proceedings of IPSN 2010.

Ebden, M., Briers, M., and Roberts, S.J. (2008). Ebden, M., Briers, M., and Roberts, S.J. (2008) Decentralized Predictive Sensor Allocation. Proceedings of the 47th IEEE Conference on Decision and Control, 1702-1707.. Proceedings of the 47th IEEE Conference on Decision and Control, 1702-1707..

Ebden, M. and Roberts, S.J. (2011). Ebden, M. and Roberts, S.J. (2011) Graph Marginalization for Rapid Assignment in Wide-Area Surveillance. Advances in Ad Hoc Networks, 9 (2), 180-188.. Advances in Ad Hoc Networks, 9 (2), 180-188..

Fox, C., Rezek, I., and Roberts, S.J. (2008). Local quantum computing for fast probably MAP inference in graphical models. Proceedings of the Second AAAI Symposium on Quantum Interaction..

Lee, H.J. and Roberts, S.J. (2008). Lee, H.J. and Roberts, S.J. (2008) On-line Novelty Detection Using the Kalman Filter and Extreme Value Theory. Proceedings of the 19th International Conference on Pattern Recognition,1-4.. Proceedings of the 19th International Conference on Pattern Recognition,1-4..

Osborne, M., Roberts, S., Rogers, A., Ramchurn, S. and Jennings, N. (2008). Roberts, S. et al. (2008) Towards real-time information processing of sensor network data using computationally efficient multi-output Gaussian processes. Procs. of the 7th International Conference on Information Processing in Sensor Networks, 109-120.. In: International Conference on Information Processing in Sensor Networks (IPSN 2008), St. Louis, Missouri, USA. pp. 109-120.  .

Pickup, L., Capel, D., Roberts, S.J., and Zisserman, A. (2009). Pickup, L., Capel, D., Roberts, S.J., and Zisserman, A. (2009) Bayesian methods for image super-resolution. The Computer Journal, 52, 101-113.. The Computer Journal, 52, 101-113..

Reece, S., and Roberts, S. (2010). Reece, S., and Roberts, S. (2010) Generalised covariance union: a unified approach to hypothesis merging in tracking. IEEE Transactions on Aerospace and Electronic Systems, 46 (1), 207-221.. IEEE Transactions on Aerospace and Electronic Systems, 46 (1), 207-221..

Reece, S., Roberts, S., Claxton, C. and Nicholson, D. (2009). Reece, S., Roberts, S., Claxton, C. and Nicholson, D. (2009) Multi-Sensor Fault Recovery in the Presence of Known and Unknown Fault Types. 12th International Conference on Information Fusion, 1695-1703.. 12th International Conference on Information Fusion, 1695-1703..

Rezek, I., Leslie, D., Reece, S., Roberts, S., Rogers, A. Dash, R. and Jennings, N. (2008). Rezek, I., Leslie, D., Reece, S., Roberts, S., Rogers, A., Dash, R. and Jennings, N. (2008) On Similarities between Inference in Game Theory and Machine Learning. Journal of Artificial Intelligence Research, 33, 259-283.. Journal of Artificial Intelligence Research, 33, 259-283. .

Shah, N. and Roberts, S.J. (2008). Shah, N. and Roberts, S.J. (2008) Hidden Markov Independent Component Analysis as a Measure of Coupling in Multivariate Financial Time Series. ICA Research Network International Workshop Proceedings.. ICA Research Network International Workshop Proceedings..

Yoon, J.W., Roberts, S., Dyson, M. and Gan, J. (2008). Sequential Bayesian Estimation for Adaptive Classification. IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems proceedings..