Jaroslav Fowkes is a researcher in the computational mathematics group at STFC Rutherford Appleton Laboratory. He did his DPhil at Oxford with Nick Gould and Chris Farmer on Bayesian Global Optimization, before moving on to postdocs in the Mathematics and Informatics Schools at Edinburgh and the Numerical Analysis Group at Oxford.
His principal research interests lie in developing numerical algorithms that bridge the gap between optimization and machine learning. He is currently researching novel algorithms for ptychographic phase retrieval and for nonlinear least-squares data fitting problems arising from the STFC facilities. He previously worked on approximation algorithms for statistical pattern mining and their applications to source code. His DPhil research investigated algorithms for Bayesian global optimization in order to tackle the optimal well placement problem in oil reservoirs.
Recent Publications:
Gaussian Processes for Unconstraining Demand. I. Price, J. Fowkes and D. Hopman. European Journal of Operational Research, vol. 275, no. 2, pp. 621–634, 2019.
A Subsequence Interleaving Model for Sequential Pattern Mining. J. Fowkes and C. Sutton. KDD 2016 (18% acceptance rate).
A Bayesian Network Model for Interesting Itemsets. J. Fowkes and C. Sutton. PKDD 2016 (28% acceptance rate).
Autofolding for Source Code Summarization. J. Fowkes, P. Chanthirasegaran, R. Ranca, M. Allamanis, M. Lapata and C. Sutton. IEEE Transactions on Software Engineering, vol. 43, no. 12, pp. 1095–1109, 2017.
Parameter-Free Probabilistic API Mining across GitHub. J. Fowkes and C. Sutton. FSE 2016 (27% acceptance rate).
TASSAL: Autofolding for Source Code Summarization. J. Fowkes, P. Chanthirasegaran, R. Ranca, M. Allamanis, M. Lapata and C. Sutton. ICSE 2016 Demo Track (32% acceptance rate).
Branching and Bounding Improvements for Global Optimization Algorithms with Lipschitz Continuity Properties. C. Cartis, J. M. Fowkes and N. I. M. Gould. Journal of Global Optimization, vol. 61, no. 3, pp. 429–457, 2015.
A Branch and Bound Algorithm for the Global Optimization of Hessian Lipschitz Continuous Functions. J. M. Fowkes, N. I. M. Gould and C. L. Farmer. Journal of Global Optimization, vol. 56, no. 4, pp. 1791–1815, 2013.
Bayesian Numerical Analysis: Global Optimization and Other Applications. J. M. Fowkes. DPhil Thesis, Mathematical Institute, University of Oxford, 2012.
Optimal Well Placement. C. L. Farmer, J. M. Fowkes and N. I. M. Gould. Proceedings of the 12th European Conference on the Mathematics of Oil Recovery, 6–9th September 2010.