|Position||Reader in Statistics|
|Themes||Computational Statistics, Stochastic Modelling of Complex Systems|
Since 2015: Reader (Associate Professor) in Statistics, Department of Statistical Science, UCL.
Since 2017: Research Fellow of the Alan Turing Institute for Data Science.
2020 (1st half): Visiting Associate Professor, Yale-NUS College, Singapore.
2014-2015: Visiting Researcher, Engineering Department, Signal Processing & Communications Laboratory, University of Cambridge.
2013-2014: Associate Professor, Department of Statistics & Applied Probability, National University of Singapore, Singapore.
2012-2013: Senior Lecturer in Statistics, Department of Statistical Science, UCL.
2008-2012: Lecturer in Statistics, Department of Statistical Science, UCL.
2005-2008: Post-Doc, Mathematics Institute and Department of Statistics, University of Warwick.
2002-2005: PhD, Lancaster University, supervisor Professor Gareth Roberts.
Bayesian Statistics, Computational Statistics, Machine Learning, Stochastic Volatility, Financial Statistics, Inverse Problems, Filtering, Econometrics, Biostatistics, Graphical Models, Models in Epigenetics, Population Models.
- Efficient Sequential Monte Carlo Algorithms for Integrated Population Models, with Axel Finke, Ruth King, Petros Dellaportas. Journal of Agricultural, Biological, and Environmental Statistics, 24(2019), 204-224.
- Optimization Based Methods for Partially Observed Chaotic Systems, with Daniel Paulin, Ajay Jasra, Dan Crisan. Journal of Foundations of Computational Mathematics, 19(2019), 485-559.
- Particle Filtering for Stochastic Navier-Stokes Signal Observed with Linear Additive Noise, with Francesc Llopis, Nikolas Kantas, Ajay Jasra, SIAM Journal of Scientific Computing, 40(2018), A1544-A1565.
- Bridging Tree for Posterior Inference on Ancestral Recombination Graphs, with Kari Heine, Ajay Jasra, David Balding, Maria De Iorio. Proceedings of Royal Society A, 474(2018), 20180568.
- Multilevel Sequential Monte Carlo with Dimension-Independent Likelihood-Informed Proposals, with Ajay Jasra, Kody Law, Youssef Marzouk, Yan Zhou. SIAM/ASA Journal of Uncertainty Quantification, 6(2018), 762-786.
- Asymptotic Analysis of the Random-Walk Metropolis Algorithm on Ridged Densities, with Gareth Roberts, Alex Thiery, Natesh Pillai. The Annals of Applied Probability, 28(2018), 2966-3001.
- On Concentration Properties of Partially Observed Chaotic Systems, with Daniel Paulin, Ajay Jasra, Dan Crisan. Advances in Applied Probability, 50(2018), 440-479.
- A Stable Particle Filter for a Class of High-Dimensional State-Space Models, with Dan Crisan, Ajay Jasra, Kengo Kamatani, Yan Zhou. Advances in Applied Probability, 49(2017), 1-25.
- Geometric MCMC for Infinite-Dimensional Inverse Problems, with Mark Girolami, Shiwei Lan, Farell, Andrew Stuart. Journal of Computational Physics, 335(2017), 327-351.
- Multilevel Sequential Monte-Carlo Samplers, with Ajay Jasra, Kody Law, Raul Tempone, Yan Zhou. Stochastic Processes and their Applications, 127(2017), 1417-1440.
- Natural Hedge of a Gas-Fired Power Plant, with Xiaojia Guo, Afzal Siddiqui. Computational Management Science, 13(2016), 63-86.
- On the Convergence of Adaptive Sequential Monte Carlo Methods, with Ajay Jasra, Nikolas Kantas, Alex Thiery. The Annals of Applied Probability, 26(2016), 1111-1146.
- Bayesian Inference for Partially Observed Stochastic Differential Equations Driven by Fractional Brownian Motion, with Joseph Dureau, Konstantinos Kalogeropoulos. Biometrika, 102(2015), 809-827.
- Bayesian inference for Duplication-Mutation with Complementarity Network models, with Ajay Jasra, Adam Persing, Kari Heine, Maria De Iorio. Journal of Computational Biology, 22, 11(2015), 1025-1033.
- Sequential Monte-Carlo methods for high-dimensional Inverse Problems: a case study for the Navier-Stokes equations, with Nikolas Kantas, Ajay Jasra. SIAM/ASA Journal of Uncertainty Quantification, 2, 1(2014), 464-489
- On the stability of Sequential Monte-Carlo methods in high dimensions, with Dan Crisan, Ajay Jasra. The Annals of Applied Probability, 46, 4(2014), 1396-1445.
- Advanced MCMC methods for sampling on diffusion pathspace, with Kostas Kalogeropoulos, Erik Pazos. Stochastic Processes and their Applications, 123, 4(2013), 1415-1453.
- Optimal tuning of the Hybrid Monte-Carlo, with Natesh Pillai, Gareth Roberts, Jesus Maria Sanz-Serna, Andrew Stuart. Bernoulli, 19, 5A(2013), 1501-1534.
- \epsilon-strong simulation of the Brownian path, with Stefano Peluchetti, Gareth Roberts. Bernoulli, 18, 4(2012), 1223-1248.
- Hybrid Monte-Carlo on Hilbert spaces, with Frank Pinski, Jesus Maria Sanz-Serna, Andrew Stuart. Stochastic Processes and their Applications, 121, 10(2011), 2201-2230.
- Optimal scalings for local Metropolis-Hastings chains on nonproduct targets in high dimensions, with Gareth Roberts, Andrew Stuart. The Annals of Applied Probability, 19, 3(2009), 863-898.
- Monte-Carlo maximum likelihood estimation for discretely observed diffusion processes, with Omiros Papaspiliopoulos, Gareth Roberts. The Annals of Statistics, 37, 1(2009), 223-245.
- Retrospective exact simulation of diffusion sample paths with applications, with Omiros Papaspiliopoulos, Gareth Roberts. Bernoulli, 12, 6(2006), 1077-1098.
- Exact simulation of diffusions, with Gareth Roberts. The Annals of Applied Probability, 15, 4(2005), 2422-2444.
- Exact and computationally efficient likelihood-based estimation for discretely observed diffusion processes (with discussion), with Omiros Papaspiliopoulos, Gareth Roberts, Paul Fearnhead. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 68, 3(2006), 333-382.
* For an up-to-date complete list of publications, see my google scholar webpage: