|Position||Reader in Statistics|
|Themes||Computational Statistics, Stochastic Modelling of Complex Systems|
Since 2017: Research Fellow, Alan Turing Institute.
2020-21: Visiting Associate Professor, Yale-NUS College, Singapore.
2007-08: Research Fellow, Centre for Research in Statistical Methodology (CRiSM), Department of Statistics, University of Warwick.
- Bayesian Statistics
- Computational Statistics
- Machine Learning
- Stochastic Volatility
- Financial Statistics
- Inverse Problems
- Graphical Models
- Population Models
Current & Past PhD Students
- Since 2020: Christopher Stanton, UCL; funded by EPSRC DTP, UCL Studentships Award.
- Since 2018: Warrick Poklewski-Koziell (Part-Time), UCL; funded by Centre for Doctoral Training in Financial Computing & Data Science.
- 2016-20: Shouto Yonekura, UCL & Alan Turing Institute; funded by Alan Turing Institute | Current position: Lecturer (with Tenure) in Statistics, Chiba University, Japan.
- Since 2015: Neil Foster (Part-Time), UCL; funded by UCL & Channel 4.
- 2012-16: Samuel Livingstone (Co-Supervisor), UCL; funded by Xerox | Current position: Lecturer in Statistics, Department of Statistical Science, UCL.
- 2009-14: Erik Pazos, UCL; funded by EPSRC DTP, UCL Studentships Award | Current position: Senior Consultant - Data Science, QuantumBlack, McKinsey & Company, London.
Current & Past Post-Doctoral Researchers
- Since 2020: Marcel Hirt (Co-Supervisor); funded by internal Departmental resources.
- 2016-17: Axel Finke, UCL; funded by Leverhulme Trust Prize | Current position: Lecturer in Statistics, Loughborough University.
- 2013-14: Alexandre Thiery, National University of Singapore; funded by internal Departmental resources | Current position: Assistant Professor (with Tenure) in Statistics, National University of Singapore.
- 2012-13: Nikolas Kantas, UCL; funded by EPSRC First Grant | Current position, Senior Lecturer in Statistics, Imperial College.
* For an up-to-date complete list of publications, see my Google Scholar webpage:
- Asymptotic Analysis of Model Selection Criteria for General Hidden Markov Models, with Yonekura, S., Singh, S., Stochastic Processes and their Applications, 2021.
- Monte Carlo Co-Ordinate Ascent Variational Inference, with Ye, L., De Iorio, M., Hao, J., Statistics and Computing, 2020.
- Efficient Sequential Monte Carlo Algorithms for Integrated Population Models, with Finke, A., King, R., Dellaportas, P., Journal of Agricultural, Biological, and Environmental Statistics, 2019.
- Optimization Based Methods for Partially Observed Chaotic Systems, with Paulin, D., Jasra, A., Crisan D., Journal of Foundations of Computational Mathematics, 2019.
- Particle Filtering for Stochastic Navier-Stokes Signal Observed with Linear Additive Noise, with Llopis, F., Kantas, N., Jasra, A., SIAM Journal of Scientific Computing, 2018.
- Bridging Tree for Posterior Inference on Ancestral Recombination Graphs, with Heine, K., Jasra, A., Balding, D., De Iorio, M., Proceedings of Royal Society A, 2018.
- Multilevel Sequential Monte Carlo with Dimension-Independent Likelihood-Informed Proposals, with Jasra, A., Law, K., Marzouk, Y., Zhou, Y., SIAM/ASA Journal of Uncertainty Quantification, 2018.
- Asymptotic Analysis of the Random-Walk Metropolis Algorithm on Ridged Densities, with Roberts, G., Thiery, A., Pillai, N., Annals of Applied Probability, 2018.
- On Concentration Properties of Partially Observed Chaotic Systems, with Paulin, D., Jasra, A., Crisan, D., Advances in Applied Probability, 2018.
- A Stable Particle Filter for a Class of High-Dimensional State-Space Models, with Crisan, D., Jasra, A., Kamatani, K., Zhou, Y., Advances in Applied Probability, 2017.
- Geometric MCMC for Infinite-Dimensional Inverse Problems, with Girolami, M., Lan, S., Farell, P., Stuart, A., Journal of Computational Physics, 2017.
- Multilevel Sequential Monte-Carlo Samplers, with Jasra, A., Law, K., Tempone, R., Zhou, Y., Stochastic Processes and their Applications, 2017.
- Natural Hedge of a Gas-Fired Power Plant, with Guo, X., Siddiqui, A., Computational Management Science, 2016.
- On the Convergence of Adaptive Sequential Monte Carlo Methods, with Jasra, A., Kantas, N., Thiery, A., Annals of Applied Probability, 2016.
- Bayesian Inference for Partially Observed Stochastic Differential Equations Driven by Fractional Brownian Motion, with Dureau, J., Kalogeropoulos, K., Biometrika, 2015.
- Bayesian inference for Duplication-Mutation with Complementarity Network Models, with Jasra, A., Persing, A., Heine, K., De Iorio, M., Journal of Computational Biology, 2015.
- Sequential Monte-Carlo Methods for Bayesian Elliptic Inverse Problems, with Jasra, A., Muzaffer, E., Stuart, A., Statistics and Computing, 2015.
- A Simulation Approach for Change-Points on Phylogenetic Trees, with Persing, A., Jasra, A., Beskos, A., De Iorio, M., Balding D., Journal of Computational Biology, 2015.
- A Stable Manifold MCMC Method for High Dimensions, Statistics and Probability Letters, 2014.
- Error Bounds and Normalising Constants for Sequential Monte Carlo Samplers in High Dimensions, with Crisan, D., Jasra, A., Whiteley N., Advances in Applied Probability, 2014.
- Sequential Monte-Carlo methods for High-Dimensional Inverse Problems: A Case Study for the Navier-Stokes Equations, with Kantas, N., Jasra, A., SIAM/ASA Journal of Uncertainty Quantification, 2014.
- On the Stability of Sequential Monte-Carlo Methods in High Dimensions, with Crisan, D., Jasra, A., Annals of Applied Probability, 2014.
- Markov Chain Monte Carlo for Exact Inference for Diffusions, witth Sermaidis G., Papaspiliopoulos, O., Roberts, G., Fearnhead, P., Scandinavian Journal of Statistics, 2013.
- Advanced MCMC Methods for Sampling on Diffusion Pathspace, with Kalogeropoulos, K., Pazos, E., Stochastic Processes and their Applications, 2013.
- Optimal Tuning of the Hybrid Monte-Carlo Algorithm, with Pillai, N., Roberts, G., Sanz-Serna, J.-M., Stuart, A., Bernoulli, 2013.
- \epsilon-Strong Simulation of the Brownian Path, with Peluchetti, S., Roberts, G., Bernoulli, 2012.
- Hybrid Monte-Carlo on Hilbert Spaces, with Pinski, F., Sanz-Serna, J.-M., Stuart, A., Stochastic Processes and their Applications, 2011.
- The Acceptance Probabiity of the HMC Method in High-Dimensional Problems, with Pillai, N., Roberts, G., Sanz-Serna, J.-M., Stuart, A., American Institute for Physics, Conference Proceedings, 2010.
- Optimal Scalings for Local Metropolis-Hastings Chains on Nonproduct Targets in High Dimensions, with Roberts, G., Stuart, A., Annals of Applied Probability, 2009.
- Monte-Carlo Maximum Likelihood Estimation for Discretely Observed Diffusion Processes, with Papaspiliopoulos, O., Roberts, G., Annals of Statistics, 2009.
- MCMC Methods for Sampling Function Space, with Stuart, A., 6th International Congress on Industrial and Applied Mathematics, 2009.
- MCMC Methods for Diffusion Bridges, with Roberts, G., Stuart, A., Voss, J., Stochastics and Dynamics, 2008.
- A Factorization of Diffusion Measure and Finite Sample Path Constructions, with Papaspiliopoulos, O., Roberts, G., Methodology and Computing in Applied Probability, 2008.
- Computational Complexity of Metropolis-Hastings Methods in High Dimensions, with Stuart, A., 8th International Conference on Monte Carlo and Quasi-Monte Carlo Methods, 2008.
- Retrospective Exact Simulation of Diffusion Sample Paths with Applications, with Papaspiliopoulos, O., Roberts, G., Bernoulli, 2006.
- Exact and Computationally Efficient Likelihood-Based Estimation for Discretely Observed Diffusion Processes (with Discussion), with Papaspiliopoulos, O., Roberts, G., Fearnhead, P., Journal of the Royal Statistical Society: Series B (Statistical Methodology), 2006.
- One-Shot CFTP; Application to a Class of Truncated Gaussian Densities, with Roberts, G., Methodology and Computing in Applied Probability, 2005.
- Exact Simulation of Diffusions, with Roberts, G., Annals of Applied Probability, 2005.
- A 4D-Var Method with Flow Dependent Background Covariances for the Shallow-Water Equations, with Paulin, D., Jasra, A., Crisan, D., 2021.
- Manifold MCMC Methods for Bayesian Inference in a Wide Class of Diffusion Models, with Graham, M., Thiery, A., 2021.
- MCMC Algorithms for Posteriors on Matrix Spaces, with Kamatani, K., 2021.
- Online Smoothing for Diffusion Processes Observed with Noise, with Yonekura, S., 2021.
- Score-Based Parameter Estimation for a Class of Continuous-Time State Space Models, with Crisan, D., Jasra, A., Kantas, N., Ruzaycat, H., 2021.
Grants & Awards
Co-Investigator | Alan Turing Institute Grant, PI: Prof Serge Guillas, UCL, 2019-21 | Title: Real-Time Advanced Data assimilation for Digital Simulation of Numerical Twins on HPC (RADDISH) | Value, £225,000.
Principal Investigator | Leverhulme Trust Prize, 5 years, 1 Post-Doc, 2015-20 | 1 of 5 prizes awarded in Mathematics & Statistics from the Leverhulme Trust in 2014 | Value, £100,000.
Co-Investigator | EPSRC Standard Grant, 5 years, PI: Prof Maria De Iorio, UCL,1 Post-Doc, 2013-18 | EP/K01501X/1: Advanced Stochastic Computation for Inference from Tree, Graph & Network Models | EPSRC Contribution, £408,546.
Principal Investigator | EPSRC First Grant, 1 year, 1 Post-Doc, 2012-13 | EP/J01365X/1: Sequential Monte Carlo Methods for Applications in High Dimensions | EPSRC Contribution, £98,868.