Professor Alexandros Beskos

* @ucl.ac.uk

• Biographical Details

• Research Interests

• Current & Past PhD Students

• Current & Past Post-Doctoral Researchers

• Publications

• Submitted Manuscripts

• Grants & Awards

Biographical Details

Since 2022: Professor in Statistics, Department of Statistical Science, UCL.

2017-23: Research Fellow, Alan Turing Institute.

2015-22: Reader in Statistics, Department of Statistical Science, UCL.

2020-21: Visiting Associate Professor, Yale-NUS College, Singapore.

2014-15: Visiting Researcher, Engineering Department, Signal Processing & Communications Laboratory, University of Cambridge.

2013-14: Associate Professor, Department of Statistics & Applied Probability, National University of Singapore, Singapore.

2012-13: Senior Lecturer in Statistics, Department of Statistical Science, UCL.

2008-12: Lecturer in Statistics, Department of Statistical Science, UCL.

2007-08: Research Fellow, Centre for Research in Statistical Methodology (CRiSM), Department of Statistics, University of Warwick.

2005-08: Research Fellow, under EPSRC grant, Mathematics Institute, University of Warwick. 

2002-05: PhD in Statistics, supervisor Professor Gareth Roberts, Department of Mathematics and Statistics, Lancaster University.

Research Interests

• Bayesian Statistics
• Computational Statistics  
• Filtering
• Econometrics
• Biostatistics
• Graphical Models
• Financial Statistics
• Inverse Problems
• Epigenetics
• Population Models

Current & Past PhD Students

• Since 2021: Yuga Iguchi, UCL | Funded by the Heilbronn Institute. 
• 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 the 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: Associate Professor 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

• 2020-21: Marcel Hirt (Co-Supervisor) | Funded by internal Departmental resources | Current position: Postdoctoral Researcher, Nanyang Technological University, Singapore.
• 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: Associate Professor in Statistics, National University of Singapore.
• 2012-13: Nikolas Kantas, UCL | Funded by EPSRC First Grant | Current position: Senior Lecturer in Statistics, Imperial College.

Publications

* For an up-to-date complete list of publications, see my Google Scholar webpage:

https://scholar.google.co.uk/citations?user=EZGoin0AAAAJ&hl=en

• Bayesian Learning of Graph Substructures, with van den Boom, W., De Iorio, M., Bayesian Analysis, 2023.
• Unbiased Estimation Using a Class of Diffusion Processes, with Ruzayqat, H., Crisan, D., Jasra, A., Kantas, N., Journal of Computational Physics, 2022.
• A 4D-Var Method with Flow-Dependent Background Covariances for the Shallow-Water Equations, with Paulin, D., Jasra, A., Crisan, D., Statistics and Computing, 2022.
• The G-Wishart Weighted Proposal Algorithm: Efficient Posterior Computation for Gaussian Graphical Models, with van den Boom, W., De Iorio, M., Journal of Computational and Graphical Statistics, 2022.
• A Lagged Particle Filter for Stable Filtering of Certain High-Dimensional State-Space Models, with Ruzayqat, H., Er-Raiy, A., Crisan, D., Jasra, A., Kantas, N., SIAM/ASA Journal on Uncertainty Quantification, 2022.
• Unbiased Approximation of Posteriors via Coupled Particle Markov Chain Monte Carlo, with van den Boom, W., Jasra, A., De Iorio, M., Eriksson, J., Statistics and Computing, 2022
• Manifold Markov Chain Monte Carlo Methods for Bayesian Inference in Diffusion Models, with Graham, M., Thiery, A., Journal of the Royal Statistical Society, Series B, 2022.
• Online Smoothing for Diffusion Processes Observed with Noise, with Yonekura, S. Journal of Computational and Graphical Statistics, 2022.
• MCMC Algorithms for Posteriors on Matrix Spaces, with Kamatani, K., Journal of Computational and Graphical Statistics, 2022
• Score-Based Parameter Estimation for a Class of Continuous-Time State Space Models, with Crisan, D., Jasra, A., Kantas, N., Ruzayqat, H., SIAM Journal of Scientific Computing, 2021.
• 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 Trees 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.

Submitted Manuscripts

• Change Point Detection in Dynamic Gaussian Graphical Models: The Impact of COVID-19 Pandemic on the US Stock Market, with Franzolini, B.,  De Iorio, M., Koziell, W., Grzeszkiewicz, K., forthcoming at the Annals of Applied Statistics, 2023.
• Parameter Estimation with Increased Precision for Elliptic and Hypo-Elliptic Diffusions, with Iguchi, Y., Graham, M., under revision for Bernoulli, 2023.
• ParticleDA.jl v.1.0: A Real-Time Data Assimilation Software Platform, with Giles, D., Graham, M., Giordano, M., Koskela, T., Guillas, S., under revision for Geoscientific Model Development, 2023 
• Sequential Markov Chain Monte Carlo for Lagrangian Data Assimilation with Applications to Unknown Data Locations, with Ruzayqat, H., Crisan, D., Jasra, A., Kantas, N., submitted to the Quarterly Journal of the Royal Meteorological Society, 2023.
• Parameter Inference for Degenerate Diffusion Processes, with Iguchi, Y., Graham, M., submitted to the Stochastic Processes and their Applications, 2023.

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.