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.

Since 2017: 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 
• Machine Learning 
• Stochastic Volatility 
• Financial Statistics
• Inverse Problems
• Filtering
• Econometrics
• Biostatistics
• Graphical Models
• 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, 2022.
• 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., 2022.
   

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.