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Former Members of my Research Group

Postdoctoral Researchers

Postdoctoral Researchers

  Dates Project Currently
Francesca R. Crucinio 2021-2022 CoSinES CREST PostDoctoral Fellow at ENSAE Paris
Juan Kuntz 2020-2023 RSMC Senior Research Engineer at Polygeist
Alberto Sorrentino 2010-2012 NiMBLE Associate Professor at Università di Genova
Jure Vogrinc 2022-2023 RSMC AI Researcher at SymphonyAI Sensa-NetReveal
       

PhD Students

I've also enjoyed working with a number of other students here, including

Ryan Chan (now Research Software Engineering at the Alan Turing Institute)
Christopher Nam.

Javier Rubio (now Lecturer at University College London).

See the list of my former students at the Mathematics Genealogy Project.

PhD Students

  Year Thesis Currently
Letizia Angeli 2020 Interacting Particle Approximations of Feynman-Kac Measures for Continuous-Time Jump Processes Capital Analyst at Apollo
Susanna E. Brown 2021 Resampling and genealogies in sequential Monte Carlo algorithms Software Developer at Ghiston
Francesca R. Crucinio 2021 Some Interacting Particle Methods with Non-Standard Interactions

CREST PostDoctoral Fellow at ENSAE Paris

Axel Finke 2015 On Extended State Space Constructions for Monte Carlo Methods

Lecturer in The Department of Mathematics at Loughborough University

Pieralberto Guarniero 2017 The Iterated Auxiliary Particle Filter

Lecturer at Bocconi

James Hodgson 2022 Exact and unbiased simulation of rare events Scientist at Achilles Therapeutics
Thomas Honnor 2017 Some spatial statistical techniques with applications to cellular imaging Lecturer in The Department of Statistical Science at UCL
Murray Pollock 2013 Some Monte Carlo Methods for Jump Diffusions Director of Statistics in the Department of School of Mathematics, Statistics and Physics at Newcastle University
Lewis Rendell 2020 Sequential Monte Carlo variance estimation and global consensus Data Scientist at Google
Denish Thesingarajah 2021 Node-wise Pseudo-marginal Methods for Spatial Model Selection  
Matthew Thorpe 2015 Variational Methods for Geometric Statistical Inference Associate Professor at the University of Warwick
MÃ¥ns Unosson 2020 Spatio-temporal Inference for Circadian Gene Transcription in the Mammalian SCN Data Scientist at Visma Finance
Yan Zhou 2014 Bayesian Model Comparison via Sequential Monte Carlo Head of Data Platform at Cubist Systematic Strategies

DTC Miniprojects

Projects carried out in 10-12 weeks by students in the first year of various doctoral training centres.

Year Centre Student Project
2011/12 MASDOC Matthew Thorpe Multi Target Tracking as Applied to
Telecommunications
2012/13 Complexity Science Christopher Windsor Optimal Derivative Hedging: A Monte Carlo Approach
2014/15 OxWaSP Suchen Jin Neural Block Sampling
2015/16 OxWaSP Arne Gouwy Iterative twisted particle filters for optimal control
2015/16 OxWaSP Dominic Richards Constrained Monte Carlo
2015/16 MASC Emily Holt Predicting the End of a Reaction
2015/16 MASDOC Letizia Angeli Feynman-Kac Models for Large Deviation Conditioning Problem
2017/18 OxWaSP Susanna Brown Conditional SMC genealogies
2017/18 OxWaSP Francesca Crucinio Sequential Monte Carlo Methods for Fredholm Equations of the First Kind
2017/18 OxWaSP James Hodgson Estimating Small Probabilities
2018/19 MathSys Chatchuea Kimchaiwong Robust Multi-target Tracking
2021/22 Statistics CDT Rocco Caprio Convergence of MCMC-PF Algorithms
2021/22 Statistics CDT Jen Ning Lim Scaling Particle-based Expectation Maximization
2021/22 Statistics CDT Liwen Xue A Block-sampling Particle Filter via Iteration
2022/23 Statistics CDT Shu Huang Parameter Inference for SDEs with Non-globally Lipschitz Drift
with A SMC Method for Partially Observed Diffusion
2022/23 Statistics CDT Janique Krasnowska Genealogy of a Multilevel Splitting
Algorithm

Masters Students

Year Type Student Project
2008/09 MSc Heng Aaron Yeung Variance Reduction in Importance Sampling
2008/09 MSc James Singleton Variance Reduction in Importance Sampling
2009/10 MSc Ayhen Yuksel MCMC and Particle Filtering for Stochastic Volatility Models
2009/10 MSc Yan Zhou Bayesian Model Selection with Application to Positron Emission Tomography Compartmental Models
2010/11 MMORSE Ho Tang Simultaneous Localization and Mapping
2010/11 MMORSE Keegan Kang Simultaneous Localization and Mapping
2010/11 MSc Antony Medford Approximate Bayesian Computation - How Approximate is Best
2010/11 MSc Axel Finke Multiple Particle Filter Smoothing
2011/12 MSc Yuezhang Liu Importance tempering revisited
2012/13 MMORSE Edwin Yan Ma Approximate Bayesian Computation - How Approximate is Best
2012/13 MMORSE Richard Hopps Approximate Bayesian Computation - How Approximate is Best
2012/13 MMORSE Yeqian Dong Bayesian Inference and the Parametric Bootstrap
2012/13 MSc Xiaojin Liu Timetabling Interdisciplinary University Course
2012/13 MSFM Chloe Harper Hedge Fund Return Replication
2013/14 MMORSE David Whitcombe Simulated Annealing
2013/14 MMathStat Iain Carson Overcatting Without Seymour
2015/16 MMORSE Yushen Ma Tempering Strategies for Sequential Monte Carlo
2015/16 MMORSE Dominic Richards Tempering Strategies for Sequential Monte Carlo

2015/16

MSc Emil Lalov

Further Investigation of the Block-Tempered Particle Filter

2016/17 MSc Project Piotr Wiercinski Predicting the end of a reaction
2016/17 MSc Project Dimitri Zografos Particle Efficient Importance Sampling

2017/18

MMORSE Kaiyan Li

Combining Weighted Samples with Application to Monte Carlo for "Big Data" Problems

2018/19

MMORSE Bartu Gupta

Investigating the Hyvarinen Score for Model Selection

2018/19

MMORSE Callum Latimer

Coupling Constructions and Unbiased MCMC

2018/19

MMathStat Han Zhang

State-space methods for Real-time End of Reaction Forecasting

2019/20

MMathStat Emma O'Hare

Linking Process Parameters and Crystal Properties

2019/20

MSc Theodore Ntounias

Using MCMC Methods to Quantify Gerrymandering in US Congressional Maps

2019/20

MSc Yixuan Yao

Algorithm Comparison against SMC methods and Alive Particle Filter in simulating Quasi Stationary Distribution

2020/21

MSc Rocco Caprio

Topics in Robust Filtering

2020/21

MSc Daniel Kingswell

Forecasting Formula One Grand Prix with State Space Models

2021/22

MSc Alexander Kent Limit Theorems for Sequential
Adaptive Markov Chain Monte Carlo
Methods
2021/22 MSc Benjamin Taylor How Can MCMC Kernels be Most Effectively Employed in an SMC Algorithm?
2022/23 MMORSE Rafael Bilbao-Lopez Hedge Fund Replication Using Kalman Filters
2022/23 MMathStat Subhaan Amir The Effectiveness of Kalman Filtering on Hedge Fund Replication

Undergraduate Projects

Third Year Data Science Projects

Research Interns

URSS / Warwick Statistics Research Internship Students

Year Student Project
2023 Sumit Bagchi State Augmentation in Bayesian Decision Making
2023 Aryan Kotwal Sequential Quasi Monte Carlo Expectation Maximisation Smoothing

If any of the students listed here would like their project dissertations/reports/posters made available then they should send a .pdf to along with confirmation that they would like it made accessible.