International Visiting Professors

The M.Sc. in Stochastics and Data Science features courses modules taught by renowned visiting professors who are internationally recognised leading experts in their respective fields of research. These activities are partially supported by: 

• CRT Foundation 
• "de Castro" Statistics Initiative

 

Academic year 2024/2025

• Kolyan Ray (Imperial College London), Fall 2024
  

Posterior asymptotics in Bayesian nonparametrics in Bayesian Statistics

• Samuel Hermann, Spring 2025
  

Simulation methods for diffusion processes in Stochastic Processes

• Luis Alberiko Gil-Alana (University of Navarra, Spain), Spring 2025
  

ARIMA time series and spectral theory in Statistics for Stochastic Processes

 

 

Previous academic years

• Samuel Livingstone (University College London, UK), Spring 2024

Monte Carlo methods for statistical inference in Stochastic Modelling for Statistical Applications

• Sergei Fedotov (University of Manchester, UK), Spring 2024
  

On discrete time/space random walks and their diffusion approximations in Stochastic Processes

• Luis Alberiko Gil-Alana (University of Navarra, Spain) Spring 2024
  

Spectral analysis of time series in Statistics for Stochastic Processes

• Ismael Castillo (Univesrité Sorbonne, France), Fall 2023

Asymptotics in Bayesian nonparametrics in Bayesian statistics

• Pierre Patie (Cornell University, USA), Spring 2023

A first introduction to diffusion processes in Stochastic Processes

• Paul Jenkins (University of Warwick, UK), Spring 2023
  

Simulation and inference in Population Genetics in Stochastic Modelling for Statistical Applications

• Luis Alberiko Gil-Alana (University of Navarra, Spain) Spring 2023
  

Spectral analysis of time series in Statistics for Stochastic Processes

• Vinayak Rao (Purdue University, USA), Fall 2022

Causal machine learning in Statistical Machine Learning

• Marta Catalano (University of Warwick, UK), Fall 2022

Dependent nonparametric priors via completely random measures in Bayesian statistics

• Natesh Pillai (Harvard University, USA), Spring 2022

Fundamentals of Markov chain Monte Carlo methods in Stochastic Modelling for Statistical Applications

• Goran Peskir (University of Manchester, UK), Spring 2022

An introduction to Brownian motion in Stochastic Processes

• Alessandro Flammini (Indiana University, USA) Spring 2022
  

Dynamical processes in complex networks in Complex networks

• Luis Alberiko Gil-Alana (University of Navarra, Spain) Spring 2022
  

Frequency domain and spectral analysis in Statistics for Stochastic Processes

• Francesco Russo (ENSTA Paris Tech, France) Fall 2021
  

Brownian motion and stochastic integrals in Stochastic Differential Equations

• Bas Kleijn (University of Amsterdam, Netherlands), Fall 2021 

Frequentist limits from Bayesian statistics in Bayesian statistics

• Goran Peskir (University of Manchester, UK), Spring 2021 

Diffusion processes and boundary classification in Stochastic Processes

• Paul Jenkins (University of Warwick, UK), Spring 2021
  

Simulation and inference in Population Genetics in Stochastic Modelling for Statistical Applications

• Luis Alberiko Gil-Alana (University of Navarra, Spain) Spring 2021
  

Frequency domain and spectral analysis in Statistics for Stochastic Processes

• David Rossell (Universitat Pompeu Fabra, Spain), Fall 2020
  

Bayesian inference in high dimensions in Bayesian statistics

• Franziska Kuhn (Dresden University, Germany), Fall 2020

Some path properties of Brownian motion in Stochastic Differential Equations

• Albert Milani (University of Wisconsin-Milwaukee, USA), Fall 2020

Distribution theory, Fourier and Laplace transforms in Analysis

• Pierre Jacob (Harvard University, USA), Spring 2020
  

Probability couplings and Monte Carlo in Stochastic Modelling for Statistical Applications

• Yosef Rinott (Hebrew University of Jerusalem, Israel), Spring 2020

Spectral theory for times series and asymptotics in Statistics for Stochastic Processes

• Jozsef Lorinczi (Loughborough University, UK), Spring 2020 (canceled for Covid-19 emergency)
  

Ornstein-Uhlenbeck processes and exit problems in Stochastic Processes

• Enrico Scalas (University of Sussex, UK), Fall 2019

Heuristic introduction to stochastic differential equations with simulation in Stochastic Differential Equations

• Botond Szabo (Leiden University, Netherlands), Fall 2019

Asymptotics for posterior Bayesian inference in Bayesian statistics

• Yosef Rinott (Hebrew University of Jerusalem, Israel), Spring 2019
  

Levy Processes in Stochastic Modelling for Statistical Application

• Luis Alberiko Gil-Alana (University of Navarra, Spain) Spring 2019 
  

Frequency domain and spectral analysis in Statistics for Stochastic Processes

• Samuel Herrmann (Université de Bourgogne Franche-Comté, France) Spring 2019 
  

Simulation methods for diffusions in Stochastic Processes

• Omiros Papaspiliopoulos (Universitat Pompeu Fabra, Spain) Fall 2018
  

Scalable algorithms in modern Bayesian computation in Bayesian statistics

• Julien Berestycki (University of Oxford, UK) Spring 2018
  

Topics in branching processes in Stochastic Modelling for Statistical Applications

• Vassili Kolokoltsov (University of Warwick, UK), Spring 2018
  

Markov semigroups and diffusion processes in Stochastic Processes

• Yosef Rinott (Hebrew University of Jerusalem, Israel), Spring 2018
  

Spectral theory for times series and asymptotics in Statistics for Stochastic Processes

• Alessandro Flammini (Indiana University, USA) Spring 2018

Dynamical processes in complex networks in Complex networks

• Jim Griffin (University of Kent, UK) Fall 2017
  

Computational methods for Bayesian nonparametrics in Bayesian statistics

• Isaac Meilijson (Tel Aviv University, Israel) Fall 2017
  

Introduction to martingales in Probability Theory

• Dario Spanò (University of Warwick, UK) Spring 2017
  

Introduction to stochastic modelling in Population Genetics in Stochastic Modelling for Statistical Applications

• Alessandro Flammini (Indiana University, USA) Spring 2017
  

Dynamical processes in complex networks in Complex networks

• Vassili Kolokoltsov (University of Warwick, UK), Spring 2017
  

Brownian motion in Stochastic Processes

• Yosef Rinott (Hebrew University of Jerusalem, Israel), Spring 2017
  

Spectral theory for times series and asymptotics in Statistics for Stochastic Processes

• Ramses H. Mena (UNAM, Mexico), Fall 2016
  

Random partitions and dependent processes in Bayesian nonparametric statistics

• Goran Peskir (University of Manchester, UK), Spring 2016
  

Diffusion processes and conditioned processes in Stochastic Processes

• Andreas E. Kyprianou (University of Bath, UK), Spring 2016
  

Lévy processes and Poisson random measures in Stochastic Modelling for Statistical Applications