cv

Curriculum Vitae

General Information

Full Name Liam Llamazares-Elias
Email l.llamazares@lancaster.ac.uk
Website https://liamllamazareselias.com

Education

  • 2025
    PhD in Mathematical Modelling, Analysis and Computation
    University of Edinburgh, School of Mathematics
    • PhD with Integrated Study. Supervised by Prof. Finn Lindgren and Dr. Jonas Latz.
  • 2020-2021
    MA in Mathematical Modelling
    University of Salamanca
    • GPA: 9.85/10
    • Master's thesis: Mathematical Theory in Non-linear Diffusion Processes, The Porous Medium. Grade: 10/10 (Summa cum laude)
    • Link to thesis: here
  • 2016-2020
    BSc in Mathematics
    University of Salamanca
    • GPA: 9.14/10
    • Undergraduate thesis: Some Results on the Existence and Uniqueness of Solutions to the Navier-Stokes Equations. Grade: 10/10 (MH)
    • Link to thesis: here

Research Experience

  • Sep. 2025 -- Aug. 2028
    Senior Research Associate
    Department of Mathematics and Statistics, Lancaster University
    • Postdoctoral position within the EPSRC Hub in Probabilistic AI (ProbAI Hub).
    • Supervised by Prof. Chris Nemeth, and Prof. Paul Fearnhead.
  • June 2023
    Participant in Research Program
    Isaac Newton Institute for Mathematical Sciences, University of Cambridge
    • The Mathematical and Statistical Foundation of Future Data-Driven Engineering.

Publications

  • 2026
    A Parameterization of Anisotropic Gaussian Fields with Penalized Complexity Priors
    • L. Llamazares-Elias, J. Latz, F. Lindgren. Journal of the American Statistical Association. DOI · arXiv
  • 2026
    Data-driven approximation of Koopman operators and generators: Convergence rates and error bounds
    • L. Llamazares-Elias, S. Llamazares-Elias, J. Latz, S. Klus. Journal of Computational Dynamics, 15, 163-206. DOI · arXiv
  • 2021
    An Analysis of Contact Tracing Protocol in an Over-Dispersed SEIQR Covid-Like Disease
    • L. Llamazares-Elias, S. Llamazares-Elias, A. Martín del Rey. Physica A: Statistical Mechanics and its Applications. DOI

Selected Talks and Presentations

  • June 2026
    Data-driven approximation of transfer operators
    AI Hub Seminar, Department of Statistics, University of Oxford
    • Invited seminar.
  • April 2026
    Non-stationary Gaussian Fields and Penalized Complexity Priors
    CSML Reading Group, Lancaster University
  • December 2025
    Robots, simulación y optimización
    MUMOMA, University of Salamanca
    • Invited talk.
  • May 2025
    Data-driven approximation of Koopman operators and generators: Convergence rates and error bounds
    Hidden Structures in Dynamical Systems, Optimization, and Machine Learning Workshop, L'Aquila
  • December 2024
    Penalized Complexity Priors for Non-Stationary Gaussian Fields
    CMStatistics Conference, London
  • December 2024
    Penalized Complexity Priors for Anisotropic and Non-Stationary Gaussian Fields
    Spatial Point Processes Reading Group
  • December 2023
    A Parameterization of Anisotropic Gaussian Fields with Penalized Complexity Priors
    CMStatistics Conference, Berlin
  • December 2023
    A Parameterization of Anisotropic Gaussian Fields with Penalized Complexity Priors
    Mathematics of Information and Data Science Seminar, University of Edinburgh
  • April 2023
    A Parameterization of Anisotropic Gaussian Fields with Penalized Complexity Priors
    Numerical Analysis of Stochastic Partial Differential Equations Workshop

Scholarships and Awards

  • 2021-2025
    MAC-MIGS PhD Scholarship
    University of Edinburgh, Maxwell Institute Graduate School
    • Competitive fully funded PhD position.
  • 2020-2021
    Collaboration Scholarship
    Department of Applied Mathematics, University of Salamanca
    • Awarded by the Spanish Ministry of Education.
  • 2020-2021
    Research Scholarship, Porous Medium Equation
    Institute of Theoretical Physics and Mathematics, University of Salamanca

Teaching Experience

  • 2023-2025
    Tutor of Statistical Methodology
    University of Edinburgh
  • 2023-2024
    Tutor of Applied Statistics
    University of Edinburgh

Academic Service

  • 2025-Present
    Organiser, Computational Statistics and Machine Learning Reading Group
    Lancaster University
  • 2026-2027
    Working Group Member, Prob_AI Hub Winter School
    EPSRC Hub in Probabilistic AI
    • Contributing to the programme and speaker selection for the Winter School in Bristol.
  • 2022
    Co-organiser, Malliavin Calculus Reading Group
    University of Edinburgh

Other Experience

  • 2022--Present: Author of mathematics blog on PDE and stochastic analysis. nowheredifferentiable.com
  • 2023-2024: Participation in reading group on Mean field games and interacting particle systems.

Skills

  • Programming: Experienced in use of Python, R, C and Mathematica.