CV

General Information

Name Lucas M. Moschen
Languages Portuguese, English, studying French
E-mail lucas.moschen22@imperial.ac.uk
Description My research combines mathematical modelling, control theory, and numerical analysis to study probability distributions and interacting stochastic systems. I develop feedback control methods for Fokker-Planck, McKean-Vlasov, and Wasserstein gradient-flow models based on spectral properties, with current work on coupled populations, sampling, and effective dynamics. My earlier research concerns constrained vaccination policies on networks and statistical inference for correlated proportions.

Education

  • 2024 - present
    Ph.D. in Mathematics
    Imperial College London, London (UK)
    • Supervisors: Grigorios A. Pavliotis and Dante Kalise.
    • Research focus: control and stabilisation of probability distributions, Wasserstein gradient flows, and interacting particle systems.
  • 2023 - 2024
    MSc in Mathematics of Modelling
    Sorbonne University, Laboratoire Jacques-Louis Lions - Paris (France)
    • Supervisors Camille Coron and Luis Almeida
    • Memoire "Modeling and Control of Mosquito Populations, From Stochastic Processes to Reinforcement Learning"
    • Research Focus Analysis and control of stochastic models for mosquito populations.
  • 2022 - 2023
    MSc in Mathematical Modelling
    Fundação Getulio Vargas, School of Applied Mathematics - Rio de Janeiro (Brazil)
    • Supervisor María Soledad Aronna
    • Master's Thesis "Optimal vaccination strategies for epidemics in metropolitan areas"
    • Research Focus Optimal control of constrained affine systems, applied to epidemic dynamics in networks of cities.
  • 2018 - 2021
    BSc in Applied Mathematics
    Fundação Getulio Vargas, School of Applied Mathematics - Rio de Janeiro (Brazil)
    • Supervisor Luiz Max Carvalho
    • Bachelor Dissertation "Prevalence estimation and binary regression methods for respondent-driven sampling with outcome uncertainty"
    • Research Focus Bayesian methods for prevalence estimation under partial graph observation.

Research Experience

  • 2024 - present
    Control of Probability Distributions and Interacting Systems
    Imperial College London
  • May - Jun 2025
    Research Visit
    CERMICS, Paris, France
    • Visited Urbain Vaes to develop research directions related to my PhD.
  • 2023 - 2024
    Control and Stochastic Modeling in Biology
    Sorbonne University
    • Developed models for mosquito population control using reinforcement learning.
    • Supervised by Luis Almeida and Camille Coron.
  • 2022 - 2023
    Optimal Control in Epidemiology
    FGV
    • Investigated optimal vaccination strategies across connected populations, supervised by Maria Soledad Aronna.
    • Epidemics in networks — master’s dissertation followed by papers in Infectious Disease Modelling (2024) and IEEE Control Systems Letters (2025), covering commuting networks, vaccination constraints, and bang-bang policies.
  • 2022 - 2023
    Statistical Inference and Bayesian Methods
    Fundação Getulio Vargas (FGV)
    • Modelling correlated proportions — classical and Bayesian inference, prior elicitation, and model diagnostics with Luiz Max Carvalho.
    • Compared bivariate beta and logistic-normal models, with applications to vaccination coverage and diagnostic-test data. Published in TEST (2026).
  • 2014 - 2021
    Early Research & Scientific Initiation
    Fundação Getulio Vargas & IMPA
    • Undergraduate research on optimal control in biological models (supervised by Maria Soledad Aronna).
    • Junior Scientific Initiation at IMPA (2014-2017).
    • Co-authored early papers on optimal control and epidemiology.

Publications and Preprints

Teaching Experience

  • 2024 - present
    Graduate Teaching Assistant / Senior GTA
    Imperial College London
    • Linear Algebra and Groups — Fall 2024 and Winter 2026 (BSc level); Senior GTA in Winter 2026.
    • Optimisation and Decision Models — Winter 2026.
    • Analysis I — Fall 2024 and Winter 2025 (BSc level).
  • 2019 - 2023
    Teaching Assistant
    Fundação Getulio Vargas, School of Applied Mathematics
    • Graduate level (Ph.D. and MSc)
      • Partial Differential Equations and Applications (2023), Probability (2023), Functional Analysis (2022), Statistical Inference (2022), Bayesian Statistics (2022)
    • BSc level
      • Partial Differential Equations (2021, 2022), Curves and Surfaces (2021, 2022), Introduction to Numerical Analysis (2021), Statistical Inference (2020), Ordinary Differential Equations (2020), Linear Algebra (2019)
  • 2019
    Volunteer Algebra Teacher
    Project Elos Educação - Rio de Janeiro (Brazil)
    • Prepared students for high school entrance exams.

Honors and Awards

  • 2023
    • Best poster presentation for the work on COVID-19 mathematical modelling at the Latin American Congress on Industrial and Applied Mathematics;
    • Best poster presentation for the work on COVID-19 mathematical modelling at the IX Congreso de Matemática Aplicada, Computacional e Industrial;
  • 2022
    • Scientific Initiation Award SBMAC (3rd place) for my Bachelor's Dissertation
  • 2021
    • Academic Excellence with the highest final grade in the BSc course.
  • 2013 - 2017
    • Two gold, one silver and two bronze medals in the Brazilian Mathematical Olympiad of Public Schools;

Social Engagement

  • 2024 - present
    Academic & Professional Societies
    • SBMAC Jovem Member, Brazilian Society of Computational and Applied Mathematics - Supporting content dissemination on social media.
    • SIAM Student Chapter Member - Organizing academic events and outreach activities.
    • Department Representative at Imperial College London.
  • 2023
    Academic Representation & Conference Organization
    • Member of the Local Committee for the Latin American Congress on Industrial and Applied Mathematics (LACIAM 2023).
    • Representative of graduate students on the School of Applied Mathematics (FGV) Board.
  • 2018 - 2019
    Community & Student Leadership
    • Vice-President of the Student Association, School of Applied Mathematics, FGV.
    • Volunteer at the Elos Educação project, Rio de Janeiro, Brazil (2019) - Providing educational support for students.

Conferences, Workshops, and Seminars

Relevant Knowledge

  • Programming languages
    • Programming skills in Python, R, Julia, C++, Matlab and JavaScript
  • Additional programming skills
    • Programming tools Git, Visual Studio Code and Project Jupyter