Juan Kuntz

Juan Kuntz

Research Fellow

The University of Warwick

About me

I am a Research Fellow working with Adam Johansen and Theo Damoulas as part of the Warwick Machine Learning Group, the Department of Statistics at the University of Warwick, and the Alan Turing Institute. I develop tools for machine learning, Bayesian inference, and computational statistics by combining concepts and techniques from optimization and Monte Carlo; see here for a recent example. In the past, I worked on Markov processes, numerical methods for the analysis thereof, and applications of control theory to synthetic biology. I have also been writing a book on Markov chains, see here for the latest draft.

Short CV.

Interests
  • Machine Learning
  • Computational Statistics
  • Optimization
  • Monte Carlo Methods
  • Control Theory
Education
  • PhD in Bioengineering, 2018

    Imperial College London

  • MEng in Biomedical Engineering, 2012

    Imperial College London

Publications

Click here to search the publications. Or you could try the tags below the list.
(2022). Scalable particle-based alternatives to EM. Under review (AISTATS).

PDF Cite Code Video

(2022). Product-form estimators: exploiting independence to scale up Monte Carlo. In Statistics and Computing.

PDF Cite Video DOI

(2021). The divide-and-conquer sequential Monte Carlo algorithm: theoretical properties and limit theorems. Under review (Annals of Applied Probability).

PDF Cite

(2021). Approximations of Countably Infinite Linear Programs over Bounded Measure Spaces. In SIAM Journal on Optimization.

PDF Cite DOI

(2020). Markov chains revisited. Book draft.

PDF Cite

(2019). Diffusion limit for the random walk Metropolis algorithm out of stationarity. In Annales de l’Institut Henri Poincaré, Probabilités et Statistiques.

PDF Cite DOI

(2019). Bounding the stationary distributions of the chemical master equation via mathematical programming. In The Journal of Chemical Physics.

PDF Cite DOI

(2019). The exit time finite state projection scheme: bounding exit distributions and occupation measures of continuous-time Markov chains. In SIAM Journal on Scientific Computing.

PDF Cite DOI

(2018). Non-stationary phase of the MALA algorithm. In Stochastics and Partial Differential Equations: Analysis and Computations.

PDF Cite DOI

(2016). Bounding Stationary Averages of Polynomial Diffusions via Semidefinite Programming. In SIAM Journal on Scientific Computing.

PDF Cite DOI

(2014). Model Reduction of Genetic-Metabolic Networks via Time Scale Separation. In A Systems Theoretic Approach to Systems and Synthetic Biology I: Models and System Characterizations.

PDF Cite DOI