Brief research description

Research areas: probability, statistical and mathematical physics, algebraic combinatorics, statistical/machine learning, random sampling

Research synopsis: I am interested in finite-size and asymptotic behavior of statistical mechanical (and combinatorial) models in the Kardar--Parisi--Zhang universality class and beyond. Examples of interest include:

• last passage percolation (and the related TASEP);

• measures on partitions (motivated by probability or representation theory) and Young tableaux;

• lattice and continuous fermions;

• random tilings (mostly by dominoes and lozenges, examples here);

• Airy, Bessel, Pearcey, sine, ... processes;

• random matrix models;

• determinantal/pfaffian point processes in general;

• the six-vertex model;

• symmetric polynomials (e.g. Schur, Macdonald) and special functions (elliptic, hypergeometric, q-, etc.), from combinatorial and probabilistic perspectives.

On the applied side, I am looking into:

• machine and statistical learning (various aspects, notably transfer learning, or applying statistical techniques to 'areas where they don't naturally fit');

• random sampling algorithms and Markov dynamics (see simulations page for a glimpse).