Junior Investigator at IAIFI and affiliated with LIDS at MIT, leading interdisciplinary research projects.
Current projects include:
- Trajectory and SDE inference in computational biology using multimarginal Schrödinger bridges and least squares in distribution space;
- Identifiability theory of stochastic dynamics;
- Probabilistic machine learning and generative models in physics, especially time-domain astronomy, focusing on irregularly sampled sequence data (e.g., time series, spectra) and simulation-based inference;
- Theory of learning human preferences from binary annotations, corresponding experimental design, and robustness checks, with applications in LLM alignment and evaluation;
- Population ecology of apex predators (e.g., jaguars, wolves) using capture-recapture models.
Past work includes:
- Species and feature sampling with heterogeneity, multivariate (completely) random measures, and applications in genetics and sequencing strategies;
- Identifying stellar flares from photometric data using Hidden Markov Models;
- Spike-and-Slab LASSO for multivariate regressions/chain graphs, its frequentist properties, and experimental design for microbiome studies.