My research interests are mostly centered on the intersection of statistics and machine learning with novel application areas. Current projects deal with parallelized Bayesian nonparametrics and multi-messenger constraints, statistical denoising and spatial analysis, generative models and deep learning for anomaly detection, and hybrid analytic and machine learning frameworks for simulations.

Statistics & machine learning:

  • Non-parametric Bayesian methods
  • Estimation theory and sampling
  • Deep learning techniques

Management science & finance:

  • Geospatial analysis and optimization
  • FinTech and econometric methods
  • Computational criminology

Cosmology & astrostatistics:

  • Dark energy and large-scale structure
  • Cosmological parameter estimation
  • Galaxy formation and evolution

Research visits and programs: