I am interested in multiple aspects of computational statistics and in the development of novel methodologies. My area of research falls under the general domain of “high-dimensional filtering”, with epidemiology as a real-world application (see section “Area of interests” for more details). I am also an avid programmer, with knowledge of C++, R, and Python.

# List of publications
• Approximating optimal SMC proposal distributions in individual-based epidemic models,
  by L. Rimella, C. Jewell, P. Fearnhead (Statistica Sinica 2023)
• Consistent and fast inference in compartmental models of epidemics using Poisson Approximate Likelihoods,
  by M. Whitehouse, N. Whiteley, L. Rimella (JRSS:Series B)
• Inference on Extended-Spectrum Beta-Lactamase Escherichia coli and Klebsiella pneumoniae data through SMC,
  by L. Rimella, et al. (JRSS:Series C)
• Exploiting locality in high-dimensional factorial hidden Markov models,
  by L. Rimella, N. Whiteley (JMLR 2022)
• Inference in stochastic epidemic models via multinomial approximations,
  by N. Whiteley, L. Rimella (AISTAT 2021)
• Simulation Based Composite Likelihood,
  by L. Rimella, C. Jewell, P. Fearnhead (preprint)
• A State-Space Perspective on Modelling and Inference for Online Skill Rating,
  by S. Duffield, S. Power, L. Rimella (preprint)
• Dynamic bayesian neural networks,
  by L. Rimella, N. Whiteley (preprint)