volesti

During my PhD I developed volesti. It is a open-source C++ library, with an R interface. volesti implements various MCMC algorithms for high-dimensional sampling and volume approximation of convex bodies as well as functions for copula estimation and portfolio scoring in financial modeling.

dingo

During my PhD I also developed dingo. It is a python package that analyzes metabolic networks. It relies on high dimensional sampling with Markov Chain Monte Carlo (MCMC) methods and fast optimization methods to analyze the possible states of a metabolic network. To perform MCMC sampling, dingo relies on the C++ package volesti, which provides several algorithms for sampling convex polytopes. dingo also performs two standard methods to analyze the flux space of a metabolic network, namely Flux Balance Analysis and Flux Variability Analysis.

Google Summer of Code

Google

My projects as student hosted by R-project for statistical computing org:

• State-of-the-art geometric random walks in R, 2019.

• Efficient R tools for geometrical statistics, 2018.

The projects that I mentored hosted by GeomScale org:

• From DNA sequences to metabolic interactions: building a pipeline to extract key metabolic processes (GSoC 2021).
• Monte Carlo Integration (GSoC 2021).
• Counting linear extensions (GSoC 2021).
• High dimensional geometric computations with least matrix inequalities (GSoC 2021).

• Parallel Geometric Random Walks with Sparse Numerical Optimizations (GSoC 2021).

• A comparative study of uniform high dimensional samplers (GSoC 2020).
• Sampling from High-Dimensional log-concave densities (GSoC 2020).