Solym  MANOU-ABI               

(Data Modeling, Cloud computing)

Solym conducts research in computational probability and statistics, with a particular focus on stochastic processes and statistical methods for such processes. He is especially interested in probability and statistics combined with strong learning approaches applied to real-world data. His research explores stable laws, heavy-tailed distributions, stable processes, Markov chains, and stochastic differential equations. A primary area of interest lies in statistical learning for stable non-Gaussian processes, Markov processes, and heavy-tailed distributions. He is also engaged in data modeling and computational methods, including spatial statistics and machine learning techniques.