During this postdoc, I will be modeling the system of interest with a probabilistic framework by using the Random Finite Set(RFS) approach. This approach accounts for measurement, cardinality estimation, and state estimation challenges by modeling the measurement vectors and state vectors as finite sets.
During this project, I will be using Probability Hypothesis Density(PHD) filters approach to model the RFS distributions as Poisson Point Processes(PPP) where I will focus on estimating the intensity function of the PPP.
I am currently working on the first part of the postdoc, which requires developing machine learning-based methods to estimate the intensity function of the PPP.
This page will be updated during these two years that I am at Inria.