Dr. Servadio’s research interest focuses on estimation, control, and astrodynamics. Whenever needed, estimation can be performed on available models to strengthen their validity. With his experience on nonlinear filtering and Bayesian updates, Dr. Servadio will guide the students in incorporating real data into the modeling of the real environment. He has worked extensively with graduate and undergraduate students and working in his lab on the creation of the LEO population dataset, developing economical optimization for Active Debris Removal (ADR) Target selection using Genetic Algorithms.