In my doctoral thesis, I develop novel deep learning models to detect human affective states based on time-series data and analyze how the developed models could be explained. My current research interests are machine learning, explainable AI, time series.
Before joining my doctoral studies, I worked on developing evolutionary algorithms for optimization in dynamic environments.
AIxIA 2020 – Advances in Artificial Intelligence: XIXth International Conference of the Italian Association for Artificial Intelligence, Virtual Event, November 25–27, 2020, Revised Selected Papers, Springer 2021 : 3-18