Dr Zito’s main research interest is in mapping perception into actions to model intelligent behaviours for next-gen AI systems. Perception is hard and uncertain in real-world tasks, autonomous systems have the need of computational models for i) inferring the current state of the world from noisy sensors; ii) making predictions on how their actions will effect changes in the state, given unknown or uncertain dynamics; and select the most resonable actions for safety completing the desired task. Dr Zito employs a combination of model-based and data-driven machine learning approaches to provide robust autonomous reasoning to machines that have to interact with the physical world.
PhD in Intelligent Robotics, 2015
University of Birmingham (UK)
MPhil in Machine Learning and AI systems, 2012
Universita' di Pisa (Italy)
BS in Math and Computer Science, 2002
Universita' degli studi di Siena (Italy)