From 2015 I work in the ALTAIR robotics laboratory, I had the opportunity to see different aspects of computer vision: from virtual reality with a hand tracking device, to the implementation of cross-platform serious games. During the thesis I became passionate about neural networks with a focus on temporal modeling. I carried out this research developing time delay neural network for automatic recognition of collaborative industrial processes.
My Ph.D, supervised by Prof. Paolo Fiorini, concerns Industry 4.0 and the development of a decision support system that allows operators to intervene on the machines improving product quality using a data driven approach. Right now, I’m studying causal inference as I am convinced it can describe the way of thinking typical of the manufacturing operators which embed strong causes-effect relationship.
I want to combine my skills on machine learning and new causal discovery methods to get a full description of the industrial plant understanding not only the features of the product but also the interaction between the product and the whole plant, employers included, within a data driven approach. Possible outcomes of this researches are to reduce the complexity of the plants and allow SME to better respond to customer’s needs, create a coherent schema for in line interventions and finally I hope to improve collaboration between academic research and industry.