Research lab: Alstom Ferroviaria SPA
Via di Corticella, 75, 40128 Bologna BO
Digital and Integrated System

Arianna Nocente

Msc Data Science and Business Informatics, PhD Candidate

Born in Italy, she has consistently pursued a multidisciplinary approach with a focus on analytical, goal-oriented outcomes. She earned her B.Sc. degree in Civil Engineering in 2018 and her M.Sc. degree (cum laude) in Computer Science - Data Science and Business Informatics in 2021, from the University of Pisa. During her Master’s program, she began working with Alstom in Bologna, where she contributed to the development of technologies for the railway industry on international projects spanning Italy, Denmark, and India. Currently, she is a third-year Industrial PhD candidate in Smart Industry at the University of Pisa and continues her employment with Alstom in Bologna. Recently, she spent six months at Alstom’s headquarters in Paris as a data scientist, conducting research on anomaly detection for automatic train operations.


Strategic and Competitive Intelligence, Artificial Intelligence, Data Science, Industrial Automation

Research Topic:

Her PhD research is centered on Model-Based methodologies applied to the railway sector. Additionally, she has worked on the development of neural networks for the medical field in collaboration with the University of Siena, automated document processing using Natural Language Processing in partnership with Columbia University and the National Research Council of Pisa, and the customization of chatbots for industrial applications.

Other Activities:

During her Master’s program, she was a member of the Formula SAE Driverless division at the University of Pisa. She also investigated house price prediction using road network topology with support from SoBigData, which resulted in a conference paper on Complex Networks and won the Best Conference Presentation award in Lisbon in 2019. In 2023, she was engaged in the Summer School organized by the European Institute of Innovation & Technology at the Technical University of Munich, focusing on Methods and Tools for Resilient Industrial IoT with use cases from sponsors such as Kaercher, Siemens, and Selmo.