We welcome three new students of the National PhD AI for Society
Praveen Bushipaka, Claudio Mazzi and Riccardo Porcedda have recently joined L’EMbeDS and the Sant'Anna School as PhD students of the National PhD in AI for Society. Their fellowships are funded by L’EMbeDS, the School and dedicated funds from the PNRR. The nation-wide doctoral program in AI comprises five federated programs, among which the PhD in AI for Society, and brings together a network of 61 universities and research institutions. Specifically, the PhD Program in AI for Society aims to foster the education of researchers, innovators and professionals working on cutting-edge methodology, as well as applications in sectors of high societal impact.
The three PhD students, who belong to the XXXIX cycle, will embark in innovative research directions -- integrating data science approaches with problems specific to the domain pillars of L’EMbeDS.
Praveen Bushipaka: Praveen obtained his Master's degree in Computer Science from the University of Milan in 2020, focusing on the domains of AI and Machine Learning (ML). For his Master's thesis, he worked with Wunderman Thompson applying ML algorithms to the optimization of product placement. He gained experience in Big Data Analytics and developed a keen interest in the application of AI and ML in multiple disciplinary fields -- especially in the use of Natural Language Processing (NLP) in social sciences research. Following such interests, he worked as a researcher at the Sant'Anna School using Large Language Models (LLMs) for the analysis of legal documents. For his PhD research Praveen will focus on designing and developing trustworthy and privacy-aware LLM systems in legal domain, exploiting Federated Learning and efficient parameter tuning techniques. He is currently investigating these methods on English and Italian legal documents.
Claudio Mazzi: Claudio obtained his Master's degree in Mathematical and Theoretical Physics from the University of Milano Bicocca in 2021, with a thesis entitled “Large charge expansion and semiclassical method: the XYZ-model in BPS and superfluid phase”. After obtaining his Master's degree, he taught Mathematics and Physics at Liceo M. Gioia (Piacenza, Italy) and Liceo Respighi (Piacenza, Italy), and was subsequently granted a one-year research fellowship at the Sant’Anna School -- during which he employed stochastic models to estimate claims reserve in the health care system, and worked on performance evaluation indicators for the healthcare system. For his PhD research Claudio will focus on the methodological foundations of AI, encompassing both mathematical principles and computer science perspectives, and on the integration of AI with process management techniques. The purpose is to apply data-driven tools to study the care of chronic patients, starting from data and event logs from the national healthcare system.
Riccardo Porcedda: Riccardo's entire academic path has revolved around data-driven approaches applied to various scientific fields. For his Bachelor degree in Physics at University of Pisa, he worked on a thesis where he employed ML techniques for the classification of astrophysical gamma-ray sources. For his Master's degree in Data Science at the University of Milano Bicocca, he graduated cum Laude with a thesis where he employed Functional Data Analysis methods for time series to study optimal bidding strategies in the energy market. Riccardo also had the occasion of working and publishing on the subject of Explainable AI. For his PhD research Riccardo will focus on data-driven approaches applied to Economics and Finance, analyzing massive data on B2B (Business-to-Business) payments. Instead of treating these as simple one-to-one transactions, Riccardo will model B2B payments as components of financial networks, developing Graph Neural Networks architectures.
