Lorenzo Perini

Lorenzo Perini is a skilled researcher with a focus on data science and machine learning. Experience includes a Data Science Intern role at Tierra S.p.A. where Lorenzo investigated predictive maintenance and anomaly detection for IoT data. At KU Leuven, Lorenzo serves as a PhD Researcher, concentrating on topics such as PU Learning, Active Learning, Transfer Learning, Anomaly Detection, Uncertainty Quantification, and Learning to Reject. Lorenzo has also held positions as a Research Scientist at Meta and a Visiting PhD Researcher at the University of Helsinki, supported by the Sofina-Boel Foundation Scholarship. Additionally, Lorenzo completed a Machine Learning Research Internship at the Bosch Center for Artificial Intelligence. Education culminates in a PhD in Computer Science from KU Leuven, pursued between 2019 and 2024.