معرفی
Claudio Meggio is a researcher affiliated with the University of Oslo's Faculty of Mathematics and Natural Sciences. He collaborates with the Hylleraas Centre and CompSci group, focusing on machine learning applications in chemistry and explainability of models. His PhD research involves boosting algorithms on graph-structured data.
Education: BSc in Mathematics from the University of Trento, MSc in Mathematics (Probability/Statistics) from University of Torino, with study abroad at University of Waterloo. His master's thesis on the COVID-19 outbreak was supervised by Prof. Andrea Pugliese.
Research Interests: Supervised/unsupervised learning, boosting algorithms, graph-structured data analysis, and metal compound studies. He is part of the SALSA team at University of Bolzano and works under supervisors Riccardo De Bin, Johan Pensar, and David Balcells.
Publications include work on Path Boosting for chemistry applications. Active in interdisciplinary projects at the intersection of computational science and chemistry.
