Giulia DeSalvo is a fifth year mathematics PhD student at NYU’s Courant Institute of Mathematical Sciences with funding from NSF. Her research interests are in both theory and applications of machine learning including computational learning theory, decision trees, ensemble methods, abstention learning, and on-line learning. She received a B.A. in applied mathematics and Italian studies from UC Berkeley with Highest Honors in Applied Mathematics and Highest Distinction in General Scholarship. She has worked and lived in multiple countries namely Italy, US, Japan, France, Germany, and Switzerland. Most notably, she completed a Fulbright in Italy and a NSF funded REU in Japan. Outside of research, Giulia enjoys volleyball, hiking, rock climbing, and photography.
You can reach her at desalvo (at) cims (dot) nyu (dot) edu.