Bio
Giuseppe Ragusa received his BA and MA in economics from Bocconi University in 1999 and 2000, respectively. He completed his Ph.D. in Economics at University of California, San Diego in 2005. His first academic job was as an Assistant Professor at Rutgers University from 2005-06. He then taught at University of California, Irvine and at Luiss University in Rome.
From 2013 he serves as the director of the Master in Big Data Analytics and scientific director of the Big Data Lab at Luiss Business School. He is research interests are theoretical and applied econometrics, labor economics, computational methods, and machine learning applications. The applied part of his research has focused on the study of the labor market with a particular emphasis on patterns of income inequality. He has published many papers on econometrics that have appeared in the top scientific journals including the Journal of Econometrics, Review of Economics and Statistics, Econometric Theory.
He has taught econometrics, statistics, and machine learning at undergraduate and graduate level. He also teaches statistics, econometrics, and machine learnings at Luiss Business School (LBS).
Giuseppe’s research interests are theoretical and applied econometrics. Theoretical research interests include incorporating expert judgment into macroeconomic structural models. He is interested in computational methods for macroeconomic and finance based on the interplay of Bayesian and classical estimation techniques. He is involved in several research projects having as a common thread the use of big data and machine learning for econometric applications. The more applied part of his research has focused on the study of the labor market with a particular emphasis on patterns of income inequality. His more recent works have focused on using high-frequency financial data in understanding the transmission mechanism of monetary policy.
He is an avid Julia user and he has taught Julia at the graduate level in several classes and will use Julia in the coming fall when he will teach Machine Learning at London Business School using Julia. He is also a consultant for many firms on topics related to applications of Julia in the field of optimization of processes.