AI

Stefano Leonardi

Stefano Leonardi is full professor of Computer Science at Sapienza University of Rome, and leads the Web algorithmics and data mining group at the Department of Computer, Control and Management Engineering. After receiving his PhD from Sapienza University of Rome, he held postdoctoral positions at the International Computer Science Institute and at the Max Planck Institut für Informatik, Saarbrücken. Since then, Dr. Leonardi has held visiting positions at Carnegie Mellon University (2005), Google Research NYC (2013), and at the Simons Institute for the the Theory of Computing, Berkeley (2016).

He is broadly interested on algorithm design and its applications to Internet economy and to data science, with research focusing on approximation and online algorithms and on the modeling of uncertainty in various optimization problems. He is also interested into algorithmic problems at the intersection between economics and computation for auction design and Internet advertising. Additionally, Dr. Leonardi is actively working on algorithmic design for data mining applications in the realm of Web search, social networks and crowdsourcing.

Dr. Leonardi received a Google Faculty Research Award in 2012 in support of his research on online market algorithms and a Google Focused Research Award in 2014 on “Algorithms for Large-scale Data Analysis”. He co-chaired the 2013 ACM conference on Web Search and Data Mining, the 2015 International WWW conference, and the semester held in 2016 on “Algorithms and Uncertainty” at the Simons Institute for the Theory of Computing, Berkeley. He serves in the Editorial board of the ACM Transactions on Algorithms. He chairs the study program on Science and Technology at the Sapienza School for Advanced Studies and the Data Science Program at Sapienza University of Rome.

While at Google Research NYC, Dr. Leonardi collaborated with Google researchers on a wide set of algorithmic problems in Internet advertising and graph mining relevant to both industry and academia. He was involved in the study of new algorithmic solutions for advance reservation of inventories in the two-sided publishers/advertisers display ads market and for online recommendation to advertisers in the Adwords market. For graph mining, he was involved in the design of new sampling methods for measuring the structural properties of large-scale weighted networks and the design of new algorithms for hierarchical and dynamic clustering of networks. Publications containing the results of this research appeared at WWW 2014, ITCS 2015, ICALP 2016, Journal of Internet Mathematics, NIPS 2016.