I'm a co-founder and Head of Data Science at Evidation Health.
In the past, I worked on aggregation of news articles at Ask.com, on community detection in social networks at Google and on low-latency web caching at the CERN.
My research focuses on designing efficient algorithms for finding approximate solutions to problems for which computing an exact solution would require an impractical amount of resources.
Simply put, a recurrent pattern you'd find in my research papers is "This theorem proves that this problems can't be solved exactly on large inputs within a reasonable amount of time or memory, but if you're willing to settle for a slightly suboptimal solution, here's an algorithm that can compute that efficiently."
The problems I studied include detecting outliers on large streams of network packets in real time; quickly finding shortest paths in road networks under heavy traffic conditions; and efficiently partitioning large graphs into balanced components.
During my Ph.D. I was lucky enough to spend time visiting prestigious research institutions such as Google Research, ETH Zurich, and UIUC. That allowed me to collaborate with scholars from many different fields of study, including computational geometry, computer security, data compression, and computer vision.
You can find a complete list of my publications here.
- Ph.D., Computer Science, UCSB (2012), Dean's Fellowship.
- M.S., Computer Science, UCSB (2011), GPA 4.0
- Diploma di Licenza Specialistica, Sant'Anna School of Advanced Studies (2007), Magna cum Laude.
- M.E., Computer Engineering, University of Pisa (2007), Summa cum Laude.
- Diploma di Licenza, Sant'Anna School of Advanced Studies (2005), Summa cum Laude.
- B.E., Computer Engineering, University of Pisa (2004), Summa cum Laude.
I live in Santa Barbara, CA, where I spend most of my spare time at a small or negative distance from the Pacific Ocean.
I grew up on Cappelletti and Piadina on a farm near Ravenna, Italy.
See my full resume here.