M.O.D.A.L. – Mathematical mOelling and Data AnaLysis research group
In the recent years, there has been an exponential growth in researchers’ use of the term “Data Science” to describe the interdisciplinary field of collecting, drawing inference from, and acting on data. We are facing an evolution in the way traditional Business Intelligence (BI) operations are conducted, bringing it closer to Data Science. In applying innovative techniques to old problems, however, we must be careful to distinguish between those that are advances in Machine Learning (ML) research and concrete results. ML offers the possibility to automate processes, even sophisticated ones, without having to explicitly program a computer, but letting the rules and structures emerge from the available data. First, the amount of data must be sufficient to support the algorithms and distinguish the value signal from the background noise. However, there are many possible models and approaches in order to accomplish this task. This research group integrates the mathematical, statistical and computer science knowledge to develop new Data Analysis, Machine and Deep Learning methodologies for complex phenomena.
People
Francesco Piccialli - Founder, Head and Scientific Coordinator of the M.O.D.A.L. group, Associate Professor of Computer Science | ||||
Salvatore Cuomo - Co-Founder of the M.O.D.A.L. group, Scientific Machine Learning coordinator, Associate Professor of Numerical Analysis | ||||
Fabio Giampaolo | Edoardo Prezioso | Stefano Izzo | Diletta Chiaro | MariaPia De Rosa |
Ph.D., Research Fellow | Ph.D., Research Fellow | Ph.D. student | Ph.D. student | Ph.D. student |
Scholar Link | Scholar Link | Scholar Link | Scholar Link | |
Pian Qi | Daniela Annunziata |
Martina Savoia | Marzia Canzaniello | Sara Amitrano |
Ph.D. student | Ph.D. student | Ph.D. student | Ph.D. student | Ph.D. student |
Scholar Link |