Francesco PiccialliAssistant Professor of Computer Science
Department of Mathematics and Applications “R. Caccioppoli” (DMA)
University of Naples Federico II (UNINA), Italy
Speech Title: Lessons Learned from Artificial Intelligence applications in Cultural Heritage and Medicine
Abstract: In recent years, there has been an exponential growth in researchers’ use of the term “Data Science” to describe the interdisciplinary field of collecting, drawing inferences from, and acting on data. We are facing an evolution in how 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 advances in Machine and Deep Learning (ML and DL) research and concrete results. DL offers the possibility to automate processes, even sophisticated ones, without having to program a computer explicitly 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 to accomplish this task. The choice of the most suitable models depends crucially on the type of problem and the data available. The world of research (state of the art) offers some preliminary indications in this regard.
In this talk, we firstly discuss the application of ML techniques on IoT data collected in a Cultural Heritage framework. Behavioural data have been gathered in a non-invasive way to achieve a classification that can be exploited by cultural stakeholders in terms of medium-long term strategy and also in terms of strictly operational decisions. Then we discuss the role of Deep Learning in Medicine, also focusing on challenges and future directions. Finally, we will point out the attention on the role of Artificial Intelligence in fighting the COVID-19 pandemic, presenting an overview and the application of AI in the different phases of the pandemic.
Biography: Francesco Piccialli is currently Assistant Professor (tenure track) of Computer Science at the Department of Mathematics and Applications “R. Caccioppoli” (DMA) of the University of Naples Federico II (UNINA), Italy. In 2018 he took the Italian Scientific Habilitation for Associate Professorship. He received a Laurea Degree (BSc+MSc) in Computer Science and a PhD in Computational and Computer sciences from the Unviersity of Naples Federico II.
He is also research fellow at CINI (National Interuniversity Consortium for Informatics) from 2013. He is the founder and Scientific director of the M.O.D.A.L. research group that is engaged in cutting-edge on novel methodologies, applications and services in Data Science and Machine Learning fields and their emerging application domains.
He has been involved in research and development projects in the research areas of Internet of Things, Smart Environments, Data Science, Mobile Applications. He is author of many papers (100+) in international conferences and top-level journals (IEEE, ACM, Springer and Elsevier). Currently he serves in the editorial board of IEEE Trans. on Industrial Informatics (Associate Editor), IEEE IoT journal (Associate Editor), IEEE Access, FGCS (Future Generation Computer Systems, Elsevier), CAEE (Computers and Electrical Engineering, Elsevier), PAUC (Personal and Ubiquitous Computing, Springer), NCAA (Neural Computing and Applications, Springer), Information Fusion (Elsevier).