Keynote Speakers

Prof. Antonio Bahamonde

University of Oviedo, Spain

Antonio Bahamonde Biography:

Antonio Bahamonde received MSc and PhD degrees in Mathematics from the University of Santiago de Compostela, Spain, in 1979 and 1982 respectively. He is currently a Full Professor of Artificial Intelligence at the University of Oviedo at Gijón, Spain. Prof. Bahamonde has been Visiting Professor in the University of Massachusetts (Amherst, MA) and Cornell (Ithaca, NY). He is Director of the Artificial Intelligence Center of his University, and has presided the Spanish Association for Artificial Intelligence (AEPIA) between 2007 and 2013. His research interests include Machine Learning applications in livestock, sensory analysis, and genetics.





Applications of Machine Learning algorithms for Embeddings in Euclidean Spaces


Recently, embeddings have been used in a number of interesting applications. The idea is to learn from a dataset some matrices that can be seen as embeddings in an Euclidean space. One of such applications is understanding and modeling human preferences. It is one of the key problems in applications ranging from marketing to automated recommendation. In this talk, we focus on learning and analyzing their preferences of consumers regarding food products. In particular, we present machine learning methods that embed consumers and products in a common space such that their relationship to each other models the stated consumer preferences. In addition to predicting preferences that were not explicitly stated, the embedding enables visualization and clustering to understand the overall structure of a population of consumers and their preferences regarding the set of products. Additionally, we introduce another application for peer assessments in MOOCs (Massive Open Online Courses).


Prof. Davide Balzarotti

Eurecom Graduate School and Research Center

Davide Balzarotti Biography:

Davide Balzarotti is an Assistant Professor at the Eurecom Graduate School and Research Center, located in Sophia Antipolis on the French riviera. His research interests include most aspects of system security and in particular the areas of binary and malware analysis, reverse engineering, computer forensics, and web security and he is also part of the International Security Lab .





Large scale data analysis for system security


Certain phenoma do not manifest themselves on a small scale. For example, if you check the spam messages received by a single company you may not notice any pattern. But by looking at millions of spam messages collected worldwide, some structure can suddenly emerge and it may become possible to recognize spam campaigns, and even the infrastructure responsible for sending them. The same concept applies to many other security areas, from botnet detection to malware analysis, from web-based infection to network intrusion detection systems. In this talk, I will present some of the advantages of performing large scale analysis in the area of system security. In particular, I will describe several case studies, using results we obtained in the areas of embedded systems, online scam analysis, user risk profiling, and botnet detection as main running examples.