Carlos Vega

Received his Computer Science Ph.D. (2018, Excellent Cum Laude & Industrial Mention) at Universidad Autónoma de Madrid (U.A.M) researching high performance data analysis solutions for network traffic analysis as well as anomaly detection methodologies.

His Ph.D. thesis "Exploring the collection, analysis and visualisation processes of computer networks traffic" revolves around the new challenges affecting the ETL stages involved in the network traffic analysis, contributing on each stage, from the data collection to the data visualization through the intermediate processing and analysis processes.
He collaborated on different European research projects and continued his work as technical research staff for the projects Fed4Fire, EINS, TRÁFICA, and dReDBox among others.

Currently, he works for Naudit HPCN applying my research on projects with different enterprises. His current research topics include data analysis, log collection at high performance speeds and network traffic analysis for anomaly detection. He has also been a teaching assistant on different subjects at the E.P.S.