Xavier Vilasis-Cardona is full professor at the Engineering Dept. at la Salle, Universitat Ramon Llull. He leads the Smart Society research group, is member of the LHCb collaboration (CERN). He is also member of the IEEE Cellular Nonlinear Networks and Array Computing Technical Committee. He is director of the Master Universitario en Data Science. He is also member of the steering committee of the Associació Catalana d'Intel·ligència Artificial.

He has directed 10 PhD thesis, 10 competitively funded research projects, published more that 200 journal papers and contributed to more than 50 conferences. 

He actively participates in outreach activities and lectures. 

He has been Director for Doctoral Studies at La Salle, URL (2012-2022), Research coordinator at La Salle, URL (2003-2008), Coordinator of the Experiment Control System of the calorimeter of LHCb (2006-2020), Deputy Project Leader of the LHCb Calorimeter (2012-2014), and Chair of the IEEE Cellular Nonlinear Networks and Array Computing Technical Committee (2013-2015). Previously lead research groups are LIFAELS (Lab. d'Instrumentació per a Física d'Altes Energies La Salle - 2003-2014), GR-SETAD (Grup de Recerca en Sistemes Electrònics, de Telecomunicacions i Anàlisi de Dades - 2014-2017) and DS4DS (Data Science for the Digital Society - 2018-2023)

He has taught subjects in Advanced Math, Probability, Numerical Analysis, Calculus, Physics, Neural Networks, Control Theory, Optical Communications, Data Analysis and Advanced Statistics. He has been coordinator of the Postgrau en Web Analytics. 

He got a Physics Degree from Universitat de Barcelona in 1989 and a Physics PhD from Universitat de Barcelona. He is also PDG (Programa de Dirección General) by IESE. He has been FPI fellow from the Ministerio de Educacion y Ciencia (1990-1993), assistant professor at Universitat de Barcelona (1994), analyst at Aplicaciones en Informatica Avanzada (1994-1996) and from 1996 on he is at La Salle, Universitat Ramon Llull. 

His research interests and expertise are Particle Physics, HEP, Data Science, Data Analysis, Neural Networks, Machine Learning and Artificial Intelligence.