He obtained his PhD in Applied Maths from Polytechnique Montréeal in 2009 and he has been assistant professor at Universidade Federal do Rio Grande do Norte, Brazil, in 2009-2016. His research interests include data mining, optimization, mathematical programming and how these disciplines interact to tackle problems in the Big Data era. Daniel has published in leading operations research and data mining journals including Machine Learning, Pattern Recognition, European Journal of Operational Research, Mathematical Programming and Journal of Global Optimization.