I work at the Data System Laboratory of the School of Engineering and Applied Sciences.
I research on designing techniques to accelerate ensembles of deep learning models’ training and discovering strategies to reduce computations and increase generalization during the inference of those ensembles. Futhermore, I am carrying and empirical study on the importance of deep residual architectures compared with ensembles of shallower networks.
Master's Degree in Visual Analytics and Big Data
The Master's Degree in Visual Analytics and Big Data is focused on current techniques regarding Big Data phenomenon, dividing resources into:
◆ Distributed Computing Architecture ◆ Artificial Intelligence ◆ Business Intelligence ◆ Visual Analytics ◆ Statistical Learning ◆ Client analysis and strategic marketing
Master's Degree in Chemical Engineering
Chemical engineering is directly related to the obtaining of products that guarantee our quality of life, such as fuels, solvents, medicines, paints, plastics, detergents, fertilizers and paper. Without them, society as we now know it would be impossible. The global demand for these products generated by the chemical industry is continuously growing, as is the demand for experts in this sector: the aim of the master's degree in Chemical Engineering is to train students for these professions.
6 months exchange to research in the department of Material Science.
My responsabilities were the development of mathematical model-based reactor simulator of the polimerization process of PMMA.
I did research on state-of-the-art techniques for free radical initiated polymerization techniques, modeling the mechanisim of symetrical, cyclic, multifunctional initiators.
The objective of my thesis was the simulation of the evolution of molecular weight distribution and the mono and di-radicals distribution over the reaction time.