Fall 2018 - Present
Software Engineer in Research - Google
I am currently part of the Google Brain team in Zurich. I am broadly interested in ways of making a better/smarter use of current data and models for new tasks. I am particularly fond of generative models and unsupervised/semi-supervised learning.
Summer/Fall 2017
Software Engineer Intern - Google
I interned at Google Research, working with the Video Content Analysis team. I applied deep learning to content-based video recommendation, in order to improve the recommendation of recently uploaded videos, aiming to solve the "fresh start" problem present in traditional recommendation systems.
Summer/Fall 2015
Software Engineer Intern - Google
Working with the StreetSmart team at Google Geo, we significantly improved the models for business change detection from Street View imagery, based on Convolutional and LSTM neural networks. This allows to keep the listings of businesses in Google Maps fresh at a lower cost.
Summer 2014
Computer Vision Engineer - Blinkfire Analytics
Worked on the backend system for brand logo detection on millions of images from social networks. Designed system to use multiple classification models, and improved the speed and the accuracy of the models. Blinkfire Analytics uses computer vision to measure impact on social media providing reports to sport teams, players, agents and sponsors.
Summer 2013
Software Engineer Intern - Google
Working at Google Research with the OCR team, I developed a framework for synthetic training data generation for many OCR applications. We used the framework to improve the training for Google Books, and trained state-of-the-art models for Ads OCR and on-the-wild OCR, using only synthetic data.
Summer 2012
Software Engineer Intern - Google
I joined the OCR team at Google Research to developed one of the first systems for feature extraction, based on deep learning. Thanks to this work, the character error rate was reduced significantly across more than 40 languages for Google Books.


2013 - 2018
Ph.D. - Universitat Politècnica de València
I did a Ph.D. at the Pattern Recognition and Human Language Technology Research Center. The main result of my PhD was "A Probabilistic Formulation of Keyword Spotting", but I also worked on general handwritten text recognition.
2012 - 2014
Master's degree - Universitat Politècnica de València
Master in Artificial Intelligence, Pattern Recognition and Digital Imaging working on keyword spotting for historical handwritten text documents. Thesis: "Out of Vocabulary Queries for Graph-based Keyword Spotting".
2007 - 2012
Engineer's degree - Universitat Politècnica de València
Engineering degree in Computer Science, focusing on Formal Languages and Artificial Intelligence. I spent one year at the Royal Institute of Technology (KTH), in Sweden doing Machine Learning and Distributed Systems courses.