My research interests cover recommender systems, information retrieval and machine learning. My main line of research consists in adapting information retrieval models to different recommendation tasks focusing on accuracy, diversity, novelty and scalability.
from September 2015 to present day
I received a competitive grant from the Spanish Government (Ministerio de Eduación). This fellowship funds the development of a PhD thesis during a maximum of four years. The criteria followed in the granting were the quality of the PhD project, the CV of the applicant and the work of his research group.
from May 2018 to August 2018
During this software engineering internship, I worked with the Meeting Room Intelligence team developing solutions to improve Google's meeting technologies.
from April 2017 to June 2017
I spent three months working at the Information Retrieval Group (IRG) under the supervision of Dr. Pablo Castells and Dr. Alejandro Bellogín. The IRG is part of the Autonomous University of Madrid. My stay was funded by a competitive grant from the Spanish Government ( Ministerio de Educación, Cultura y Deporte) for FPU fellows. I worked on studying the applicability of Information Retrieval evaluation etrics to Recommender Systems.
from April 2016 to June 2016
I spent three months working at the High Performance Computing Lab under the supervision of Dr. Raffaele Perego. The HPC Lab is part of the Istituto di Scienza e Tecnologie dell’Informazione “A. Faedo” (ISTI), the largest institute of the Consiglio Nazionale delle Ricerche (CNR) involved in ICT Research. My stay was funded by a competitive grant from the Spanish Government (Ministerio de Educación, Cultura y Deporte) for FPU fellows. I worked on applying Information Retrieval techniques to Recommender Systems.
from April 2015 to September 2015
I received a competitive grant from the Galician Government (Consellería de Educación). This fellowship funds the development of a PhD thesis during a maximum of three years. The criteria followed in the granting were the quality of the PhD project and the academic record.
from April 2014 to April 2015
I was hired by the IRLab as a researcher to work on distributed recommender systems for big data environments using MapReduce and NoSQL paradigms. I also focused on studying and improving accuracy, diversity and novelty of different approaches to recommendation.
from November 2013 to July 2014
This is a competitive grant from the Spanish Government (Ministerio de Educación) for outstanding students that are interested in pursuing an academic career in the last year of their degrees.
I developed a distributed recommender platform and implemented several collaborative filtering algorithms using Hadoop and Cassandra. I also worked on scalable web applications using Django, Lucene and caching technologies such as Memcached and Varnish.
from 2009 to 2014
This degree is structured as a five-year programme plus a final project (300 ECTS, BSc + MSc).
Mark: 9.32/10 (with honours)
A distributed recommender platform capable of making personalised recommendations using collaborative filtering techniques in a big data environment.
Mark: 10/10 (with honours)
This valedictorian distinction was given by the University of A Coruña to the students, one for each degree, with the best marks among all the graduates that finished their studies in 2014 at the University of A Coruña.
This valedictorian distinction was given by the Reginal Government of Galicia to the students, one for each degree, with the best marks among all the graduates that finished their studies in 2014 in the Galicia region.
This distinction was given by the Spanish Ministry of Education to those students with the best marks among all the graduates that finished their studies in 2014 in Spain.
Coursera - deeplearning.ai specialization on Deep Learning taught by Prof. Andrew Ng in 2017-2018.
Stanford Coursera specialization on Probabilistic Graphical Models taught by Dr. Daphne Koller in 2016-2017.
Stanford Lagunita course on MWriting in the Sciences taught by Dr. Kristin Sainani in 2015.
Stanford Coursera course on Mining of Massive Datasets taught by Dr. Jure Leskovec, Dr. Anand Rajaraman and Prof. Jeffrey Ullman in 2015.
2014 edition of the Machine Learning Summer School at Carnegie Mellon University (Pittsburgh, PA) organised by Prof. Alex Smola and Dr. Zico Kolter.
Stanford Lagunita course on Statistical Machine Learning taught by Prof. Trevor Hastie and Prof. Rob Tibshirani in 2014.
Caltech edX course on theoretical and applied Machine Learning taught by Prof. Yaser S. Abu-Mostafa in 2013.
Stanford Coursera courses on algorithm design and analysis taught by Dr. Tim Roughgarden in 2013.
Michigan Coursera course on model design taught by Prof. Scott E. Page in 2012.
Berkeley Coursera course on Quantum Computing taught by Prof. Umesh V. Vazirani in 2012.
Stanford Coursera course on Machine Learning foundations taught by Dr. Andrew Ng in 2012.
Udacity course on Artifical Intelligence foundations taught by Prof. Peter Norvig and Prof. Sebastian Thrun in 2011.
daniel [DOT] valcarce [AT] udc [DOT] es
+34 881 01 1276
Facultad de Informática
Campus de Elviña s/n
15071 A Coruña (Spain)