prlz77

An information compressor in a pale blue dot.

Pau Rodríguez López

PhD researcher on AI and Computer Vision.

Studies


2015 - present

PhD researcher


Computer Vision Center, Universitat Autònoma de Barcelona
On bio-inspired machine learning techniques applied to computer vision and social media.
2014 - 2015

Advanced master of Artificial Intelligence


KU Leuven
Magna Cum Laude. Topics: Artificial Neural Networks, Machine learning, SVM, Data Mining, Cybernetics and more.
2009 - 2014

Computer Engineering (5 years)


Universitat Autònoma de Barcelona
With honors. Topics: Artificial Intelligence, Networks, HPC and more.

Work Experience


May 2014 - Aug. 2014

Research Assistant


Visual Tagging Services, Computer Vision Center, Universitat Autònoma de Barcelona.
Developing learning algorithms for image classification.
Oct 2013 - May 2014

Research Assistant


Universitat Autònoma de Barcelona
Engineering on large scale image classification and retrieval with deep learning techniques.
Jun. 2013 - Oct. 2013

Member of the Chalearn Organization Committee


Computer Vision Center, Universitat Autònoma de Barcelona
Research assistant, organizing the human gesture databases used in the ChaLearn Multimodal Gesture Recognition Challenge 2013, and in the ChaLearn Looking at People 2014 @gesture.chalearn.org, co-organized by CVC, UAB, UB, UOC, Coplinet (California) and Microsoft.
Sep. 2012

Research Assistant


Department of Information and Communications Engineering, Universitat Autònoma de Barcelona.
Extending proposal of standard for the Consultative Commitee for Space Data Systems for the Group on Interactive Coding of Images. Working over an implementation based on the Nasa’s CSSDS-122 Public Release Version.

Projects


Jun. 2015

MASTER THESIS - Reducing Redundancy in Convolutional Neural Networks


STADIUS, KU Leuven
Director: Prof. Bart de Moor / Supervisor: Peter Roelants
Successfuly reduced the redundancy of CNNs by prunning redundant filters.
Jun. 2014

DEGREE THESIS - A Big Data approximation with deep neural networks


Computer Science department, Universitat Autònoma de Barcelona
Director: Jordi Gonzàlez Sabaté / Supervisor: Pep Gonfaus
Designed and deployed a deep learning system for big data applications.

Awards and merits


2017

Google Summer of Code


tiny-dnn - OpenCV
Include recurrent neural networks in the tiny-dnn framework.
2016

FI Doctoral scholarship


Government of Catalonia
Government fundings for the PhD studies.
2015

PIF Doctoral scholarship


Universitat Autònoma de Barcelona
Waived.
2015

First-of-class honours


Universitat Autònoma de Barcelona
Distinction for the best grade in the class.
2014

Kaggle Galaxy Zoo


kaggle.com
15th out of +300, signed as prlz77.
May 2014 - Aug. 2014

Santander Grants for SME Internships


Santander Bank
For an internship in Visual Tagging Services.
May 2014

Scholarship for collaboration in a University department.


Spanish Ministry of Education

Teaching and Seminars


2016-2017

Machine Learning seminars (Computer Engineering)


Engineering school, UAB
2015-2016

Programming methodology labs (Computer Engineering)


Engineering school, UAB
Oct. 14th 2015

Deep learning 101


Vall d'Hebron Research Institute (VHIR), Barcelona

Other courses


2014

Machine Learning


Coursera - Standford, Andrew NG.

Reviewing


Journals TPAMI2017, PR(SI-AMDO)2017
Conferences NIPS2016

Publications


  1. Rodrı́guez Pau, Gonzàlez, J., Cucurull, G., Gonfaus, J. M., & Roca, X. (2017). Regularizing CNNs with Locally Constrained Decorrelations. In Proceedings of the International Conference on Learning Representations (ICLR).
  2. Bellantonio, M., Haque, M. A., Rodriguez, P., Nasrollahi, K., Telve, T., Escarela, S., … Anbarjafari, G. (2016). Spatio-Temporal Pain Recognition in CNN-based Super-Resolved Facial Images. In International Conference on Pattern Recognition (icpr). Springer.
  3. Rodrı́guez Pau, Cucurull, G., Gonfaus, J. M., Roca, F. X., & Gonzàlez, J. (2017). Age and Gender Recognition in the Wild with Deep Attention. Pattern Recognition.
  4. Rodriguez, P., Cucurull, G., Gonzàlez, J., Gonfaus, J. M., Nasrollahi, K., Moeslund, T. B., & Roca, F. X. (2017). Deep Pain: Exploiting Long Short-Term Memory Networks for Facial Expression Classification. IEEE Transactions on Cybernetics.