Pablo Arnau-González

Paisley, Scotland, United Kingdom · Pablo.ArnauGonzalez@uws.ac.uk

I am starting to get some experience in research. My main skills are machine learning, signal processing and emotional models of affect, but don't let that fool you I am just beginning to figure out things. For a more formal presentation, download my CV (last button).


Publilcations

Fusing highly dimensional energy and connectivity features to identify affective states from EEG signals

Arnau-González, P., Arevalillo-Herráez, M., Ramzan, N.
Neurocomputing, 2017

On the influence of affect in EEG-based subject identification

Arnau-González, P., Arevalillo-Herráez, M., Katsigiannis, S., Ramzan, N.
IEEE Transactions on Affective Computing, 2018

SOM-BASED CLass discovery for emotion detection based on DEAP dataset

Ayes, A., Arevalillo-Herráez, M., Arnau-González, P.,
Internationa Journal of Software Science and Computational Intelligence, 2018

Perceptual video quality evaluation by means of physiological signals

Arnau-González, P., Althobaiti, T., Katsigiannis, S., Ramzan, N.
Ninth International Conference in Quality of Multimedia Experience (QoMEX), 2017

Affective and Behavioral Assessment for Adaptive Intelligent Tutoring Systems

Marco-Giménez, L., Arevalillo-Herráez, M., Ferri, F.J., Moreno-Picot, S., Boticario, J., Santos, O.C,.... Arnau-González, P., Ramzan, N.
Conference on User Modeling, Adaptation, and Personalization (UMAP), 2016

A method to identify affect levels from EEG signals using two dimensional emotional models

Arnau-González, P., Ramzan, N., Arevalillo-Herráez, M.
The 30th European Simulation and Modelling Conference (ESM'16), 2017

Combining supervised and unsupervised learning to discover emotional classes

Arevalillo-Herráez, M., Ayesh, A., Santos, O.C, Arnau-González, P.
Conference on User Modeling, Adaptation, and Personalization (UMAP), 2017

ES1D: A deep network for EEG-based subject identification

Arnau-González, P., Katsigiannis, S., Arevalillo-Herráez, M., Tolson, D., Ramzan, N.
International Conference on Bioinformatics and Bioengineering (BIBE), 2017

Class discovery from semi-structured EEG data for affective computing and personalisation

Ayesh, A., Arevalillo-Herráez, M., Arnau-González, P.
International Conference on Cognitive Informatics & Cognitive Computing (ICCI* CC), 2017

Teaching

Data Mining and Visualization

Lab Assistant - University of the West of Scotland

Data Mining and Visualization techniques in R, ggplot2. Techniques include:Linear regression, common classifiers (SVM, Naive Bayes, k-NN), and dimensionality reduction.
Required module for Big Data MSc. 20 Hours - 2 ECTS

January 2019 - Present

Computing Systems

Lab Assistant - University of the West of Scotland

Introductory module to computing, includes a variety of topics, including: base conversion, introduction to assembly (x86), internet threats, image formats, and more.
Required module for Computing BSc. 20 Hours - 2 ECTS

January 2019 - Present

Programming with Objects C#

Lab Assistant - University of the West of Scotland

Introductory module to OOP.
20 Hours - 2 ECTS

January 2019 - Present

Programming with Objects C#

Lab Assistant - University of the West of Scotland

Introductory module to OOP.
30 Hours - 3 ECTS

September 2018 - December 2018

Mobile Networks and Smartphone Applications

Lab Assistant - University of the West of Scotland

Introductory module to Android (API 19) programming. Basic Knowledge of activities, permissions, localization and services
Optional module for Advanced Computing MSc. 20 Hours - 2 ECTS

September 2018 - December 2018

Computing Systems

Lab Assistant - University of the West of Scotland

Introductory module to computing, includes a variety of topics, including: base conversion, introduction to assembly (x86), internet threats, image formats, and more.
Required module for Computing BSc. 40 Hours - 4 ECTS

September 2018 - December 2018

Data Mining and Visualization

Lab Assistant - University of the West of Scotland

Data Mining and Visualization techniques in R, ggplot2. Techniques include:Linear regression, common classifiers (SVM, Naive Bayes, k-NN), and dimensionality reduction.
Required module for Big Data MSc. 20 Hours - 2 ECTS

January 2018 - May 2018

Computing Systems

Lab Assistant - University of the West of Scotland

Introductory module to computing, includes a variety of topics, including: base conversion, introduction to assembly (x86), internet threats, image formats, and more.
Required module for Computing BSc. 40 Hours - 4 ECTS

September 2017 - December 2017

Real Time Collision Detection

Lab Assistant - University of the West of Scotland

Introduction to collision detection algorithms and techniques, C++.
Required module for Big Data MSc. 20 Hours - 2 ECTS

January 2017 - May 2017

Education

University of the West of Scotland

PhD
EEG Machine learning applications: Affect detection, low-cost EEG-biometrics, and how the affect affects EEG-based biometrics (Provisional title)

Thesis writing in process

February 2018 - Present (Expected defense date April-June 2018)

University of the West of Scotland

MPhil
Emotion Recognition from EEG signals

Transfered to PhD program

February 2016 - January 2018

Universitat de València

BSc.(Hons) In Computer Engineering

GPA: 6.83

September 2011 - June 2015

Skills

Machine Learing and Data Analysis

Common classification algorithms (SVM, k-NN, LDA, ensemble methods)
Dimensionality reduction and data visualization: Isomap, t-SNE, Autoencoders
Identification of Over-fitted models and biased behaviors

Programming Languages and Frameworks

Matlab · Python · R · Java · C/C++ · Android · Tensorflow · Machine Learning Toolbox

Additional skills

Signal Processing · Regular Expressions · Web scrapping · Aldebaran Robotics

Interests

I have special interest in affective computing, specially in emotion recognition, and its applications. I have a personal dream of being able to implement emotion recognition to Intelligent tutoring systems, for childrean with special learning requirements. Deep architectures are truly fascinating! The way they learn underlying representations of the data provided for recognition. I think people don't give enough attention to one-dimensional networks and its just not fair. I'm pretty sure 1D-CNN are capable of discovering new great features that will boost the accuracy of some signal processing open problems, like fall detection!

Knowledge should be free! I'm pretty sure you can find all my papers in certain SCIentific Hub, somewhere in Kazakhstan. But that is illegal, don't do it! Enough about work! I love music, netflix, and video-games.


Awards

  • UWS Annual Learning, Teaching & Research Conference 2018 - Research Output Prize 2018
  • Elsevier, "Computers in Biology and Medicine" - Certificate of Outstanding Contribution in Reviewing 2018
  • Elsevier, "Signal Processing: Image Communication" - Certificate of Outstanding Contribution in Reviewing 2017
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