Experience

Forsberg Services Ltd.

• Software Engineer

  • Mar 2016 - Present

  I am currently working on a navigation system based on computer vision techniques. I am currently working on a navigation system based on computer vision techniques.



The University of Manchester

• United Kingdom
• Higher Education
• 700 & Above Employee

• Post-doctoral research associate

  • Jun 2015 - Feb 2016

  I am currently working on the project: "Using mobile phone technology in the assessment of Raynaud’s phenomenon; a potential outcome measure for clinical trials?" funded by Arthritis Research UK. I am in charge of: • Programming a mobile app to monitor Raynaud's phenomenon (RP) attacks. • Developing computer vision methods to analyse the images of hands showing the effect of an RP attack. I am currently working on the project: "Using mobile phone technology in the assessment of Raynaud’s phenomenon; a potential outcome measure for clinical trials?" funded by Arthritis Research UK. I am in charge of: • Programming a mobile app to monitor Raynaud's phenomenon (RP) attacks. • Developing computer vision methods to analyse the images of hands showing the effect of an RP attack.



University of Central Lancashire

• United Kingdom
• Higher Education
• 700 & Above Employee

• Research Associate

  • May 2014 - May 2015

  My position was research associate in the area of Computer Vision and Pattern Recognition within the FP7 SEMEOTICONS project.I was in charge of the system that controls the access to the mirror-like computer and the analysis of iris images. In more detail:• I developed an automatic face recognition system which controls the access to the different functionalities of the mirror-like system. This software was programmed in C++.• I studied the suitability of analysing iris images to detect abnormal cholesterol levels. This study was performed with software developed in Matlab and C++.



Universitat Jaume I de Castellón

• Translation and Localization
• 1 - 100 Employee

• PhD Candidate

  • May 2010 - Apr 2014

  Title: Face Gender Classification under Realistic Conditions. Dealing with Neutral, Expressive and Partially Occluded Faces. Abstract: This thesis is focused on face gender classification under more realistic scenarios than those traditionally considered in the literature. In real environments, many problems can arise dueto the lack of control over the subjects and their surroundings. Moreover, the individuals’ characteristics, such as age or race, can significantly vary. At the same time, the subjectscan express their emotions by means of facial expressions as well as wear pieces of clothingcovering their faces both of which would result in face images with distortions. These arethe main problems that we tackle in this thesis together with some other complicationsrelated to having different illumination conditions and inaccurate face detections.Supervisors: Dr. Pedro García-Sevilla and Dr. Ramón A. Mollineda

• Research Assistant

  • May 2009 - Apr 2010

  Proyecto: Metodologías avanzadas en observación de la Tierra: calibración de datos ópticos yextracción de la información (EODIX)

• Research Assistant

  • Aug 2007 - Apr 2009

  Proyecto: Diseño e integración de técnicas de reconocimiento de formas para control de calidadmediante visión artificial y análisis de imágenes (DIRFAI)



The Ohio State University

• United States
• Higher Education
• 700 & Above Employee

• Visiting Scholar

  • Sep 2011 - Feb 2012

  Worked on the Dynamics of Facial Expressions of Emotion in the Computational Biology and Cognitive Science Lab under the supervision of Dr. Aleix M. Martinez. Worked on the Dynamics of Facial Expressions of Emotion in the Computational Biology and Cognitive Science Lab under the supervision of Dr. Aleix M. Martinez.



University of Bristol

• United Kingdom
• Higher Education
• 700 & Above Employee

• Visiting Researcher

  • Jun 2010 - Sep 2010

  Worked on Gender Recognition using Static Images of Faces in the Computer Vision Group under the supervision of Dr. Neil Campbell. Worked on Gender Recognition using Static Images of Faces in the Computer Vision Group under the supervision of Dr. Neil Campbell.