Educational background

I did my undergraduate studies at Escuela Tecnica Superior de Ingenieros de Telecomunicacion (ETSIT) de la Universidad Politecnica de Madrid and Ecole Nationale Superieure des Telecommunications de Paris (ENST). I studied the Double Diploma in Electrical and Computer Engineering co-sponsored by these two institutions and graduated in September 2005, after having specialised in Applied Mathematics and Artificial Intelligence.

I completed a Master of Research in Applied Mathematics for Computer Vision and Machine Learning from Ecole Normale Superieure de Cachan in France between September 2004 and September 2005.

I first arrived at the Center for Imaging Science - today part of the Institute for Computational Medicine - of the Johns Hopkins University in April 2005, where I worked on my Master's thesis under the supervision of Professors Donald Geman and Laurent Younes. In January 2006, I became a student of the Ph.D. program at the Applied Mathematics and Statistics Department.

Doctoral education

My main areas of study involve the domains of machine learning, pattern recognition and artificial intelligence, namely addressed from the perspective of statistical learning and information theory.  I am particularly interested in their applications in bioinformatics and computational biology.

As a part of my doctoral education at Hopkins, I have taken the following courses:

  • Graph Theory
  • Machine Learning
  • Statistical Methods in Imaging
  • Matrix Analysis and Linear Algebra
  • Topics in Bioinformatics
  • Statistical Theory I
  • Statistical Theory II
  • Statistical Pattern Recognition
  • Computational Functional Genomics
  • Probability Theory I
  • Eukaryotic Molecular Biology (audit)
  • Molecules and Cells (audit)
  • Systems Bioengineering III (audit)
  • Graphical Models
  • Information Extraction
  • Foundations of Optimization

During Spring Term 2012, I am working as a teaching assistant for the course 'Probability and Statistics for the Life Sciences'. In the past, I have also worked as a teaching assistant for the following courses:

  • Bioinformatics and Statistical Genetics
  • Scientific Computing
  • Probability and Statistics
  • Statistical Analysis II
  • Statistical Learning with Applications
  • Topics in Bioinformatics
  • Machine Learning
  • Graphical Models
  • Monte Carlo Simulation