Javier Dehesa

Machine learning researcher in applications of deep learning to video games and other interactive digital experiences.

C++ developer in automotive navigation solutions. Implementation of customer requirements and standard specifications (NDS). Work in agile teams in a continuous integration environment. Quality assurance through requirements analysis and use case definition and testing.

Collaboration in the topic of complex networks and graph mining. Design and analysis of graph structures from public healthcare records towards the detection of comorbidity patterns.

Design and development of integrated home server systems. Involvement on all of the major technical aspects of the software, from higher level design to C++ and Python programming and system configuration.

Implementation of an auto-tuning association rules learning algorithm based on the measure of confidence boost into the KNIME platform. Work funded by the Harvest Programme of the Pascal-2 Network of Excellence.

Collaboration in the research of genetic programming algorithms, leading to a co-authorship in the paper "​Penalty Functions for Genetic Programming Algorithms".

Development and maintenance of the corporate web portal and other internal webs using the .NET framework. Involvement in both database, backend and frontend development.

Thesis: "A Novel Neural Network Architecture with Applications to 3D Animation and Interaction in Virtual Reality". Applications of deep learning to video games animation and interaction. Research conducted in collaboration with video games studio Ninja Theory.

Taught postgraduate programme with a strong theoretical component on data analysis and intelligent systems. Covered topics include data mining, neural networks, Bayesian networks, genetic algorithms and support vector machines.

Five-year undergraduate programme (plus one extra year for the research project) of foundations of computer science, including software design, database design, networking, computer architecture, concurrency and parallelism, data mining and artificial intelligence.