PhD in Computational Optimization
Do you want to do a PhD in computational optimization under my supervision, either at the Autonomous University of Barcelona (UAB) or at BarcelonaTech (UPC)?
There are several options for applying for funding:
You have the Spanish (or EU) nationality and/or you are a resident in Spain: in this case you are most probably eligible for applying for European fellowships, Spanish national fellowships, Catalan fellowships, or even UAB and UPC fellowships. For more information you may contact me.
The government of your home country has fellowships for doing the PhD abroad: this is the case, for example, in Brazil, Chile, and Mexico, among other countries. In this case you can apply for such a fellowship in your home country in order to come here to the UAB or to the UPC and do a PhD under my supervision.
In any case, during the application process you need an approval letter signed by me. Therefore, it is strongly advisable that you contact with me before starting with any application. When doing so, please, send a CV and, if possible, a recommendation letter.
My research lines are, broadly, in computation optimization. More specifically, with my current collaborators and PhD students I am working on aspects concerning the following two lines of research:
Swarm Intelligence is an artificial intelligence discipline whose goal is designing intelligent multi-agent systems by taking inspiration from the collective behavior of animal societies such as ant colonies, flocks of birds, or fish schools. Apart from techniques such as ant colony optimization, which is a metaheuristics inspired by the shortest-path-finding ability of natural ant colonies, I am also interested in discovering models of intelligent animal behaviors that have not yet been used in technical applications. A prominent example is our latest work on making use of the de-synchronization behavior found in Japanese tree frogs.
The hybridization of metaheuristics with exact approaches. Research in metaheuristics for combinatorial optimization problems has lately experienced a noteworthy shift towards the hybridization of metaheuristics with other techniques for optimization. At the same time, the focus of research has changed from being rather algorithm-oriented to being more problem-oriented. Nowadays the focus is on solving a problem at hand in the best way possible, rather than promoting a certain metaheuristic. This has led to an enormously fruitful cross-fertilization of different areas of optimization, algorithmics, mathematical modeling, operations research, statistics, simulation, and other fields. This cross-fertilization has resulted in some powerful hybrid algorithms that were obtained by combining components or concepts from different optimization techniques. In this context I am especially interested in developing new kinds of generally applicable hybrid algorithms.
I am fluent in English, Spanish and German. So, any of these three languages may be the working language. However, research articles and the thesis must be written in English.