About Alberto / Sobre Alberto


Dr. Alberto Cascajo

 Alberto Cascajo is a post-doctoral researcher of Computer Science at the Universidad Carlos III de Madrid, which he joined in 2013. He obtained a B.Sc. in Computer Science (specializing in Computer Architecture and Software Engineering) in 2016, followed by an M.S. in Computer Science and Technology in 2017 and a PhD in Computer Science and Technology in 2021 under the direction of Prof. Jesús Carretero Pérez and David E. Singh. The PhD. topic was the development of a monitoring system capable of offering an overview of large distributed systems, as well as identifying applications that are running to do scheduling based on different criteria. In order to build an efficient system, the developed framework includes Machine Learning and Neural Network algorithms that compute the metrics and generate new interesting data (such as application model, performance prediction, application interference detection, etc.).

After several years of dealing with HPC issues, combined with simulators and scientific applications, I can confirm that my main interest is the application and improvement of HPC techniques. On the other hand, there is the BigData paradigm, which requires techniques that allow the handling and processing of huge volumes of data. The thought is that each of these two paradigms must be treated, from architectural points of view, in a different way, and each one requires a specific platform. Due to this reason, it may be possible to design a model capable of supporting both paradigms and, depending on the type of problem, the platform should be able to handle different algorithms and methods to obtain the best performance of both worlds.

As you can see, the search for performance, the power of the clusters and the importance that the Cloud has gained last years are my main topics, but I do not close the door to any research field:

  • HPC
  • Distributed and parallel systems
  • Scientific computation
  • BigData
  • Computer architecture