Juan J. Merelo
(University of Granada)
JJ Merelo obtained a degree in Theoretical Physics in 1988 and a PhD in Physics in 1994, both at the university of Granada. Since 1988 he has also been teaching at this university, lately (since 2009) as professor. He started to be interested in evolutionary algorithms and artificial life in 1993, and since then he's published more than 300 papers on the subject. He's also led the SIGEvo summer school in two occasions, 2018 and 2019.
He's a strong supporter of open source software and open science, developing most of his work openly using GitHub. He's also been a software developer since 1983, and never stopped since, integrating lately in the Perl 6 developing team, mainly in charge of documentation. He teaches cloud computing in the university, and has been in the Technical Advisory Committee of Microsoft related to cloud services and SDK.
From computer science and engineering to AI:
cloud native artificial intelligence and artificial life.
The main theme of this course is how cloud computing is changing the paradigm of software development to a codesign of software and systems (devops) and also to several other trends, like serverless computing, concurrency and software as a system. This has led to the mainstreaming of artificial intelligence (as a service), but also to the creation of systems whose very nature is stochastic, leading to version of traditional metaheuristics that can't rely on static, never-changing deployments. We will explain in this course how to tap these resources, and how to redesign traditional metaheuristics, specially evolutionary algorithms, to take advantage of them.
Helder Coelho (University of Lisbon)
Other lectures (confirmed):
Luc Steels (Catalan Institute for Advanced Studies (ICREA)) |
Matteo Valleriani (Max Planck Institute for the History of Science) |
Jochen Büttner (Max Planck Institute for the History of Science) |
Nuno Sousa (University of Minho) |
Paulo Gomes (Critical Software) |
Tony Veale (University College Dublin)