Daniel Molina
As many people, I have several roles:
As a computer science that love programming, I am interested in programming in different languages (like C++, Java, ....), and I particularly love Python, and another interesting growing programming languages (like Rust or Julia). I define myself also as a Linux user, this is the only OS in my computers for more than 15 years. Also, I am a believer in Free Software (actually, I was for years the secretary of Free Software Office at the University of Cadiz). I usually give talks in PyData in my country, and I also I have participated in several JuliaCon conferences.
Since a professional side, I am Assistant Professor at the University of Granada, Spain, in Computer Science. I research in Artificial Intelligence using Metaheuristics for optimization (I have won two international competitions) and also in Neuroevolution, combining Metaheuristics with Deep Learning, with an index-h of 31, and be member of the 2% most influencer researcher in Stanford's list. I have directed two thesis. I have participated in several research projects involving Machine Learning. i am currently co-leading a General Purpose Artificial Intelligence project, a €120K Knowledge Generation Project, funded by the Ministry of Science, Innovation and Universities of Spain.
Sessions
Julia is a high-performance language for technical computing that offers advantages like type stability, just-in-time compilation, and extensive parallel computing support. Its Machine Learning ecosystem, although having fewer options, is functional and includes packages like DataFrames.jl, Flux.jl, MLJ.jl, and SciML for various ML tasks. Additional tools cover data visualization, R compatibility, and specific ML applications. The ecosystem is comprehensive and can meet many ML researcher/professional needs. This talk provides an overview of the ecosystem, discussing both its strengths and potential areas for improvement.