Data imputation in biological sequences with Machine Learning
Final project (10/10): Machine Learning techniques to impute missing data in biological sequences, with an automated bioinformatics pipeline in Python.
Computer Engineer
Software solutions for the financial sector, with a strong foundation in artificial intelligence and high-performance computing.
About
Computer Engineer focused on software development and data solutions. I work as a technology consultant in the financial sector, designing and building software solutions powered by Artificial Intelligence. Working in banking gives me a business perspective that complements my technical profile, without claiming to be a domain expert. My technical focus is artificial intelligence (machine learning, deep learning, NLP) and high-performance computing in C/C++ with MPI, OpenMP, CUDA and OpenCL.
Stack
OpenCL
OpenMP
MPI Experience
BBVA · via Nfq Advisory, Solutions, Outsourcing
Nfq Advisory, Solutions, Outsourcing
University of Extremadura · ARCO Research Group
Education
National Distance Education University (UNED)
University of Extremadura
Final project (Grade: 10/10): Machine Learning for imputation of missing data in biological sequences.
University of Extremadura
University of Extremadura
University of Extremadura
Projects
Final project (10/10): Machine Learning techniques to impute missing data in biological sequences, with an automated bioinformatics pipeline in Python.