Axel Brando Guillaumes
About Axel Brando Guillaumes
Axel Brando Guillaumes is a Postdoctoral Research Engineer at the Barcelona Supercomputing Center, specializing in AI-based systems for safety-critical applications. He has extensive experience in data science and machine learning, having worked at institutions such as BBVA Data & Analytics and Universitat de Barcelona.
Current Role at Barcelona Supercomputing Center
Axel Brando Guillaumes serves as a Postdoctoral Research Engineer at the Barcelona Supercomputing Center. He has held this position since 2020, contributing to advanced research in computational technologies. His work focuses on developing AI-based systems that address safety-critical real-world problems, leveraging the center's high-performance computing resources to enhance research outcomes.
Previous Experience at BBVA Data & Analytics
Guillaumes worked as a Data Scientist Industrial Ph.D. at BBVA Data & Analytics from 2017 to 2022. His role involved applying deep learning techniques to address challenges in the banking sector. He completed his Industrial Ph.D. in collaboration with the University of Barcelona, focusing on the specific needs of the banking industry.
Educational Background in Artificial Intelligence
Guillaumes studied at multiple institutions, including Universitat Politècnica de Catalunya, Universitat de Barcelona, and Universitat Rovira i Virgili. He obtained a Master's degree in Artificial Intelligence from 2015 to 2017. His academic background also includes a Grado en Matemáticas and a Grado en Ingeniería Informática from Universitat de Barcelona, completed between 2009 and 2015.
Research and Development Experience
Prior to his current role, Guillaumes gained diverse research experience. He worked as a Machine Learning Research Developer at IIIA-CSIC for five months in 2017. Additionally, he held various positions at Universitat de Barcelona and DataScienceUB, including roles as an Undergraduate Researcher and Course Assistant, contributing to projects in data science and machine learning.
Specialization in Deep Learning and Uncertainty Modeling
Guillaumes specializes in uncertainty modeling using deep learning techniques. His research interests are centered on designing AI systems that can operate effectively in safety-critical environments. This specialization aligns with his broader goal of addressing real-world problems through advanced computational methods.