Summary
Pablo Lago is a research engineer specializing in efficient deep learning and model compression, currently advancing quantization techniques for large language models at AMD. With an MPhil in Machine Learning from the University of Cambridge and dual B.Sc. degrees in Mathematics and Computer Science, he blends rigorous mathematical foundations with practical systems and algorithm engineering. Over seven years he has shipped compression and post-training quantization solutions for edge and server settings, including production-focused tooling for automated hyperparameter tuning and scalable data pipelines. He has hands-on HPC and attention-architecture experience from academic process-mining work and has presented at national conferences, signaling strong communication of research to applied teams. Based in Dublin, he brings a rare combination of theoretical depth and pragmatic implementation across research internships and industry roles.
7 years of coding experience
2 years of employment as a software developer
Bachillerato (Post-Compulsory Secondary Education), Science, Bachillerato (Post-Compulsory Secondary Education), Science at IES Plurilingüe Fontexería
Master of Philosophy - MPhil, Machine Learning and Machine Intelligence, Master of Philosophy - MPhil, Machine Learning and Machine Intelligence at University of Cambridge
UPC Universitat Politècnica de Catalunya
Double Bachelor's Degree in Mathematics and Computer Science, Mathematics and Computer Science, Double Bachelor's Degree in Mathematics and Computer Science, Mathematics and Computer Science at Universidad de Santiago de Compostela
Alumni Association (scholars) of the Barrie Foundation
Galician, Spanish, English, French