Summary
Iñigo Urteaga is a tenure-tracked Ramón y Cajal & Ikerbasque Research Fellow at BCAM specializing in statistical machine learning, computational Bayesian methods, approximate inference, and sequential decision processes. With a PhD in Electrical Engineering from Stony Brook and nine years of research experience spanning Columbia University and European research centers, he blends theoretical rigor with applied modeling for electronic health records and real-world systems. His work spans descriptive, predictive, and prescriptive modeling, with a strong background in Monte Carlo methods, time series, and nonparametric Bayesian statistics. Notably, he has transitioned successfully between applied engineering projects (from delay-tolerant networks to sensor networks) and cutting-edge ML research, demonstrating a rare fluency across systems, algorithms, and domain-driven data science. Based in Bilbao, he combines international academic experience with grant-funded leadership (LaCaixa Junior Leader-Incoming award) to drive impactful, computation-first research.
9 years of coding experience
15 years of employment as a software developer
MS Telecommunication Engineering, MS Telecommunication Engineering at EHU
Master's degree Wireless Sensor Networks, Master's degree Wireless Sensor Networks at Colorado School of Mines
Doctor of Philosophy (PhD) Electrical Engineering, Doctor of Philosophy (PhD) Electrical Engineering at Stony Brook University
Basque, Spanish, English, French