Foundations of Data Science
I am an Associate Research Scientist in the Applied Physics and Mathematics department at Columbia University. I have specialized in statistical machine learning, computational Bayesian statistics, approximate inference methods, and sequential decision processes.
My research focuses not only on the development of Bayesian probabilistic models and algorithms, but also on their application to a wide range of disciplines. I am currently working on descriptive, predictive, and prescriptive modeling with applications in science, engineering and healthcare.
I was a data-science postdoc at Columbia University with Prof. Chris Wiggins and Prof. Noémie Elhadad, I completed my Ph.D. in Electrical Engineering at Stony Brook University under the supervision of Prof. Petar M. Djurić, and previously obtained my degree in telecommunications engineering from the UPV/EHU Faculty of Engineering in Bilbao, Spain.