Javier Rasero

I am physicist and data scientist interested in obtaining the maximum amount of information from the brain. My research focuses on developing and applying new pipelines and methodologies for the efficient integration of multimodal brain data to predict and explain individual differences in healthy and neuropathological populations.

My previous research experience includes postdoctoral years at the University of Bari (Italy) and the Biobizkaia Health Research Institute (Spain), where I developed and applied machine learning methods for the study of brain disorders using connectivity data. I followed this with a postdoctoral position in the CoAx Lab at Carnegie Mellon University (Pittsburgh), contributing to the growth of the Health Neuroscience field by building predictive models of cardiovascular disease risk factors from neuroimaging data.

I am enthusiastic about building methodological pipelines that can be translated into clinical settings. Indeed, I have contributed to this in Neuroscience and other fields such as melanoma cancer. Additionally, I advocate for the open-source philosophy and have developed several freely available libraries and toolboxes for working with brain data.