Milton is an Assistant Professor and PI of the Pividori Lab in the Department of Biomedical Informatics and the Center for Health Artificial Intelligence (AI) at the University of Colorado Anschutz Medical Campus.
His lab aims to design the next generation of computational methods that consolidate large and heterogeneous sources of biomedical data to extract biological insights to ultimately improve human health. Our research approach uses the latest developments in machine learning for knowledge discovery to increasingly incorporate the emergent complexity present in biological systems. A core mission of the lab is to provide these technological advances through open-source software and data resources to enable reproducible and transparent research conducted by a diverse team of researchers.
Before starting the Pividori Lab, Milton earned a B.S. in Information Systems Engineering from Universidad Tecnológica Nacional, Argentina, in 2010. In 2016, he received his Ph.D. in Bioinformatics from the same institution and the Research Institute for Signals, Systems and Computational Intelligence at Universidad Nacional del Litoral, Argentina. He started as a postdoctoral scholar in the Department of Medicine at the University of Chicago where he worked on advanced statistical methods to study the phenome-wide consequences of gene regulation and the genetic heterogeneity of asthma. He continued his postdoctoral training in the Department of Genetics at the University of Pennsylvania where he developed computational methods to integrate multi-omics datasets and extract complex, nonlinear patterns from transcriptomic data. In 2022, he was awarded a K99/R00 grant (K99HG011898) from the National Human Genome Research Institute to develop computational approaches to improve risk stratification in complex disease phenotypes (R00HG011898).
Search for Milton Pividori's papers on the Research page