About

Julián Candia is Staff Scientist at the Longitudinal Studies Section of the Translational Gerontology Branch at the National Institute on Aging, NIH in Baltimore, MD. He works in collaboration with basic, translational, and clinical research scientists to develop quantitative methods of data analysis to better leverage the potential of new technologies in the biomedical realm.
 In this context, his expertise at the crossroads of data science, biostatistics, machine learning, network science, and bioinformatics is applied to contribute innovative ideas to key problems in systems biology, with special emphasis in aging.

Dr. Candia obtained his Licenciado (1999) and Ph.D. in Physics (2004) degrees from the University of La Plata (Argentina). He earned the 2000 “Dr. Joaquín V. González” award for highest GPA. In subsequent years, he worked on a variety of problems involving computational and mathematical modeling of far-from-equilibrium dynamical systems, as well as on data mining and machine learning. In 2009-2011, he worked for the electronic health record software company Epic Systems. In 2011-2014, he worked at the University of Maryland with a joint appointment between the Department of Physics (Losert lab) and the School of Medicine (Civin lab), where he was a recipient of an NIH T32 Cancer Biology Training Grant. Since 2014, he works as Staff Scientist at the National Institutes of Health.

He authored over 110 original research peer-reviewed articles in top scientific journals (including Cell, Immunity, Nature Comm, Science Adv, J Hepatol, J Clin Invest, Biomaterials, Aging Cell, eLife, Sci Rep, PLOS Comp Biol, BMC Bioinformatics, Phys Rev Lett) and 3 book chapters. For his full list of refereed publications (with PDFs available for download), visit https://juliancandia.github.io

Google Scholar Citation-
https://scholar.google.com/citations?user=FMGdZqcAAAAJ&hl=en&oi=ao

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Publications (97)