Dr. María Loreto Muñoz-Venegas is a Genetic Epidemiologist and Data Scientist specializing in bioinformatics, statistical genetics, and machine learning applied to complex disease research. She holds a PhD in Genetic Epidemiology from the University of Groningen (Netherlands, 2016), an MSc in Applied Data Science from the University of Canterbury (New Zealand, 2024), and an MSc in Clinical Epidemiology from Universidad de la Frontera (Chile, 2011). Her academic foundation was established with a BSc in Cellular and Molecular Biology from the University of Stellenbosch (South Africa).
With over a decade of research experience at world-class institutions, Dr. Muñoz-Venegas has held postdoctoral fellowships at NEUROMED I.R.C.C.S. (Italy), the Institute for Cardiogenetics at the University of Lübeck (Germany), and the University Medical Centre Groningen (Netherlands). Her research integrates multi-omic data (genomic and epigenomic) to elucidate the mechanisms underlying complex traits, with a primary focus on cardiovascular health and biological aging. She utilizes advanced statistical modeling, polygenic risk scores (PRS), methylation profiles, and machine learning to dissect intricate gene-environment interactions.
Her work has been published in prestigious journals, including Nature Genetics, Nature Communications, and Scientific Reports, and she has authored a book chapter on the genetics of coronary heart disease. An active collaborator within several international consortia, she is a registered Scientific Researcher Epidemiologist (SWMBO) and a member of the Chilean Society of Epidemiology (SOCHEPI). Currently, at BrainLat, she leverages her multidisciplinary expertise to bridge neurological and cardiovascular health through innovative data science.
