Vinicius Alves

Postdoctoral Research Associate (Cheminformatics and quantitative structure-activity relationships)

Chapel Hill, US

Cheminformatician and computational chemist with experience in the development and implementation of innovative cheminformatics and molecular modeling approaches; quantitative structure-activity relationships (QSAR) modeling using machine learning algorithms; management, curation, and analysis of complex chemical-biology data; application of predictive models in screening large libraries of virtual compounds for prioritizing hits to be tested experimentally. More recently, he has developed projects in health informatics, applying predictive modeling to identify relevant clinical features associated with patients' state of health. He was awarded with the 2018 Lush Prize Young Researcher Americas for his work on developing computational methods as an alternative to animal testing. His areas of interest are rare and neglected diseases, computational toxicology, computer-aided drug design, drug repurposing, health informatics, data science, and cheminformatics.

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