Anacleto Silva de Souza

He holds a Bachelors degree in Physical and Biomolecular Sciences from the Institute of Physics of São Carlos (IFSC) at the University of São Paulo (USP, São Carlos-SP campus) (2012), a Masters degree in Sciences (Applied Physics program) from IFSC-USP (2015), and a Doctorate in Sciences (Physics program) from IFSC-USP (2019). His expertise includes data mining techniques (such as neural networks, decision trees, support vector machines, and Bayesian networks), multivariate analysis (including Principal Component Analysis and correlation analysis), and the development of simple and multiple linear regression models. He also specializes in the application of stochastic methods (Monte Carlo simulations via Markov Chains, MCMC - Gibbs Sampling, and the Metropolis-Hastings algorithm), statistical inference using both classical and Bayesian approaches, and experimental statistics. He develop deep learning models (convolutional neural networks, generative adversarial networks, multilayer perceptrons, transformer architeture, among others) in big data studies (protein databases, sequence databases and small-molecule databases). He has expertise in molecular dynamics studies, molecular docking, and high-throughput virtual screening in the design of drugs and vaccines. He is currently a FAPESP postdoctoral fellow, contributing to projects on drug and vaccine design against SARS-CoV-2 at the Institute of Biomedical Sciences (ICB) at the University of São Paulo (USP, capital campus). (Source: Lattes Curriculum)