Personal webpage of Marco Inácio

  • PhD in Statistics (University of São Paulo and UFSCar).
  • Bachelor in Economics (University of São Paulo).

Full CV:

Fast Python data science practical course:

Github profile: randommm.

Arxiv profile: dealmeidainacio_m_1.

LinkedIn: marcoinacio.

Apostila de Stan (Portuguese):

Curriculum Lattes: Portuguese English.

Published papers:

  • Distance assessment and analysis of high-dimensional samples using variational autoencoders, Information Sciences (Marco Inácio, Rafael Izbicki, Bálint Gyires-Tóth).
    DOI 10.1016/j.ins.2020.06.065.

  • The NN-Stacking: Feature weighted linear stacking through neural networks, Neurocomputing (Victor Coscrato, Marco Henrique de Almeida Inácio and Rafael Izbicki).
    DOI 10.1016/j.neucom.2020.02.073.

  • Bayesian superposition of pure-birth destructive cure processes for tumor latency, Communications in Statistics - Simulation and Computation (Josemar Rodrigues, Marco Henrique de Almeida Inácio, Adriano K. Suzuki, Fernando Raimundo da Silva and Narayanaswamy Balakrishnan).
    DOI 10.1080/03610918.2018.1538455.

  • Comparing two populations using Bayesian Fourier series density estimation, Communications in Statistics - Simulation and Computation (Marco Henrique de Almeida Inácio, Rafael Izbicki and Luis Ernesto Salasar).
    DOI 10.1080/03610918.2018.1484480.

Tutorials, software and stuff:

  • Introductory Python tutorial, focused specially on statisticians and machine learning:

  • Para baixar a apostila de introdução ao Stan ou demais materiais em português, veja:

  • Python package which implements a density comparison method (for two samples) and a Fourier series nonparametric density estimation method: npcompare.


  • Professional interests: Statistics and machine learning, specially artificial neural networks, variational inference, variational autoencoders, Markov chain Monte Carlo and Bayesian inference. Programming (specially Python, C++, and R) and Probability.

Contact information: click here to view.