Can random forests tackle missing data using clever imputation for reliable predictions in practical applications?
Irving Gomez Mendez
Irving Gomez Mendez is a postdoctoral researcher at the Laboratory of Strategic Analytics Networks with Machine Learning and AI (SAI) within the Data Science and Analytics Research Group (DSARG) at the National Electronics and Computer Technology Center in Thailand. Furthermore, he has been working as a lecturer at the Ibero-American University in Mexico since 2021. He holds a PhD in Probability and Statistics from the Centre for Research in Mathematics (CIMAT), with the thesis entitled 'Random Forests and Autoencoders with Missing Data'. Between January and March 2020, he undertook a research visit at Inria-Lille, focusing on variational autoencoders with missing data.