I'm a Ph.D. student in Industrial Engineering at Purdue University, advised by Prof. Mario Ventresca.
My research interests are broadly in advancing the field of machine learning, especially in the ability of current methods to generalize for instances that escape the distribution over the training datasets, with main applications to structured data (such as graphs and images). I have also research projects on equitable scheduling and social network analysis.
Before coming to Purdue, I got my Bachelors in Laws and B.A. in Economics from the Universidade de Brasilia, in Brazil.
Email contact: lmori (at) purdue (dot) edu
Latest Updates
| June 2022 | Our paper "Examining Supervised Machine Learning Methods for Integer Link Weight Prediction Using Node Metadata" was published in the Entropy Journal (selected as a featured article). [Link] [Full text] |
| Dec. 2021 | We will present our paper "Supervised Link Weight Prediction Using Node Metadata" at the Complex Networks and their Applications Conference. [Link] |