Dr. Luiz Otavio Vilas Boas Oliveira

I'm involved in all the process of building predictive models for investment risk in startups. The process involves: - Retrieving data from different sources, including scrapping data from the web (using selenium with Beautiful Soup). - Analysing the data, using Jupyter notebooks, pandas, matplotlib, dash. - Building Machine Learning models using Random Forest, GRU, SVM to fit our prediction problems. - Feature selection/engineering.

I am working on different projects with the LaIC (Computational Intelligence Laboratory) research group: - Reducing the exponential size of solutions generated by the Geometric Semantic Genetic Programming (GSGP) framework. - Analysing datasets used as benchmark for Genetic Programming (GP)-based methods under a Data Science perspective.

I worked on the development of autonomous tugs, capable of towing the aircraft in the airport ground, from the runway to the gate. Activities performed: 1) Surveyed current advances in autonomous vehicles and worked on optimization of ground routes in airports; 2) Worked in coordination with United Technologies; 3) Worked with Python (build a parser for XML airport maps) and Java/CPLEX (route optimization).

I worked with Geometric Semantic Genetic Programming (GSGP) on two main projects: 1) A study investigating aspects related to the semantic distribution of the functions employed by geometric semantic operators 2) Investigation of the impact of different instance selection techniques on GSGP and its robustness to noisy data. - Management of a research team (three researchers) - Development using Java, R (hypothesis tests and plotting)

I worked with Dr Gisele L. Pappa (UFMG) and Dr Fernando E. B. Otero (University of Kent) on Geometric Semantic Genetic Programming (GSGP): - Geometric Dispersion Operators - Sequential Symbolic Regression - Study of different geometric semantic operators for GSGP - GSGP implementation in JAVA