Specialist in Operations Research (OR) and Machine Learning (ML) since 2016.Currently, I am working as a researcher on subjects of OR and ML at Dell Technologies.My academic background also relates to OR and ML topics (including overlapping/hybridized ones!).On these topics, I am interested in using ML techniques to improve the performances of OR solvers. Conversely, I am also interested in using OR techniques for mitigating ML training time.Some topics that I have an interest in include vehicle routing problems, minimum latency problems, graph neural networks, and hard-margin SVM.I could cite a few keywords (to facilitate Linkedin indexing) that are related to these topics, such as genetic algorithms, GRASP, metaheuristics, Mixed-Integer Programming tools, Benders Decomposition, CPLEX, JuMP, and NP-hard problems.More about my academic trajectory:As a doctorate student, I could also participate as a research intern at Polytechnique Montréal and a teaching assistant on undergraduate and graduate courses at PUC-Rio. The doctorate thesis resulted in three papers, two currently under peer review. We can check them on my Google Scholar page: https://scholar.google.com/citations?user=G3xq-skAAAAJ&hl=enMy academic background also includes a Master's degree in Operations Research and Machine Learning areas at Fluminense Federal University, and a Bachelor's in Computer Science at Tocantins Federal University, for which I was granted a 15-month study abroad program at the University of Western Australia (UWA).Since my undergraduate course, I have focused my studies on Artificial Intelligence topics, such as pattern mining. During my Master's and doctorate research, I have employed pattern mining techniques in Operations Research to make Mixed-Integer Programming tools and Metaheuristics solution algorithms more efficient. Beyond that, I have been working on side Data Science projects related to clustering and classification tasks, including projects involving Spark and NLP.Given my background, I have been working on the following: C/C++, CPLEX, Python (including Pandas, Numpy, PySpark, Pyomo, scikit-learn, NLTK, spaCy, and Seaborn), Julia (including JuMP), and Git.Reasonable experience with the following technologies:Unix/Linux scripting, PHP, Javascript, Amazon Web Services (AWS) e SQL.