I am a data scientist and researcher dealing with theoretical and applied problems of Artificial Intelligence (AI) and Machine Learning (ML). For over 14 years, I have been researching and developing AI/ML methods and algorithms for areas such as Sentiment Analysis, Computer Vision, Predictive Analytics, and Natural Language Processing (NLP). I'm particularly interested in Generative AI, Semi-Supervised Learning, Ensembles, Bio-inspired Computing, Feature Engineering, and shallow/deep Artificial Neural Networks (MLPs, CNNs, GANs, Transformers, etc.) and the fine-tuning of these models. I have published my work in prestigious journals, such as IEEE Transactions on Fuzzy Systems, Elsevier Information Sciences, ACM Computing Surveys, and Elsevier Neurocomputing.I joined OCTO Research Office at Dell in 2022 and, since then, I have conducted several research studies and projects based on cutting-edge AI/ML techniques. Most of them involve topics such as Anomaly/Novelty Detection, AI Reasoning, Continual Learning, Federated Learning, Data Fusion, Edge Intelligence, and Language Models. I have co-authored and filed 3+ patents to date.Previously, I was Associate Professor at School of Sciences and Engineering (FCE) of the São Paulo State University (UNESP/Tupã) and was with the Electrical Engineering Graduate program (PPGEE/UNESP/Sorocaba-SJBV), in both I advised students in different research areas and taught courses. I was a member of H.IAAC - Artificial Intelligence and Cognitive Architectures Hub - based at the State University of Campinas (UNICAMP), where I researched on Learning in Cognitive Architectures. Before, I completed my Ph.D. in Computer Science in 2015 at Institute of Mathematics and Computer Sciences (ICMC) of the University of Sao Paulo (USP), São Carlos/Brazil, where I also received my M.Sc. degree in Computer Science in 2011, and my B.Sc. degree in Computer Information Systems in 2009.I am proficient in various traditional ML methods, such those supervised (Naive Bayes, K-NN, Decision Trees, SVM, Random Forest, etc.), also unsupervised ones (K-Means, FCM, EM, DBScan, etc.). I'm also fluent in several programming languages: Visual Basic, C#, C, C++, Java, Matlab, R and Python. I have experience in SQL and PL/SQL and in databases such as Oracle, MS SQL Server, MySQL, PostgreSQL, MongoDB, etc. I use version control systems, like GitLab and GitHub. My favorite libraries are WEKA, ELKI in Java, NumPy, Pandas, Scikit-Learn, SciPy, Matplotlib, Seaborn, NLTK, OpenCV, PyTorch, TensonFlow and Keras in Python, and dplyr, tidyr, caret in R.