My main research interest is designing efficient algorithms and principled methods for Machine Learning and Artificial Intelligence problems, ranging from proposing models, learning algorithms, inference, and prediction. I have an interest in variational inference and other scalable and approximate inference methods, as well as causal inference methods. I obtained my Ph.D. in Computer Science at the Norwegian University of Science and Technology (NTNU, Norges teknisk-naturvitenskapelige universitet), a master's degree in Electrical and Computer Engineering at the University of Campinas (FEEC/Unicamp) and a degree in Computer Engineering at the Federal University of Espírito Santo (UFES). I have experience with Bayesian matrix and tensor factorization models (with application in recommender systems), point processes, deep learning, physical-informed neural networks, time series models, locality-sensitive hashing, and natural language processing.
Areas of interest:
- Statistical machine learning
- Deep generative models
- Causal inference
- Bayesian modeling and inference
- Combining uncertainty modeling, prior knowledge, and machine learning for diverse applications