The Big Data & Analytics utilizing Probabilistic Models group develops algorithms for specialized applications such as artificial intelligence, signal processing and information extraction, time series modeling and forecasting.

We employ probabilistic models, particularly Bayesian networks, Markov Random Fields, and Causal networks, which incorporate the data’s uncertainties. These models have a variety of uses, ranging from evaluating brain circuits to assessing the durability of energy systems.

We work on graduate studies in electrical and mechanical engineering.

Interested parties should send their CV to carlos.maciel@unesp.br