Eliezer de Souza da Silva

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
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