Miguel Lazaro Gredilla, PhD

Miguel previously earned his PhD in machine learning at Universidad Carlos III de Madrid. In his thesis, Miguel developed a sparse Gaussian process model which has become the de facto benchmark for fast regression algorithms. Since then, Miguel has been working on approximate inference algorithms for other Bayesian models. He has been a visiting scholar at the University of Cambridge and the University of Manchester, and has authored and reviewed for NIPS, JMLR, and several IEEE journals.