Noticias en español
— Associate Researchers
PhD in Adaptive Signal Processing, Imperial College London, UK (2014)
Master of Science in Electrical Engineering, University of Chile (2010)
Civil Engineering in Electricity, Universidad de Chile (2008)
Master of Science in Electrical Engineering, University of Chile (2010)
Civil Engineering in Electricity, Universidad de Chile (2008)
Institution: Universidad de Chile
Academic hierarchy: Profesor Asociado
Academic hierarchy: Profesor Asociado
Works at:
CMM Data Science
CMM Data Science
Research interests:
My research lies between Statistical Machine Learning and Signal Processing, including approximate inference, Bayesian nonparametrics, spectral estimation and computational optimal transport. I am also interested on ML/SP applications to astronomy, health, and audio. At Universidad de Chile, I have taught courses of Probability, Statistics, (Advanced) Machine Learning both for the Department of Mathematical Engineering and the Master of Data Science.
My research lies between Statistical Machine Learning and Signal Processing, including approximate inference, Bayesian nonparametrics, spectral estimation and computational optimal transport. I am also interested on ML/SP applications to astronomy, health, and audio. At Universidad de Chile, I have taught courses of Probability, Statistics, (Advanced) Machine Learning both for the Department of Mathematical Engineering and the Master of Data Science.
ftobar (at) dim (dot) uchile (dot) cl
+56 2 2977 1056
office: 722
Curriculum Vitae (link)
Publications (link)
+56 2 2977 1056
office: 722
Bio:
Felipe Tobar is an Associate Professor at the Initiative for Data and Artificial Intelligence, Universidad de Chile, and the Coordinator of the Master of Data Science at the same institution. He holds Researcher positions at the Center for Mathematical Modeling and the Advanced Center for Electrical and Electronic Engineering. Prior to joining Universidad de Chile, Felipe was a postdoc at the Machine Learning Group, University of Cambridge, during 2015 and he received a PhD in Signal Processing from Imperial College London in 2014. Felipe’s research interests lie in the interface between Machine Learning and Statistical Signal Processing, including approximate inference, Bayesian nonparametrics, spectral estimation, optimal transport and Gaussian processes.
Personal HomepageFelipe Tobar is an Associate Professor at the Initiative for Data and Artificial Intelligence, Universidad de Chile, and the Coordinator of the Master of Data Science at the same institution. He holds Researcher positions at the Center for Mathematical Modeling and the Advanced Center for Electrical and Electronic Engineering. Prior to joining Universidad de Chile, Felipe was a postdoc at the Machine Learning Group, University of Cambridge, during 2015 and he received a PhD in Signal Processing from Imperial College London in 2014. Felipe’s research interests lie in the interface between Machine Learning and Statistical Signal Processing, including approximate inference, Bayesian nonparametrics, spectral estimation, optimal transport and Gaussian processes.
Curriculum Vitae (link)
Publications (link)
