Felipe Tobar

About

I am a Senior Lecturer in Machine Learning at the Department of Mathematics & I-X, Imperial College London. Previously, I was an Associate Professor in the Data & AI Initiative at Universidad de Chile. 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.

E-mail: first initial (dot) last name (at) imperial (dot) ac (dot) uk

News

1 Oct 2024. I joined Imperial College London’s Department of Mathematics and I-X as a Senior Lecturer in Machine Learning. Looking forward to the collaborations ahead!
13-15 December 2023. Join us for our upcoming summer school: Escuela de Verano en Inteligencia Computational EVIC.
1 November 2023. See our preprint Asynchronous Graph Generators arXiv.

Research group

My group is called GAMES (Grupo de Aprendizaje de Máquinas, infErencia y Señales). Luckily enough, and up to a minor permutation, the acronym seems to also work in English as Group of MAchine learning, infErence and Signals. Current members are

Arturo Tagle (MSc, Data Science): The free energy principle
Cristóbal Alcázar (MSc, Data Science): Guidance in difussion models
Camila Andreas (MSc, Data Science): Optimal transport and fariness
Joaquín Barceló (MSc, Data Science): Difussion models and RL
Camilo Carvajal (MSc, Data Science): Safe sampling difussion models
Juan Cuevas (MSc, Data Science): Attention networks for time series
Diego Cortéz (MSc, Data Science): ML for genomics
Fernando Fetis (MSc, Data Science): Difussion models
Camila Pinto (MSc, Data Science): Graphical models applied to career choices in STEM
Gianina Salomó (MSc, Data Science): LLMs for gender-aware contexts
Stefano Schiappacasse (MSc, Data Science): Audio processing for conservation of manatees

Former members:

Tomás Valencia, now Data Scientist at PSInet
Bruno Moreno, now Data Scientist at Consorcio
Sebastián López, now at PUC
Elsa Cazelles, now CNRS Researcher at IRIT
Jou Hui Ho, now Data Scientist at Cero.ai
Taco de Wolff, Founder DeWolff Consulting
Matías Altamirano, now PhD student in Statistical Science at UCL
Alejandro Cuevas, now Data Scientist at NoiseGrasp
Mauricio Campos, now Data Scientist at Coca-Cola
Gonzalo Ríos, now Senior Data Scientist at NoiseGrasp
Lerko Araya, now Data Scientist at Liberty Latin America
Iván Castro, now Data Scientist at Amazon Web Services
Rodrigo Lara, now Data Scientist at PROSPERiA
Gabriel Parra, now Data Scientist at AutoFact

Short Bio

Felipe Tobar is an Associate Professor at Universidad de Chile and the Director of the Initiative for Data and Artificial Intelligence of 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. Felipe teaches graduate courses on Machine Learning and Statistics and between 2020 and 2022 was the Coordinator of the Master of Data Science at Universidad de Chile.

Photos: Color, Color-low-res, BW, BW-low-res