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Felipe Arturo Tobar Henriquez
Senior Lecturer
Imperial College London
Santiago, Reino Unido
Machine Learning; Artificial Intelligence; Applied Statistics; Time Series; Signal Processing
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Signal Processing, IMPERIAL COLLEGE LONDON. Reino Unido, 2014
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Control Systems, UNIVERSIDAD DE CHILE. Chile, 2010
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Electrical Engineering, UNIVERSIDAD DE CHILE. Chile, 2007
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Electrical Engineering, UNIVERSIDAD DE CHILE. Chile, 2010
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Research Associate Full Time
UNIVERSITY OF CAMBRIDGE
Cambridge, Reino Unido
2014 - 2015
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Adjunct Lecturer (non-tenure) Full Time
UNIVERSIDAD DE CHILE
FCFM
Chile
2018 - 2021
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Researcher Full Time
UNIVERSIDAD DE CHILE
FCFM
Chile
2015 - A la fecha
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Associate Researcher Other
UNIVERSIDAD TECNICA FEDERICO SANTA MARIA
Chile
2020 - A la fecha
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Associate Professor Full Time
UNIVERSIDAD DE CHILE
FCFM
Santiago, Chile
2021 - 2024
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Senior Lecturer Full Time
IMPERIAL COLLEGE LONDON
Reino Unido
2024 - A la fecha
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CMM-Data Group Leader Part Time
Center for Mathematical Modeling
Chile
2018 - 2024
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Coordinator, Master of Data Science Other
University of Chile
Santiago, Chile
2020 - 2022
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Member - study group Eng II and machine learning Other
Fondecyt
Chile
2021 - 2021
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Director, Initiative for Data & AI Full Time
Universidad de Chile
Santiago, Chile
2022 - 2024
Postdocs:
1) Application of Optimal Transportation to Machine Learning --- Elsa Cazelles --- research associate --- 1/2019 to 9/2020--- Dpt. Ingeniería Matemática
During the last 5 years, I have supervised and examined the following research theses.
Nomenclature:
MSc = Master of Science
Eng = Engineer's professional title
EE = Electrical Engineering
ME = Mathematical Engineering
IE = Industrial Engineering
DS = Data Science
CS = Computer Science
All degrees given at Universidad de Chile unless otherwise stated
All thesis supervised only by me unless otherwise stated
i) Current students
Sebastián López (MSc-ME & Eng-ME): Gaussian process and neural networks
Diego Canales (MSc-DS, & Eng-EE): Emulation of audio devices
Alonso Letelier (MSc-ME & Eng-ME): Probabilistic models for time series
Víctor Caro (MSc-DS & Eng-CS): Generalisation on neural networks
Camila Bergasa (MSc-DS, & Eng-IE)
Bruno Moreno (MSc-DS, & Eng-ME)
David Molina (MSc-ME & Eng-ME)
Benjamín Pizarro (PhD, Medical Science - jointly supervised)
ii) Completed thesis as supervisor
14) 2022, Jou-Hui Ho (MSc-EE & Eng-EE) Greedy online change point detection
13) 2021, Matías Altamirano (MSc-ME & Eng-ME): Nonstationary multi-output Gaussian processes via harmonizable spectral mixtures
12) 2021 Cristóbal Valenzuela (MSc-ME & Eng-ME): Bandlimited Functions in Machine Learning
11) 2021 Diego León (Eng-EE): Deconvolución en audio utilizando modelos basados en Machine y Deep Learning
10) 2020. Gonzalo Ríos (PhD-ME, co-supervised), Contributions to Bayesian Machine Learning via Transport Maps
9) 2020. Alejandro Cuevas (Eng-EE & MSc-ME), Multioutput Gaussian process toolkit with sparse formulation for spectral kernels
8) 2020. Juan Ruiz (Eng-EE), Destilación de modelo en redes convolucionales
7) 2020. Mauricio Campos (Eng-ME & MSc-ME), Análisis de imágenes hiperespectrales geológicas mediante herramientas de aprendizaje de máquinas
6) 2019 Lerko Araya (Eng-EE & MSc-EE), Un enfoque moderno para la estimación espectral probabilística
5) 2018. Iván Castro (Eng-EE & MSc-EE), Predicción no lineal en línea de series de tiempo mediante el uso y mejora de algoritmos de filtros adaptivos de Kernel
4) 2018 Rodrigo Lara (Eng-ME), Clasificación en imágenes satelitales: superficie construida y uso del suelo
3) 2017. Gabriel Parra (Eng-ME & MSc-ME), Spectral Mixture Kernels for Multi-Output Gaussian Processes
2) 2017. Romain Gouron (Eng-ME), Estudiando Obras Literarias con Herramientas de Procesamiento de Lenguaje Natural
1) 2017 David Gómez (Eng-EE, co-supervised), Mejoramiento de la clasificación funcional de enzimas usando aprendizaje de máquinas
iii) Examined thesis
17) 2022. Abdiel Ricaldi M. (MSc-EE), Diseño y comparación de controladores fraccionales en un banco de celdas y una columna de flotación en el proceso de extracción de cobre
16) 2021. Jhon Intriago C. (MSc-EE), Development of Spike Neural Networks Models Based on Information Theory and Biological Optimitization Criterion
15) 2021. Nicolás Cruz B. (Eng-EE & MSc-EE), Bridging the gap between simulation and reality using generative neural networks
14) 2021. Mauricio González (Eng-EE & MSc-EE), A fast-running failure prognostic algorithm based on a non-homogeneous markow chain
13) 2020. Daniel Augusto Ramos (MSc-Computer Science, Universidade Federal do Ceará), Contributions on latent projections for Gaussian processes modelling
12) 2020. Manuel Suil (Eng-ME & MSc-ME), Análisis sobre métodos de ajuste y aprendizaje de máquinas aplicados a la equivalencia y reducción de modelos de electrofisiología cardíaca
11) 2020. Nicolás Cruz (Eng-EE & MSc-EE), Bridging the gap between simulation and reality using generative neural networks
10) 2019. Rodrigo Pérez D. (Eng-EE & MSc-EE), Interactive learning with corrective feedback for continuous-action policies based on deep neural networks
9) 2019 Diego Ibáñez I. (Eng-IE) Predicción y descripción de la exclusión educativa del sistema escolar regular Chileno, ciencia de datos para la innovación pública
8) 2019 Pedro orellana (Eng-EE & MSc-EE), Segmentación semántica y reconocimiento de lugares usando características CNN pre-entrenadas
7) 2018 Tomás Valdivia (Eng-IE) Aplicaciones de aprendizaje de máquinas en electroencefalografias para salud mental
6) 2018 Antonia Larrañaga R. (Eng-EE), Evaluación de carga cognitiva y estado emocional mediante sensores psico-fisiológicos en tareas de redacción
5) 2018 Matías Mattamala (Eng-EE & MSc-EE), Localización visual en robots de recursos computacionales limitados
4) 2018 Alonso Guzman (Eng-EE) Árboles de decisión e identificación de genes en bacterias
3) 2018 Kenzo Lobos (Eng-EE & MSc-EE), Aprendizaje reforzado en robótica móvil
2) 2018. Diego Campanini G. (Eng-EE), Detección de objetos usando redes neuronales convolucionales junto con Random Forest y Support Vector Machines
1) 2017 Claudia Soto (Eng-EE & MSc-EE), Reconocimiento rápido de objetos usando object proposals y Deep Learning
1) PROFESSIONAL SERVICE (RECENT)
Editorial and Grant Agency work
-2021: Associate Editor, IEEE Transactions on Neural Networks and Learning Systems.
-2021: Member of the Fondecyt Study Group (Engineering II, Machine Learning). Duties include to recruit reviewers and assess completion reports for Chile’s Fondecyt grants.
-2021: Topic Chair - The IEEE Latin American Conference on Computational Intelligence (LA-CCI)
-2021: Guest Editor - MDPI Entropy Special Issue Adaptive filters and machine learning algorithms for non-linear system identification and processing
Reviewer
-Journals: Journal of Machine Learning Research, IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Signal Processing, IEEE Transactions on Neural Networks and Learning Systems, Springer Machine Learning
-Conferences: NeurIPS, ICML, AAAI, UAI, ICLR, AISTATS, IEEE-MLSP & IEEE-ICASSP
2) TALKS (RECENT)
The Art of Gaussian processes: Classic and Contemporary
Dec 2021: Neural Information Processing Systems (online)
From Gaussian processes to Multioutput Gaussian processes
Nov 2021: IEEE Escuela de Verano en Inteligencia Computacional (at Temuco, Chile, given remotely)
Multioutput Gaussian processes
Sept 2021: Gaussian Process Summer School (at Sheffield, UK, given remotely)
Multioutput Gaussian processes for EEG imputation
14 Jan 2021: AC3E, Bioinformatics Group, U. Santa María, Valparaíso, Chile (3eonline)
25 Nov 2021: AC3E, U. Santa María, Valparaíso, Chile (online)
19 Dec 2020: IEEE EVIC, U. de la Frontera, Temuco, Chile (online)
Discussion Panel (participant): Data Science & AI, transforming the industry form Academia
26 Nov 2020: Facultad de Ciencias Físicas y Matemáticas, U. de Chile, Santiago, Chile
Bayesian reconstruction of Fourier Pairs
30 Oct 2020: Seminar series of Astroinformatics, ALERCE, U. de Chile, Santiago, Chile
Data Science projects at the Center for Mathemtical Modeling
16 Oct 2020: Entel, Data Science Division
Sharing the experience of an Electrical Engineer in the Academia
8 Oct 2020: Electrotutores, Department of Electrical Engineering, U. de Chile, Santiago, Chile
Band-limited Gaussian processes: The sinc kernel
6 Dec 2019: Conferencia Latinoamericana de Probabilidades y Estadística, Mérida, México
13 Dec 2019: NeurIPS conference (poster presentation only)
Multi-output Gaussian processes: Generative models and toolbox demonstration
8 Aug 2019: Pucón Data Science Symposium, Puerto Varas, Chile
An introduction to Artificial Intelligence and Machine Learning
24 May 2019: Chile-Italy Forum, U. de Concepción, Concepción, Chile
Round Table participation: Challenges in Data Science, from fundamentals to applications
9 May 2019: 80 anniversary CNRS: CNRS in SouthAmerica. PUC, Santiago, Chile
Bayesian Nonparametric Spectral Estimation
19 June 2019: Mathematical Modelling Seminar, Pontificia U. de Chile.
4 Dec 2018: The Neural Information Processing Systems Conference, Montreal, Canada (slides)
14 Dec 2018: Escuela de Verano en Inteligencia Computacional (EVIC), Santiago, Chile (slides)
A Gentle Introduction to Gaussian Proceses with Applications
19 June 2018: Grupo de Aprendizaje de Máquinas en Biomedicina y Salud, U. de Chile, Santiago, Chile.
24 August 2018: Instituto Fundamentos de los Datos, U. de Chile, Santiago, Chile.
6 Nov 2018: U. de Valparaíso, Dept of Statistics, Valparaíso, Chile.
7 Nov 2018: U. de Valparaíso, Dept of Engineering, Valparaíso, Chile.
3) SCIENTIFIC CONSULTANCY
CMM & PSI-net & Codelco (PI, 12/2019 - 12/2020)
Detection of operational risk from video recordings of mining operation.
CMM & BancoEstado (PI, 8/2017 - 9/2017)
Design of forecasting algorithms for costs and profit in small companies.
Innovaxxión & Advanced mining technology center (Research Assoc. 6/2016 - 4/2018)
Mineral detection and classification based on hyperspectral analysis.
CMM & Uplanner (Research Assoc. 8/2016 - 4/2017)
Demand forecasting on higher-education courses.
CMM & Mutual de Seguridad (Research Assoc. 10/2016)
High-Dimensional Kernel Regression: A Guide for Practitioners |
ADVANCES ON GENERATIVE MODELS FOR STATISTICAL MACHINE LEARNING: THEORY AND PRACTICE |
Detection of neonatal seizures from EEG: A continual & multi-channel approach |
AI for Everyone: benefitting from and building trust in the technology |
On the relationship between Gaussian process regression and spectral estimation |
Sistema de detección y clasificación mineralógica rápida basado en análisis híper espectral |
Machine Learning Meets Signal Processing |
Machine Learning for Time-Series Data |
SEQUENTIAL MONTE CARLO METHODS AND FEEDBACK CONCEPTS APPLIED TO FAULT DIAGNOSIS AND FAILURE PROGNOSIS IN NONLINEAR, NON-GAUSSIAN DYNAMIC SYSTEMS |

Axel Osses
Profesor Titular
Departamento de Ingeniería Matemática
Universidad de Chile
Santiago, Chile

Pablo Guerrero
Founder and Head of Research and Development
Research and Development
Price Tracker
Santiago, Chile

Jorge Silva
Associate Professor
Departamento de Ingeniería Eléctrica
Universidad de Chile
Santiago, Chile

Jocelyn Dunstan
Profesora Asistente
Ciencia de la Computación
Pontificia Universidad Católica de Chile
Santiago, Chile
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Felipe Tobar
Senior Lecturer
Department of Mathematics
Imperial College London
Santiago, Reino Unido

Cristian Hernández
Assistant Professor
Gastroenterology
Pontificia Universidad Católica de Chile
Santiago, Chile

Marcela Aguirre
Analista ETESA
Gerencia de Investigación
Fundación Arturo López Pérez
Santigo, Chile

Felipe Bravo
Profesor Asociado
Departamento de Ciencias de la Computación
Universidad de Chile
Santiago, Chile

Jazmine Maldonado
Directora de Innovación y Transferencia Tecnológica
Innovación y Transferencia Tecnológica
Instituto Milenio Fundamentos de los Datos
Santiago, Chile