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Felipe Arturo Tobar Henriquez

Researcher

Universidad de Chile

Santiago, Chile

Líneas de Investigación


Machine Learning; Artificial Intelligence; Applied Statistics; Time Series; Signal Processing

Educación

  •  Signal Processing, IMPERIAL COLLEGE LONDON. Reino Unido, 2014
  •  Control Systems, UNIVERSIDAD DE CHILE. Chile, 2010
  •  Electrical Engineering, UNIVERSIDAD DE CHILE. Chile, 2007
  •  Electrical Engineering, UNIVERSIDAD DE CHILE. Chile, 2010

Experiencia Académica

  •   Research Associate Full Time

    UNIVERSITY OF CAMBRIDGE

    Cambridge, Reino Unido

    2014 - 2015

  •   Adjunct Lecturer (non-tenure) Full Time

    UNIVERSIDAD DE CHILE

    FCFM

    Chile

    2018 - A la fecha

  •   Researcher Full Time

    UNIVERSIDAD DE CHILE

    FCFM

    Chile

    2015 - A la fecha

  •   Associate Researcher Other

    UNIVERSIDAD TECNICA FEDERICO SANTA MARIA

    Chile

    2020 - A la fecha

Experiencia Profesional

  •   CMM-Data Group Leader Part Time

    Center for Mathematical Modeling

    Chile

    2015 - A la fecha

  •   Coordinator, Master of Data Science Other

    University of Chile

    Santiago, Chile

    2020 - A la fecha

  •   Member - study group Eng II and machine learning Other

    Fondecyt

    Chile

    2021 - A la fecha

Formación de Capital Humano


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

Jou-Hui Ho (MSc-EE & Eng-EE): Gaussian process for seizure detection from EEG
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

ii) Completed thesis as supervisor

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
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


Difusión y Transferencia


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)



 

Article (22)

Bayesian Reconstruction of Fourier Pairs
Data Science for Engineers: A Teaching Ecosystem
MOGPTK: The multi-output Gaussian process toolkit
The Wasserstein-Fourier Distance for Stationary Time Series
GAUSSIAN PROCESS IMPUTATION OF MULTIPLE FINANCIAL SERIES
Predicting nationwide obesity from food sales using machine learning
Compositionally-warped Gaussian processes
Echo state network and variational autoencoder for efficient one-class learning on dynamical systems
Improving battery voltage prediction in an electric bicycle using altitude measurements and kernel adaptive filters
Robust Detection of Extreme Events Using Twitter: Worldwide Earthquake Monitoring
A Bayesian mixture-of-gaussians model for astronomical observations in interferometry
Improving sparsity in kernel adaptive filters using a unit-norm dictionary
Initialising kernel adaptive filters via probabilistic inference
Recovering Latent Signals From a Mixture of Measurements Using a Gaussian Process Prior
Unsupervised blue whale call detection using multiple time-frequency features
Design of Positive-Definite Quaternion Kernels
MODELLING OF COMPLEX SIGNALS USING GAUSSIAN PROCESSES
Unsupervised State-Space Modeling Using Reproducing Kernels
Multikernel least mean square algorithm
Quaternion reproducing kernel hilbert spaces: Existence and uniqueness conditions
Study of Financial Systems Volatility Using Suboptimal Estimation Algorithms
Outer Feedback Correction Loops in Particle Filtering-based Prognostic Algorithms=> Statistical Performance Comparison

BookSection (1)

High-Dimensional Kernel Regression: A Guide for Practitioners

ConferencePaper (16)

Band-limited Gaussian processes: The Sinc kernel
LOW-PASS FILTERING AS BAYESIAN INFERENCE
Bayesian Nonparametric Spectral Estimation
Learning non-Gaussian Time Series using the Box-Cox Gaussian Process
Combining reservoir computing and variational inference for efficient one-class learning on dynamical systems
Spectral Mixture Kernels for Multi-Output Gaussian Processes
Modelling time series via automatic learning of basis functions
Learning stationary time series using Gaussian processes with nonparametric kernels
The widely linear quaternion recursive total least squares
Estimation of Financial Indices Volatility Using a Model with Time-Varying Parameters
The quaternion kernel least squares
A novel augmented complex valued kernel LMS
Multikernel least squares estimation
Noise assisted multivariate empirical mode decomposition applied to Doppler radar data
Anomaly detection in power generation plants using similarity-based modeling and multivariate analysis
A particle filtering based kernel HMM predictor

Proyecto (8)

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
41
Felipe Tobar

Researcher

Center for Mathematical Modeling

Universidad de Chile

Santiago, Chile

3
Marcos Orchard

Professor

Electrical Engineering

Universidad de Chile

Santiago, Chile

1
RENE SANCHEZ

DOCENTE

MECANICA

UNIVERSIDAD POLITÉCNICA SALESIAN

CUECA, Ecuador

1
sonia español

Líder área de cetáceos

Fundación MERI

Santiago, Chile

1
Axel Osses

Profesor Titular

Departamento de Ingeniería Matemática

Universidad de Chile

Santiago, Chile

1
Jazmine Maldonado

CTO

Innovación y Transferencia Tecnológica

Instituto Milenio Fundamentos de los Datos

Santiago, Chile

1
Jorge Silva

Assistant Professor

Departamento de Ingeniería Eléctrica

Universidad de Chile

Santiago, Chile

1
Taco de Wolff

Investigador

INRIA Chile

Santiago, Chile

1
Pablo Guerrero

Founder and Head of Research and Development

Research and Development

Price Tracker

Santiago, Chile