Man

Jorge Ramón Vergara Quezada

Profesor asistente

Universidad Tecnológica Metropolitana

Santiago, Chile

Líneas de Investigación


Feature selection/extraction/construction; Machine learning; Computational intelligence, information theory learning, signal processing and pattern recognition, multi-objective optimization, Evolutionary Computation.

Educación

  •  Science in engineering, UNIVERSIDAD DE LA FRONTERA. Chile, 2005
  •  Electrical engineering, UNIVERSIDAD DE CHILE. Chile, 2015
  •  Electronic civil engineer, UNIVERSIDAD DE LA FRONTERA. Chile, 2007

Experiencia Académica

  •   Profesor adjunto Part Time

    UNIVERSIDAD ANDRES BELLO

    Santiago, Chile

    2010 - 2011

  •   Profesor adjunto Part Time

    UNIVERSIDAD DE VALPARAISO

    Valparaiso, Chile

    2012 - 2012

  •   Profesor adjunto Other

    UNIVERSIDAD DE CHILE

    Facultad de Ciencias Físicas y Matemáticas

    Santiago, Chile

    2008 - At present

  •   Profesor asistente Other

    UNIVERSIDAD DE LA FRONTERA

    Facultad de Ingeniería y Ciencias

    Temuco, Chile

    2004 - 2006

  •   Profesor Asistente Full Time

    UNIVERSIDAD TECNOLOGICA METROPOLITANA

    Ingeniería

    Santiago, Chile

    2019 - At present

Experiencia Profesional

  •   Investigador Postdoctorado Full Time

    Universidad de Chile

    Santiago, Chile

    2016 - 2018

  •   Asesor Part Time

    ProteinLab UTEM

    Santiago, Chile

    2019 - At present

Difusión y Transferencia


- Research column for the MAS on the work done jointly with the University of Washington for the improvement of the Large Synoptic Survey Telescope (LSST) asteroid alert system. June 7,2017, http://www.astrofisicamas.cl/en/el-moving-object-pipeline-system/
- PROENTA “The Magic of the Volcanoes”. Activity focused on students between 10-13 years to deliver basic knowledge of volcanoes in Chile. University of La Fontera, 2005


Premios y Distinciones

  •   Postdoctorado

    FONDECYT

    Chile, 2016

    Postdoctorado FONDECYT 3160772


 

Article (12)

Searching for Changing-state AGNs in Massive Data Sets. I. Applying Deep Learning and Anomaly-detection Techniques to Find AGNs with Anomalous Variability Behaviors
Subset Feature Selection with Structural Variables
The Automatic Learning for the Rapid Classification of Events (ALeRCE) Alert Broker
Dimensionality Reduction of SDSS Spectra with Variational Autoencoders
A strategy for time series prediction using segment growing neural gas
Segment Growing Neural Gas for Nonlinear Time Series Analysis
Pattern recognition applied to seismic signals of the Llaima volcano (Chile): An analysis of the events' features
A review of feature selection methods based on mutual information
Nonlinear Time Series Analysis by Using Gamma Growing Neural Gas
CMIM-2: An Enhanced Conditional Mutual Information Maximization Criterion for Feature Selection
Classification of seismic signals at Villarrica volcano (Chile) using neural networks and genetic algorithms
Classification of seismic signals at Villarrica volcano (Chile) using neural networks and genetic algorithms

ConferencePaper (2)

Segment growing neural gas for nonlinear time series analysis
Nonlinear time series analysis by using gamma growing neural gas

Proyecto (9)

SELECCIÓN Y EXTRACCIÓN DE GRUPOS DE CARACTERÍSTICAS BASADO EN INFORMACIÓN MUTUA PARA CLASIFICACIÓN DE PATRONES EN IMÁGENES Y SERIES DE TIEMPO ASTRONÓMICAS
ADVANCED MACHINE LEARNING AND SIGNAL PROCESSING METHODS FOR TIME SERIES ANALYSIS=> APPLICATIONS TO ASTRONOMICAL LIGHT CURVES AND SLEEP EEG
ADVANCED MACHINE LEARNING AND SIGNAL PROCESSING METHODS FOR TIME SERIES ANALYSIS=> APPLICATIONS TO ASTRONOMICAL LIGHT CURVES AND SLEEP EEG
SOLAR ENERGY RESEARCH CENTER (SERC-Chile)
ADVANCES NEURAL NETWORKS AND INFORMATION THEORETIC LEARNING METHODS FOR TIME SERIES ANALYSIS=> APPLICATIONS TO ASTRONOMICAL LIGHT CURVES AND BIOMEDICAL SIGNALS
ADVANCED METHODS FOR MACHINE LEARNING AND PATTERN RECOGNITION BY USING INFORMATION THEORETIC LEARNING, SELF-ORGANIZING NEURAL NETWORKS, AND EVOLUTIONARY COMPUTATION
MAGNETIC PROPERTIES OF TWO INTRINSICALLY FRUSTRATED SYSTEMS.
MAGNETIC PROPERTIES OF TWO INTRINSICALLY FRUSTRATED SYSTEMS.
Utilización de Redes Neuronales Artificiales en el procesamiento y análisis de la actividad sísmica del Volcán Villarrica para modelamiento y pronóstico de erupciones
9
Jorge Vergara

Profesor asistente

Informática y Computación

Universidad Tecnológica Metropolitana

Santiago, Chile

4
Pablo Estevez

Profesor Titular

Departamento de Ingenieria Eléctrica

DEPTO. INGENIERÍA ELÉCTRICA, UNIVERSIDAD DE CHILE

Santiago, Chile

2
Millaray Curilem

Académica

Ingeniería Eléctrica

Universidad de La Frontera

Temuco, Chile

2
Guillermo Cabrera

Associate Professor

Department of Computer Science

Universidad de Concepción

Concepción, Chile

2
Lorena Hernandez

Postdoc

Universidad de Valparaíso

Valparaiso, Chile

1
Márcio Catelan

Full Professor

Instituto de Astrofísica

PONTIFICIA UNIVERSIDAD CATÓLICA DE CHILE

Santiago, Chile

1
Nayat Sánchez

Directora

Inria Chile

Santiago, Chile

1
Radostin Kurtev

Titular

Instituto de Física y Astronomía

UNIVERSIDAD DE VALPARAÍSO

Valparaíso, Chile

1
Néstor Becerra

Full Professor

Electrical engineering

Universidad de Chile

Santiago, Chile

1
Fernando Huenupan

Academico

Ingeniería Electrica

Universidad de La Frontera

Temuco, Chile

1
Gonzalo Acuña

Profesor Titular

Ingenieria Informatica

Universidad de Santiago de Chile

Santiago, Chile

1
Alejandro Clocchiatti

Professor

Astrophysics

Pontificia Universidad Católica de Chile

Santiago, Chile

1
Max Chacón

Profesor Titular

Ingeniería Informática

UNIVERSIDAD DE SANTIAGO DE CHILE

Santiago, Chile