Man

JUAN RICARDO NANCULEF ALEGRIA

Full Time Professor

Universidad Técnica Federico Santa María

Santiago, Chile

Líneas de Investigación


Lecturer in Computer Science at UTFSM, Campus San Joaquín, from 03-2014. Before: Postdoc at University of Bristol, UK. Specialized in Machine Learning, Optimization and Statistics. Doing research in support vector machines, non-linear convex optimization, randomized algorithms, dimensionality reduction and applications to text analysis.

Educación

  •  Doctor en Ingeniería Informática, Universidad Técnica Federico Santa María. Chile, 2011
  •  Magíster en Ciencias de la Ingeniería Informática, Universidad Técnica Federico Santa María. Chile, 2006
  •  Ingeniero Civil Informático, Universidad Técnica Federico Santa María. Chile, 2006

Experiencia Académica

  •   Profesor Instructor Full Time

    Universidad Técnica Federico Santa María

    Santiago, Chile

    2014 - A la fecha

  •   Researcher Full Time

    Universidad Técnica Federico Santa María

    Valparaíso, Chile

    2011 - 2014

  •   Research Assistant Full Time

    Universidad Técnica Federico Santa María

    Valparaíso, Chile

    2005 - 2008

  •   Part-Time Professor Part Time

    Universidad Técnica Federico Santa María

    Valparaíso, Chile

    2006 - 2008

  •   Part-Time Professor Part Time

    Universidad Técnica Federico Santa María

    Valparaíso, Chile

    2011 - 2011

  •   Part-Time Professor Part Time

    Universidad Tecnológica de Chile - INACAP

    Valparaíso, Chile

    2006 - 2008

  •   Part-Time Professor Part Time

    Universidad Adolfo Ibáñez

    Valparaíso, Chile

    2008 - 2008

  •   Research Assistant Part Time

    Universidad de Bologna

    Bologna, Italia

    2009 - 2010

  •   Research Assistant Part Time

    Universidad Técnica Federico Santa María

    Valparaíso, Chile

    2010 - 2011

  •   Co-researcher Project Fondecyt 1070220 Other

    Universidad Técnica Federico Santa María

    Valparaíso, Chile

    2007 - 2007

Experiencia Profesional

  •   Post-doctoral Researcher

    University of Bristol

    Bristol, Reino Unido

    2012 - 2013

Formación de Capital Humano


As a full-time professor at the Department of Informatics of the Federico Santa Maria University I teach to students in a regular basis. Typically, I give the course of Computational Statistics in the Campus Santiago San Joaquín of the university, to undergraduate students, each semester. In addition I give more specialized courses like: Machine Learning and Intelligent Data Analysis, to undergraduate and postgraduate students, at least once per year. I usually supervise students for the completition of their graduation projects (something like a thesis, but for undergraduates). Till now I have only (co-)supervised one post-graduate Master thesis. In the next years I should supervise other Master thesis as well as PhD thesis.
In the last year, I had two students working as research assistants. Their graduation projects will be related to topics of this proposal.


Premios y Distinciones

  •   Best Paper Award

    15th Iberoamercian Congress on Pattern Recognition

    Brasil, 2010

    Best paper award in the 15th Iberoamercian Congress on Pattern Recognition, Sao Paulo, 2010

  •   Valedictorian of the Class 2006 - Informatics Engineering

    UNIVERSIDAD TECNICA FEDERICO SANTA MARIA

    Chile, 2006

    Highest ranking among the graduating class of year 2006 in Informatics Engineering.


 

Article (31)

An Attention-Based Architecture for Hierarchical Classification With CNNs
Attention Mechanisms in Process Mining: A Systematic Literature Review
Enhancing Intra-modal Similarity in a Cross-Modal Triplet Loss
Cluster Distillation: Semi-supervised Time Series Classification through Clustering-based Self-supervision
Multi-attribute Transformers for Sequence Prediction in Business Process Management
A Method to Predict Semantic Relations on Artificial Intelligence Papers
Self-supervised Bernoulli Autoencoders for Semi-supervised Hashing
Automating Configuration of Convolutional Neural Network Hyperparameters Using Genetic Algorithm
Collective annotation patterns in learning from crowds
Interpretable and effective hashing via Bernoulli variational auto-encoders
Boosting collaborative filters for drug-target interaction prediction
LocalBoost: A Parallelizable Approach to Boosting Classifiers
Revisiting Machine Learning from Crowds a Mixture Model for Grouping Annotations
Calcified plaque detection in ivus sequences: Preliminary results using convolutional nets
Fast and scalable Lasso via stochastic Frank-Wolfe methods with a convergence guarantee
A novel Frank-Wolfe algorithm. Analysis and applications to large-scale SVM training
Efficient classification of multi-labeled text streams by clashing
TRAINING SUPPORT VECTOR MACHINES USING FRANK-WOLFE OPTIMIZATION METHODS
Training regression ensembles by sequential target correction and resampling
An Ensemble Method for Incremental Classification in Stationary and Non-Stationary Environments
Two One-Pass Algorithms for Data Stream Classification Using Approximate MEBs
A New Algorithm for Training SVMs using Approximate Minimal Enclosing Balls
A Sequential Minimal Optimization algorithm for the All-Distances Support Vector Machine
AD-SVMs: A light Extension of SVMs for Multicategory Classification
L2-SVM Training with Distributed Data
ENSEMBLE LEARNING WITH LOCAL DIVERSITY
Local negative correlation with resampling
Multiresolution fuzzy rule systems
Moderated innovations in self-poised ensemble learning
Self-poised ensemble learning
ROBUST BOOTSTRAPPING NEURAL NETWORKS

BookSection (2)

Support Vector Classification via Computational Geometry Methods
Ensembles Methods for Machine Learning

ConferencePaper (17)

A Binary Variational Autoencoder for Hashing
Forecasting Ozone Pollution using Recurrent Neural Nets and Multiple Quantile Regression
Boosting SpLSA for Text Classification
Efficient Sparse Approximation of Support Vector Machines Solving a Kernel Lasso
A PARTAN-accelerated Frank-Wolfe algorithm for large-scale SVM classification
An Ensemble Method for Incremental Classification in Stationary and Non-stationary Environments
Two One-Pass Algorithms for Data Stream Classification Using Approximate MEBs
A new algorithm for training SVMs using approximate minimal enclosing balls
A sequential minimal optimization algorithm for the all-distances support vector machine
Learning multi-class support vector models from distributed data using core-sets
Single-Pass Distributed Learning of Multi-Class SVMs using Core-Sets
L2-SVM training with distributed data
Multicategory SVMs by minimizing the distances among convex-hull prototypes
Bagging with asymmetric costs for misclassified and correctly classified examples
Probabilistic aggregation of classifiers for incremental learning
Robust alternating AdaBoost
Two bagging algorithms with coupled learners to encourage diversity

Proyecto (8)

MULTI LABEL CLASSIFICATION OF LARGE SCALE DATA STREAMS USING HASH KERNEL MACHINES
ENSEMBLE OF MACHINE LEARNING-BASED LOCAL ESTIMATORS FOR HIGH FREQUENCY TIME SERIES FORECASTING
Métodos de Aprendizaje Automático Aplicados a la Extracción de Patrones sobre Grandes Streams de Datos. (Machine Learning Methods Applied to Large Data Streams)
Fortalecimiento de un Nuevo Programa de Doctorado en Ingeniería Informática
Erasmus Exchange for Research in Incremental Learning of Non-Binary SVMs
ENSEMBLE LEARNING STRATEGIES FOR HIGH-DIMENSIONAL AND NON-STATIONARY DATA
ROBUST LEARNING ALGORITHMS FOR MODULAR NEURAL NETWORKS IN NON-STATIONARY TIME
Estimación Robusta y Desarrollo de Filtros en Procesamiento de Imágenes de Percepción Remota
47
JUAN NANCULEF

Full Time Professor

Universidad Técnica Federico Santa María

Santiago, Chile

11
Héctor Allende

Professor

Computer Science

UNIVERSIDAD TÉCNICA FEDERICO SANTA MARÍA

Valparaíso, Chile

9
Carlos Valle

Académico Jornada Completa

Computación e Informática

Universidad de Playa Ancha

Valparaíso, Chile

1
Héctor Allende

Profesor Asociado

Pontificia Universidad Católica de Valparaíso

Valparaíso, Chile

1
Marcelo Mendoza

Académico

Ciencias de la Computación

Pontificia Universidad Católica de Chile

Santiago, Chile

1
Rodrigo Salas

Profesor Titular Jornada Completa

UNIVERSIDAD DE VALPARAÍSO

Valparaíso, Chile

1
Ricardo Soto

Director

Escuela de Ingeniería Informática - PUCV

Valparaiso, Chile

1
franklin johnson

Director

Computación e Informática

Universidad de Playa Ancha de Ciencias de la Educación

valparaíso, Chile