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Universidad EAFIT
Carrera 49 # 7 sur -50 Medellín Antioquia Colombia
Carrera 12 # 96-23, oficina 304 Bogotá Cundinamarca Colombia
(57)(4) 2619500 contacto@eafit.edu.co

Docentes e investigadores EAFIT Olga Lucía Quintero Montoya - Docentes e investigadores

EAFITDocentes e investigadores EAFITOlga Lucía Quintero Montoya - Docentes e investigadores

Olga Lucía Quintero Montoya

​​​​​​​​​​​​​​​​​​Departamento de Ciencias Matemáticas​​

Información general

​Doctora​ en Ingeniería de Sistemas de Control, Universidad Nacional de San Juan, Argentina​.

Contacto

  • Teléfono/pho​ne: (57) (4) 261 9500, extensión 9064​.
  • Correo electrónico/e-mail: oquinte1@eafit.edu.co.
  • Dirección/address: carrera 49 número 7 sur 50, Medellín (Colombia). Bloque 38, oficina 434.​

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Resumen CV / Summary

O. L. Quintero M is a Control Engineer from Minas School of National University of Colombia-Medellin, obtained her PhD in Control Engineering Systems from Institute of Automatica at Universidad Nacional de San Juan en Argentina in 2008. 

 
From 2008 to 2011 she was consultant for oil and gas companies and developed several works on telecommunications market in Latinoamerica. Also was a Professor at USFQ in Quito.

 
Since 2011 she joined the Mathematical Sciences Department in Universidad EAFIT and currently is the Academic Director of the Mathematical Engineering PhD Program and Mathematical Modeling Research Group at Universidad EAFIT. 

 
Her research interests are not only Control Systems but also Bayesian Filtering, Multidimensional Signal Analysis, Artificial Intelligence and Machine Learning.

Intereses académicos e investigativos / Research and Teaching Interest

-Control Systems and Bayesian Filtering in cooperation with Universidad Nacional de San Juan (Argentina) and TU Delft (The Netherlands): 

 
Prof Quintero have been published several papers on Tracking Control using numerical methods and linear algebra on nonlinear systems such as mobile robots and bioprocesses in coauthorship with Gustavo Scaglia from Instituto de Ingeniería Química at UNSJ. Their results have been published in several journals such as Robotica.

 
Also, her work on Bayesian Filtering have been developed through years with Adriana Amicarelli and Fernando di Sciascio from INAUT. Their work on state estimation with particle filters for bioprocesses such as Zymomonas mobilis and Bacillus thuringiensis, have been recognized as pioneer in the field and published since 2005.

 
Recently Prof Quintero is working on Data Assimiliation with cooperation with Prof. Arnold Heemink from Math-Phys Research group at Applied Mathematics Department in TU Delft.

 
-Multidimensional Signal Analysis in cooperation with Dr. Daniel Esteban Sierra-Sosa and Begoña García-Zapirain from e-Vida Laboratory from Universidad of Deusto in Spain, Natalia López from GATEME-UNSJ, Jaime Castro from Politécnico Grancolombiano and Instituto Tecnológico Metropolitano de Medellín ITM-ECOPETROL: 

 
Signal Analysis is an area of interest because its relevance in several applications. Currently, we are working on the development of new and improved techniques for Seismic Migration, specifically Reverse Time Migration (that uses the acoustic wave) and the use of Integral Transformations for condition imaging enhancement. Also, the use of Continuous Wavelet Transform (CWT) to obtain the singularity spectrum of a signal in order to identify several features to relate with the velocities field. Juan Guillermo Paniagua is currently her PhD Student in Mathematical Engineering. Now available a position for Master in Applied Mathematics student.

 
Andrés Yarce is a graduate student in Applied Physics that works understanding the phenomenon of ultrasonic wave propagation in an array of directional speakers in the framework of acoustic perception and study its features via signal processing analysis.

 
In the other hand, we are interested in the emotion recognition from biosignals such as Voice, EEG and faces through Multiresolution and Double Fourier Analysis which lead us to the Mathematical demonstration of a relationship between the singularity degree (obtained from the spectrum via CWT) and the level of decomposition of a signal in order to extract its relevant features. Alejandro Gómez-Montoya, Sebastián Castaño, Agustin Vargas-Toro are the Physical Engineering undergraduate students working of the EEG emotion recognition and artifact removal.

 
David Ortiz Puerta is currently the Master in Applied Mathematics graduate student working on image processing under the supervision of Daniel Siera-Sosa and Begoña García-Zapirain.

 
-Artificial Intelligence and Machine Learning in cooperation with John Hopcroft at Cornell

 
Out interest have been the fuzzy algorithms for clustering and their use for extraction information. Recently we have been developing strategies for information retrieval from unstructured/structured data through the modification of the preprocessing and processing techniques. Now we are looking for the use of Spectral clustering and the recently introduced Local Spectral clustering to extract the hidden information in networks and combine them with our algorithms.

 
Also, Neural Networks have been used for solve problems in several markets such as the energy and telecommunications, but now we are evolving to the Deep Learning algorithms in order to reach a better understanding of Deep Learning, and particularly, its applications to the classification of medical images that would be a valuable resource for current and future research projects. Not only study Deep learning looking for improvement in performance but also to understand Deep Neural Networks and develop learning algorithms. 

 
Jose Daniel Gallego-Posada and Diego Alejandro Montoya-Zapata as undergraduate students of Mathematical Engineering Program and Leandro Fabio Ariza as Graduate student from PhD in Mathematical Engineering want to gain understanding in Deep Learning in order to be qualified to attend Cornell’s Program for Research Experience on Deep Learning taught by Prof. John E. Hopcroft during summer 2016, as part of joint efforts to strengthen relationships between Cornell University and Universidad EAFIT.

 
Now available a position for Master in Applied Mathematics student for Deep learning image processing.

Estudios realizados / Education

  • ​​Doctorado en Ingeniería de Sistemas de Control, Universidad Nacional de San Juan (Argentina), 2009.
  • ​​Pregrado en Ingeniería Electrónica, Universidad San Francisco de Quito (Ecuador), 2008.​
  • Pregrado en Ingeniería de Control, Universidad Nacional de Colombia, 2003.​​

Publicaciones / Publications

• Quintero,O.L. Recognition and regionalization of emotions in the arousal-valence plane. Olga Lucía Quintero, Paola Bustamante, Natalia López Celani, Maria Elisa. Annual International Conference of the IEEE Engineering in Medicine and Biology – Proceedings ISSN 1557170.

 
• Quintero,O.L. Fuzzy inference system for modelling failure modes in a ropeway for massive transportation. Luisa F. Villa, O. L. Quintero Montoya, L. Castañeda, Gustavo Mejía. 2015 Global Conference on Artificial Intelligence (GCAI2015). WIT Transactions on Information and Communication Technologies (ISSN: 1743-3517.

• Quintero,O.L. Modeling perspective for the relevant market of voice services: Mobile to Mobile December 2015 O. Lucía Quintero, Fabian L. Jaramillo P., Manuela Bastidas O. Lucia Quintero Montoya*, (MASKANA, Vol. 6, No. 2) ISSN 1390-6143.

 
 Quintero,O.L.Dynamic Analysis of Emotions through Artificial Intelligence. Susana Mejía M+., Olga Lucía Quintero M+, Jaime Castro M* +Universidad EAFIT ,*Politécnico Grancolombiano. En Avances en Psicología Latinoamericana (http://revistas.urosario.edu.co/index.php/apl/index ) ISSN: 1794-4724.

 
• Quintero,O.L.Information retrieval on documents methodology based on entropy filtering methodologies. uisa F illa, Santiago unoz, Ana C. Ruiz Arenas and Manuela Bastidas Int. J. Business Intelligence and Data Mining, Vol. 10, No. 3, 2015 ISSN online: 1743- 8195 ISSN print: 1743-8187.

 
• Quintero,O.L.​ Multiresolution analysis (discrete wavelet transform) through Daubechies family for emotion recognition in speech. Journal of Physics: C S ISSN: 17426588, 17426596 D Campo, O L Quintero, M Bastidas.

 
• Quintero,O.L.​ Double Fourier Analysis for Emotion Identification in Voiced Speech* Journal of Physics: C S ISSN: 17426588, 17426596. D. Sierra-Sosa, M. Bastidas, D. Ortiz P., and O.L. Quintero.

 
• Quintero,O.L.​ An approach to emotion recognition in single-channel EEG signals: a mother child interaction. Journal of Physics: C S ISSN: 17426588, 17426596. A Gomez, L Quintero, N Lopez and J Castro.

 
• Quintero,O.L. A simple but efficient voice activity detection algorithm through Hilbert transform and dynamic threshold for speech pathologies. Journal of Physics: C S ISSN: 17426588, 17426596.

 
• Quintero,O.L. Collaborative Networked Virtual Surgical Simulators (CNVSS) Implementing Hybrid Client–Server Architecture: Factors Affecting Collaborative Performance. Christian Andres Diaz, Helmuth Trefftz, Olga Lucía Quintero, Diego A Acosta, Sakti Srivastava. Presence Teleoperators &amp Virtual Environments (Impact Factor: 0.73). 11/2014; 23(4):393-409. DOI: 10.1162/PRES_a_00208.
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Última modificación: 17/10/2017 11:22