The event

The Mexican Congress of Artificial Intelligence is organized by the Mexican Society of Artificial Intelligence ( SMIA ) and is promoted as a serious scientific forum for the presentation and publication of research papers derived from theses or projects, completed or in process, in Spanish.

Articles must be submitted online using the system  EasyChair :  https://easychair.org/conferences/?conf=comia2018

Submitted papers must be submitted with content on significant, original and previously unpublished research in all areas of artificial intelligence, whether research or applications.

Papers must be submitted without names of the authors, affiliation and / or self-references to perform a double blind review. When presenting an article, it is assumed that at least one author will register for the conference and present the accepted work or, if applicable, a poster. The registration fee will be paid in full for each of the items that are accepted. It is also planned to have workshops, contests and tutorials within the framework of the conference.

Download Call for Papers (here)

The event

Mexican Congress of  

Artificial Intelligence 2018

5 to 8  June, Yucatan, Mexico.

  • Sistemas expertos y sistemas basados en conocimientos

  • Representación y Manejo del Conocimiento

  • Adquisición del Conocimiento

  • Sistemas Multi-agente y IA distribuida

  • Organizaciones Inteligentes

  • Procesamiento del Lenguaje Natural

  • Ontologías

  • Interfaces Inteligentes: Multimedia, Realidad Virtual

  • Visión por Computador y Procesamiento de Imágenes

  • Redes Neuronales

  •  Algoritmos Genéticos

  • Lógica Difusa

  • Aprendizaje Automático

  • Reconocimiento de Patrones

  • Revisión de creencias

  • Razonamiento cualitativo

  • Incertidumbre y Razonamiento Probabilístico

  • Razonamiento basado en modelos

  • Razonamiento No-monótono

  • Razonamiento del Sentido Común

  • Razonamiento Basado en Casos

  • Razonamiento Espacial y Temporal

  • Programación con Restricciones

  • Programación de la lógica

  • Demostración de Teoremas Automatizada

  • Robótica

  • Planificación y Programación

  • Sistemas Inteligentes Híbridos

  • Bioinformática y Aplicaciones Médicas

  •  Cuestiones Metodológicas y Filosóficas de la IA

  •  Sistemas de tutorías inteligente

  • Minería de datos

  •  Aplicaciones

Topics

DATES

April 20th  Limit for receipt of articles  
 

April 30th Notification of admitted articles

May 7th    Limit for receipt of final versions

May 18  Author registration closure and payment limit

Authors $ 3,000.00

  • Includes publication in the journal "Research in Computing Science" (indexed in Latindex and DBLP

  • Access to plenary conferences

  • Access to thematic sessions

  • Welcome cocktail

  • Gala dinner

Professionals $ 1,000.00

  • Access to plenary conferences

  • Access to thematic sessions

Students $ 250.00

  • Access to plenary conferences

  • Access to thematic sessions

COSTS

Program

Venues

  • Polytechnic University  from Yucatan

  • José Peón Contreras Theater

  • Hacienda Anicabil

Cultural activities

  • Visit to the GMMM * (info)

  • Dinner in the park of Santa Lucía ** ( directory)

  • Saint Lucia Serenade

  • Tour to ZA Uxmal *

* activity with cost

** requires prior reservation

 

Detailed Program  (download)

Speakers

Intelligent and Affective Systems in Education

Maria Lucia Barron Estrada

PhD in Computer Science

National Technological Institute of Mexico / Technological Institute of Culiacán

Artificial Intelligence (AI) has significantly impacted various areas of human endeavor and one of the most benefited areas has been Education with the incorporation of various tools and technologies that help to improve the teaching-learning process by considering cognitive and emotional aspects of the students.

This talk presents an overview of the different technologies for learning such as Intelligent Tutor Systems (STI) or Intelligent Learning Environments (EIA) that include various mechanisms for emotion recognition, in order to personalize teaching to the needs cognitive and affective of the students. The creation of emotion recognition systems that use different methods to capture signals through various devices and process them with different classifiers in order to determine the affective state of students will be described. In addition, the integration of the emotion recognition module with learning systems in order to generate Intelligent and Affective Systems will be presented.

Artificial Intelligence for Industry 4.0

Luis Alberto Muñoz Ubando

PhD in Imaging, Vision and Robotics

Southeast Regional President and National VP of Innovation of Canieti

The success of artificial intelligence techniques and algorithms for the development of applications and practical solutions  They have been opening new controversial spectra about the possible risks of unemployment in the most industrialized economies, however, and even with the enormous space facilities (Cloud) and massive processing (HPC),  they make fully automated solutions still an untenable fantasy.

On the other hand, these same facilities have allowed techniques considered ancestral to have nowadays a margin  important application, especially those related to machine learning, deep, supervised  and unsupervised.

 

But what is there beyond being able to tell the difference between a raisin muffin and a canine? The new business models  require that we strongly support the development of talent in our country, raising us in a relevant way  to the use of new technologies, but we must also innovate.  

In this presentation we will talk about the new aspects in the area of AI for the so-called Industry 4.0, we will analyze  computational complexities inherent in current methods and we will try to identify new and realistic areas  of colaboration.

Computational Linguistics

Gerardo E. Sierra Martínez 

PhD in Linguistics  Computational

National Autonomous University of Mexico, Institute of Engineering 

Leader of the Linguistic Engineering Group. Doctor in Computational Linguistics from the University of Manchester, England. His areas of interest focus on computational lexicography, terminotics, conceptual extraction, linguistic corpus, text mining, and forensic linguistics.

 

He is the author of the book “Introduction to linguistic corpus”, co-author of the books “Treatment of textual information and generation of taxonomies” and “Computational linguistics in Mexico: Research and development”, and has published more than one hundred articles in magazines, chapters of refereed conference books and articles. 

Speakers

Intelligent and Affective Systems in Education

Maria Lucia Barron Estrada

PhD in Computer Science

National Technological Institute of Mexico / Technological Institute of Culiacán

Artificial Intelligence (AI) has significantly impacted various areas of human endeavor and one of the most benefited areas has been Education with the incorporation of various tools and technologies that help to improve the teaching-learning process by considering cognitive and emotional aspects of the students.

This talk presents an overview of the different technologies for learning such as Intelligent Tutor Systems (STI) or Intelligent Learning Environments (EIA) that include various mechanisms for emotion recognition, in order to personalize teaching to the needs cognitive and affective of the students. The creation of emotion recognition systems that use different methods to capture signals through various devices and process them with different classifiers in order to determine the affective state of students will be described. In addition, the integration of the emotion recognition module with learning systems in order to generate Intelligent and Affective Systems will be presented.

Artificial Intelligence for Industry 4.0

Luis Alberto Muñoz Ubando

PhD in Imaging, Vision and Robotics

Southeast Regional President and National VP of Innovation of Canieti

The success of artificial intelligence techniques and algorithms for the development of applications and practical solutions  They have been opening new controversial spectra about the possible risks of unemployment in the most industrialized economies, however, and even with the enormous space facilities (Cloud) and massive processing (HPC),  they make fully automated solutions still an untenable fantasy.

On the other hand, these same facilities have allowed techniques considered ancestral to have nowadays a margin  important application, especially those related to machine learning, deep, supervised  and unsupervised.

 

But what is there beyond being able to tell the difference between a raisin muffin and a canine? The new business models  require that we strongly support the development of talent in our country, raising us in a relevant way  to the use of new technologies, but we must also innovate.  

In this presentation we will talk about the new aspects in the area of AI for the so-called Industry 4.0, we will analyze  computational complexities inherent in current methods and we will try to identify new and realistic areas  of colaboration.

Computational Linguistics

Gerardo E. Sierra Martínez 

PhD in Linguistics  Computational

National Autonomous University of Mexico, Institute of Engineering 

Leader of the Linguistic Engineering Group. Doctor in Computational Linguistics from the University of Manchester, England. His areas of interest focus on computational lexicography, terminotics, conceptual extraction, linguistic corpus, text mining, and forensic linguistics.

 

He is the author of the book “Introduction to linguistic corpus”, co-author of the books “Treatment of textual information and generation of taxonomies” and “Computational linguistics in Mexico: Research and development”, and has published more than one hundred articles in magazines, chapters of refereed conference books and articles. 

How the Cloud is Creating Massive Data Sets which make Enterprise Machine Learning interesting

Ing. José Luis Valerio & Oracle specialists

Oracle Autonomous Database Director

A challenge for Machine Learning is having enough clean data to do interesting things.  Now that many enterprises are running their systems on Enterprise Clouds, we have some unique opportunity to build real existing solutions using the meta-data existing in these environments.

From building databases that can manage and tune themselves, to increasing system availability from faults, to having recruiting systems that are intelligent to route candidates to the managers who have the positions that are the best fit. This session will cover how ML is transforming how we deliver enterprise systems, and introduce some of the fun challenges of doing a math focused coding career.

Similarity, Correlation and Association Measures in Data Science

Ildar Batyrshin

PhD 

Computer Research Center (CIC), IPN

Last years it is significantly increased the number of works on similarity, correlation and association measures as descriptive measures of relationship, interestingness, dependency and resemblance in data mining, data analysis, classification and machine learning. The methods of construction of similarity, correlation and association measures for different types of data are considered. The methods of 3D visualization of some families of similarity and correlation measures are presented.