of Science in Intelligent Systems

Professionals that deploy, adapt or propose models and techniques of AI to solve real world issues.

Curriculum: 2 years (4 semesters)



Technology trends in the modern world points toward the need for flexible, adaptable, and interactive computer systems. Artificial Intelligence (AI) is a technology generating area that is transforming society, economy and the environment with advances such as robots, human speaking systems, intelligent buildings and many others. The Master of Sciences in Intelligent Systems trains people in AI technologies which enables them to generate, adapt and apply innovative technology in the following:
• Productive sector: in a national or international company leader in the market
• Entrepreneurship: creating start ups that specialized in intelligent systems focused on logistics, robotics, and video games
• Academic environment: in research and technological development

The Master of Sciences in Intelligent Systems prepares professionals that master technologies and its applications in order to apply them in businesses and universities. The focus areas are: knowledge technologies, autonomous agents and ambient intelligence, evolutionary computer science, nature inspired systems, robotics, autonomous vehicles, and bioinformatics.

  • To train of people that create value in organizations through the application and development of AI techniques, interaction in multidisciplinary, and technological leadership
  • To generate and adapt knowledge and innovative technologies in AI through students’ research projects applied to products, processes or services
  • To strengthen countries technological capacity in state-of-the-art technology, such as AI, thereby combating technology dependence


Computer science professionals, such as interns, consultants, instructors or researchers that wish to develop or update their AI knowledge and techniques.

Professionals working in electronics, electrical, mechatronics, communications, mathematics, physics and other areas who wish to complement their training with AI.


Professionals that deploy, adapt or propose models and techniques of AI to solve real world issues. That estimate desirability of proposed to use AI techniques, as well as the possible impact in economy, society, environment, and ethics.

TC4000 Programming Techniques 3 0 12
3 0 12

GT4000 Research and Innovation Methods 1.5 0 6
IA4000 Intelligent Systems 3 0 12
OP4000 Quality Development Course 1.5 0 6
TC4001 Computing Fundamentals 3 0 12
9 0 36

IA4002 Uncertainty Systems 3 0 12
IA4004 Agent-Based Systems 3 0 12
IA4005 Robotics 3 0 12
9 0 36

GT5000 Thesis I 3 0 12
IA5005 Connectionist and Evolutionary Systems 3 0 12
OP5042 Elective I 3 0 12
9 0 36

GT5001 Thesis II 3 0 12
OP5043 Elective II 3 0 12
OP5044 Elective III 3 0 12
9 0 36

C Number of class hours per week
L Number of laboratory hours or activities per week
U Study hours that must be dedicated to the course (class hours included)

For more information here



Admission Test to Graduate Studies (PAEP)


  • Grade Point Average (GPA)
  • Admission Test to the Graduate Studies (PAEP) score
  • Resume
  • Essay
  • Recommendation Letter
  • Interview
  • TOEFL score

There are 100% scholarships for this program that can be awarded to academically outstanding students. The 100% scholarship tuition is offered at Campus Monterrey for full-time students without work commitments, for a maximum of four years taking complete curricular load. Additional expenses such as the admission exam payment, medical expenses insurance and the graduate degree expenditure shipping costs are not covered.


For further information contact:

Fabiola García Maldonado
+52 (81) 83582000 ext. 6011 o 5057

César Cabrera Torres
+52 (81) 83582000 ext. 5058 y 5059

International students, please contact:
Jenny Von Westphalen
+52 (81) 83582000 ext. 5097



Advancing Hyper-Heuristic Research for Solving Optimization Problems, basic science-CONACyT, (2015-2017), responsible: Hugo Terashima Marin

Development of hyper-heuristic methods using bio-inspired techniques for solving optimization issues such as: material cutting and packaging, constraint satisfaction, routing of vehicles, production and events scheduling and scheduling of events. The former issues have great theoretical and industrial impact.

Participants: Hugo Terashima Marín, Manuel Valenzuela Rendon, Santiago E. Conant Pablos and Jose Carlos Ortiz Bayliss, PHD students, masters and Bachelor Degree. Collaboration: U. of Nottingham (UK), U. of Stirling (UK), U. of Napier-Edinburgh (UK), IT de Leon.


Development of autonomous platforms with probabilistic reasoning, semantic, and causal (CB-2011-01-167460), responsible Hector Ceballos The project goal is to develop a simplify BDI agent architecture assist people in their daily activity. Human activity and agent intervention are modeled using BPMN process diagrams which are then semantically recorded. This activity allows a knowledge representation to exploit government data sources (Linked Data) for goal achievements.

The BPMN diagram is used for learning the dynamics of the activity through observation, as well as to infer probabilistically on the current situation of the activity. This development of applications methodology can be used in Intelligent Cities scenarios.

Participants: Hector G. Ceballos, Victor Flores Solorio (MIT), Eduardo Alejandro Fernandez (MIT), Jorge Espinosa (MIT), Manuel Rodriguez Mancha (DTC). Collaborators: Juan Pablo García (UABC)


  • Knowledge Technologies, Autonomous Actors and Ambient Intelligence, which examine issues related to automated handling of representing knowledge ontologies, coordination of intelligent autonomous entities, as well as the integration of intelligent environments that include multiple sensors and processors
  • Robotics, vision, and autonomous vehicles that study the design of land, sea, and air mobile robots and high-tech vehicles that use computational vision algorithms
  • Evolutionary Computation, studying evolutionary computation techniques such as genetic algorithms, simulated annealing and neural networks to efficiently resolve logistical problems – such as the task scheduling, routing, distribution, forecasts, cutting and packing of materials with less user intervention and bioinformatics (systems inspired by nature), which focuses on the design and identification of biomarkers in medicine and other areas, using molecular data including genomes and genes, proteins or metabolites, image data including x-rays, MRI, ultrasound, PET or TAC or clinical data, among others. In the analysis are used to design and implement computational algorithms of automatic learning, optimization, pattern recognition, image analysis and data mining.

For more information here


  • Project of Evolutionary Computation
  • Project of Autonomous Agents in Ambient Intelligence
  • Project of Autonomous Vehicles
  • Cell of Incubation
  • Detection and Remote Pre-Diagnosis of Cancer by Artificial Intelligence
  • Incubation Cell AMITEC
  • Safety System for Ambient Intelligence
  • Robotics Laboratory of the Northeastern and Central Mexico



  • Basic Science Project with Conacyt 128163
  • Use of Frames to Convert Text to Semantic Networks
  • Robotics Laboratory of the Northeastern and Central Mexico
  • Project Conacyt – Combinations of Evolutionary Computation and Other Techniques to Solve Problems of Material Cut and Data Mining in Image Databases
  • Project Conacyt – Working Towards the Generality of Hyper-Heuristics for Optimization Problems



  • Project Google – Remote Detection and Prediagnosis of Microcalcification Clusters in Mammograms
  • Project Laccir – Building a Database of Researchers in Latin America and the Caribbean


Generation Total
January 2003 7
August 2003 4
January 2004 6
August 2004 10
January 2005 7
August 2005 1
January 2006 3
August 2006 3
January 2007 3
August 2007 9
January 2008 4
August 2008 6
January 2009 5
August 2009 7
January 2010 4
August 2010 6
January 2011 6
August 2011 10
January 2012 4
August 2012 5
January 2013 6
August 2013 2
January 2014 3

Please download the information here



  • Ramón Felipe Brena Pinero
  • Francisco Javier Cantú Ortiz
  • Héctor Gibrán Ceballos Cancino
  • Santiago Conant Pabios
  • José Luis Gordillo Moscoso
  • Ernesto Rodríguez Leal
  • José Tamez Peña
  • Hugo Terashima Marín
  • Víctor Treviño Alvarado
  • Manuel Valenzuela Ramón

More Information

Ramón Felipe Brena Pinero
+52 (81) 83582000 ext. 5246