Octavio Loyola-González, PhD.                                                                                                                                                                             

Research/Professor at Tecnologico de Monterrey.

Building 2, level 5, Office 2506-L.
Inter-Campus: 80783 3183
e-mail: octavioloyola [at] tec [dot] mx

School of Engineering and Sciences
Tecnologico de Monterrey, Campus
Puebla.

Vía Atlixcáyotl No. 2301, Reserva Territorial Atlixcáyotl,
Puebla, Puebla, 72453, Mexico.
ORCID Researchgate Linkedin scopus scholar
                
Dr. Octavio Loyola-González received his B.Eng. in Informatics Engineering in 2010 and his M.Sc. degree in Applied Informatics in 2012, both from University of Ciego de Ávila. After, he received his PhD degree in Computer Science from the National Institute for Astrophysics, Optics and Electronics, Mexico, in 2017. He received the Best Thesis Award “José Negrete” for the Doctoral Thesis Category on Artificial Intelligence sponsored by the Mexican Society for Artificial Intelligence (SMIA). Prizewinner in the XXXI National Contest of Computer Science Thesis (ANIEI). Prizewinner to the best PhD Thesis in the Computer Science Coordination at National Institute of Astrophysics, Optics and Electronics. Currently, he is a Research Professor at Tecnologico de Monterrey (Campus Puebla) for undergraduate and graduate programs of Computer Sciences. Also, he is a member of the GIEE-ML (Machine Learning) research group at the Tecnologico de Monterrey, and the GIARP Group. These groups are devoted to research on pattern recognition, where we have developed a fingerprint verification framework and a data mining framework. Currently, he is a Member of the Mexican Researchers System (Rank 1).

Dr. Loyola-González has been involved in many research projects about pattern recognition, which have been applied on biotechnology and dactyloscopy problems, and he has published several papers in referenced journals. Also, he has won several awards from different institutions due to his research work. His current research is focused on development of algorithms based on contrast patterns for fuzzy problems as well as new minutiae-based descriptors by using deep learning.


His research interests are: Publications
  • eXplainable Artificial Intelligence (XAI)
  • Contrast and Fuzzy pattern-based classification
  • Generative adversarial networks (GANs)
  • Bot detection on social media
  • People behavior on social networks
  • Data mining and knowledge discovery
  • Pattern-based One-class classification
  • Class imbalance problems
  • Latent fingerprint and palmprint identification
Besides publishing the research on top-ranked journals and conference, he has decided to accompany the manuscript with the source code that implements the idea presented. The objective is to facilitate the replication process needed in any research work. For more information, visit his List of publication for obtaining the supplementary materials of each one.

 Prospective postgraduate students
Loyola-González's office's door is always open to motivated individuals, particularly those with excellent academic records (and publication track record), who are interested in researching on Contrast Pattern-based Classification, Data Mining, Class Imbalance Problems, Bot Detection, Cyber Security, and Biometrics. To see what types of problems he is working, please visit "List of My Publications" or see above his research interests.

It is important to highlight that for postgraduate students there are available CONACyT scholarships at the Tecnologico de Monterrey; for more information, please come to the Loyola-González's office or write him an email to
octavioloyola [at] tec [dot] mx.

Since joining the Tecnologico de Monterrey in May 2017, Loyola-González has advised and continuous as advisor of several undergraduate and postgraduate students.

PhD Students:
  • [Advisor, 2019-2023] > Luis Daniel Samper Escalante, Student in Progress. Research topic: Graph-based Classification for Bot Detection on Twitter.
  • [Advisor, 2019-2023] > Ismael Lin Esperanza, Student in Progress. Research topic: Fuzzy pattern-based classification.
  • [Collaborating, 2019-2023] > Ismay Pérez Sánchez, Student in Progress. Research topic: Fuzzy clustering.

MSc Students:
  • [Advisor, 2020-2022] > Guillermo Soto Gómez, Student in Progress. Research topic: Generative adversarial networks for improving the quality of latent fingerprints.
  • [Advisor, 2020-2022] > Gabriel Ichcanziho Pérez Landa, Student in Progress. Research topic: Contrast pattern classification for detecting xenophobia in social networks.
  • [Advisor, 2019-2021] > Michael Alexander Zenkl Galaz, Student in Progress. Research topic: Generative adversarial networks for oversampling data on class imbalance problems.
  • [Advisor, 2019-2021] > Leslie Marjorie Gallegos Salazar, Student in Progress. Research topic: Contrast pattern-based classification on sentiment features for detecting people with mental disorders on social Networks.
  • [Co-Advisor, 2020-2022] > Edwin Montiel Vázquez, Student in Progress. Research topic: Detecting sentiments and emotions from chat.
  • [Co-Advisor, 2019-2021] > Mario Alberto Mendoza Cuevas, Student in Progress. Research topic: Multinational and multi-center study for the Inception Cohort in Latin American patients suffering from Juvenile Idiopathic Arthritis (JIA).
  • [Co-Advisor, 2019-2021] > Diana Laura Aguilar Cervantes, Student in Progress. Research topic: White-box autoencoder for anomaly detection.
Undergraduate Students:
  • [Advisor, Feb. - Jun., 2020] > Ernesto Ramírez Sáyago, Student in Progress. Research topic: Developing contrast pattern-based classifiers for one-class and multi-class classification.
  • [Advisor, Aug. - Dec., 2019] > Ernesto Ramírez Sáyago, Student in Progress. Research topic: Deep Learning model for denoising and inpainting latent fingerprints.
  • [Advisor, Jan. - May., 2019] > Angel Roberto Ruíz Mendoza, Student in Progress. Research topic: Fuzzy decision tree-based Classification.
  • [Advisor, Jan. - May., 2019] > Carlos Augusto Amador Manilla, Student in Progress. Research topic: Fuzzy decision tree-based Classification.
  • [Co-advisor, Aug. - Dec., 2018] > Ian Fernando Neumann Sánchez, Student in Progress. Research topic: One-class Classification based on contrast patterns.
In addition, Loyola-González has helped to train some students through his support as a collaborator.

  • [Postdoctoral Fellow, 2018-2019] > Víctor Adrián Sosa Hernández, PhD. Graduated Student. Research topic: A review of evaluation measures for node splitting criteria in decision tree induction.
  • [Postdoctoral Fellow, 2017-2019] > Jorge Rodríguez Ruiz, PhD. Graduated Student. Research topic: Latent Palmprint Identification.
  • [Msc, 2017-2019] > Ismay Pérez Sánchez, Msc. Graduated Student. Research topic: Latent Fingerprint Indexing.
  • [Msc, 2017-2018] > Leonardo Mauricio Cañete Sifuentes, Msc. Graduated Student. Research topic: Classification Based on Multivariate Contrast Patterns.
  • [PhD, 2017-2018] > Danilo Valdes Ramirez, Msc. Student in Progress. Research topic: Latent Fingerprint Identification.