About

Octavio Loyola-González received his PhD degree in Computer Science from the National Institute for Astrophysics, Optics, and Electronics, Mexico. He has won several awards from different institutions due to his research work on applied projects; consequently, he is a Member of the National System of Researchers in Mexico (Rank1). He worked as a distinguished professor and researcher at Tecnologico de Monterrey, Campus Puebla, for undergraduate and graduate programs of Computer Sciences. He was Managing Director for Altair Management Consultants, having branches in USA, UK, Spain, and Mexico; where he was leading several teams of data scientists for AI & ML, Business Intelligence reporting, and traditional consulting. Currently, he is responsible for running advanced analytics practice inside NTT Data., where he is involved in the development and implementation using Artificial Intelligence and Generative AI. He has outstanding experience in the fields of big data & pattern recognition, cloud computing, IoT, and analytical tools to apply them in sectors where he has worked for as Automotive, Manufacturing, Real estate, Infrastructure, Banking & Insurance, Retail, Oil&Gas, Agriculture, Cybersecurity, Biotechnology, and Dactyloscopy. From these applied projects, Dr. Loyola-González has published several books and papers in well-known journals, and he has several ongoing patents as manager and researcher in NTT Data.

Statistics: 75+ research articles | 2000+ citations | 45+ AI projects | 20+ events as organizing committee | Managing several people in different countries | 20 years applying ML & AI

Main Honors & Awards: Mexican Researchers System (CONACyT, Mexico) | Distinguished Professor (Tecnologico de Monterrey) | Best Thesis Award for Doctoral Thesis Category on Artificial Intelligence (SMIA, Mexico) | Annual Award (Cuban Academy of Sciences).

Work Experience (20 years applying AI)

Apr. 2024 - Now

NTT Data
Artificial Intelligence Executive Consulting Manager

Currently, I'm an AI Executive Consulting Manager at NTT Data. Additionally, I'm responsible for bringing in clients from 🚗automotive, 🦾manufacturing, 🏠real estate, 🏗️infrastructure, and 💼services sectors for closing deals related to Advanced Analytics and Artificial Intelligence. I also assist my colleagues in managing clients from various other sectors including 🏦banking & insurance, 🏪retail & consumer packaged goods, 🔋energy & utilities, 📺telecommunications & media, 🛩️travel & hospitality, and the 🏛️public sector for applying Machine Learning approaches. I'm responsible for overseeing the operations and activities of my team of data scientists (about 100), guiding them on an optimum and accurate path, both technically and in terms of business strategy. Furthermore, I am actively involved in publishing scientific papers and books in reputable journals to promote advancements in AI research.

Sep. 2022 - Mar. 2024

Stratesys
Artificial Intelligence Executive Manager

As an AI executive manager, I was responsible for overseeing the operations and activities of my team of data scientists and guiding them on an optimum and accurate path. A few of my primary duties as an executive manager was dealing with projects and closing deals with customers from different sectors, such as 🏦 Banking & Financial, 🏪 Retail & CPG, 🪫Energy & Utilities, 📺 Telco & Media, 🛩️ Travel & Hotels and 🏠 Real Estate, among others. I was also required for developing long-term goals for the department, implementing department wide policies, allocating department resources, ensuring that the department budget is being met, giving constructive feedback to employees, and collaborating with others departments. Also, I was reporting the department's progress to upper management. As part of my strategy for growing Stratesys, I have taught data scientists to be experts in different machine learning areas. Also, I continued publishing several scientific papers and books in well-known journals to promote Stratesys's scientific advances.

Feb. 2022 - Sep. 2022

Altair Management Consultants
Managing Director (CEO)

I was dedicated to the day-to-day operations of Altair's projects for closing deals and attract new customers. Besides, I was overseeing and guiding other Altair managers (4 managers and 25 workers) on different areas, such as Artificial Intelligence, Data Analytic, Process Mining, and Business Intelligence. Several applied projects were executed on different sectors, such as Banking & Financial, Retail & FMCG, Energy, Oil & Gas, and Automotive.

Feb. 2021 - Feb. 2022

Altair Management Consultants
Artificial Intelligence Manager

I was responsible for running Machine Learning & Artificial Intelligence practice inside Altair Management Consultants, where I was involved in the development and implementation using analytics and data mining in the Altair Compass department. Currently, I was applying outstanding machine learning approaches to important sectors as Banking & Insurance, Retail, Oil & Gas, Agriculture, Cybersecurity, Biotechnology, and Criminalistics. I was publishing several books and papers in well-known journals and obtaining several patents as manager and researcher in Altair Compass.

Sep. 2018 - Feb. 2021

Tecnologico de Monterrey
Professor Researcher

I was a distinguished professor and researcher at Tecnologico de Monterrey (Campus Puebla) for undergraduate and graduate programs of Computer Sciences. My research was focused on development of algorithms for: 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, and Latent fingerprint and palmprint identification. I taught the following courses: Motion Modeling in Bioengineering and Chemical Process (August-December, 2019-2020) Intelligent Systems (January-December, 2019 and August-December, 2020) Web applications development (January-May, 2018-2019) Web applications development laboratory (August-December, 2018) Computational Approaches for Machine Learning; How to compare the performance of classifiers over multiple datasets? (September, 2017)

May. 2017 - Jan. 2018

Tecnologico de Monterrey
Senior AI Scientist

Head researcher for the project: Dynamic Networks and Metrics for Ad Efficiency Ratings. My research was focused on click-fraud detection, bot detection, and studying about metrics for Ad efficiency ratings. We develop a software that fusing approaches of pattern discovery and visual analytics on web logs for detecting human and bot traffic in web sites.

Jan. 2007 - Dec. 2010

Crime Laboratory
Senior AI Scientist

Software development and researchs for creating Automated Fingerprint Identification System (AFIS) and Ultraviolet spectra identification (AUVIS)

Jan. 2005 - Aug. 2013

Centro de Bioplantas
Research Applied Scientist

Software development and researchs for pattern recognition problems such as data mining, fingerprint recognition, clustering, supervised classification, decision trees induction and class imbalance datasets. - C#, JavaScript and ASPX programming. - SQL Databases. - Resampling Methods. - Cost-sensitive. - Algorithms Modification. - Imbalanced Databases. http://www.bioplantas.cu (website link)

Education

Feb. - Aug. 2018

Postdoctoral
Postdoctoral Fellow

Tecnologico de Monterrey

My research was focused on development of algorithms based on patterns for bot detection. For doing that, I was creating a data mining framework based on C# language. For this research, the contributions were: (i) Mining contrast patterns for bot detection and (ii) Supervised classifiers based on contrast patterns for bot detection.

Aug. 2013 - Oct. 2017

Ph.D. Degree
Ph.D. in Computer Science

Instituto Nacional de Astrofíica, Óptica y Electrónica (INAOE)

My research was focused on development of algorithms based on contrast patterns for class imabalance problems. Best Thesis Award "José Negrete" for the Doctoral Thesis Category on Artificial Intelligence sponsored by the Mexican Society for Artificial Intelligence (SMIA). Prize winner in the XXXI National Contest of Computer Science Thesis (ANIEI). Prize winner to the best PhD Thesis in the Computer Science Coordination at Instituto Nacional de Astrfofísica, Óptica y Electrónica. This PhD research allowed obtaining 6 JCR, 4 LNCS, and 1 technical report.

Sep. 2010 - Nov. 2012

Master's Degree
Master in Applied Computing

University of Ciego de Ávila

Graduated with Honors in Applied Informatics (First class honours). My academic score was 4.6 (max 5). My Thesis was about a framework for fingerprint recognition. In the framework was included several algorithms for fingerprint matching and feature extraction, as well as the evaluation protocol for several fingerprint verification competitions.

Sep. 2004 - Jul. 2010

Engineer's Degree
Computer Engineer

University of Ciego de Ávila

Graduated with Honors of Engineer in Informatics (First class honours). My academic score was 4.96 (max 5) and I got Rector's Prize for Best Graduate at University of Ciego de Ávila. My Thesis was about a new algorithm to induction decision trees based on a cluster quality measure.

Sep. 2000 - Jul. 2002

Associate Degree
Associate Degree in Accounting

IP: "Pablo Elvio Pérez Cabrera"

Graduated with Honors in Accounting, Finance, and Audit.

Publications
Student Collaborators

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 Process Mining, Cybersecurity, Biometrics, AI, XAI, ML, DL, PR applied to real-world problems, such as Banking & Insurance, Retail, Oil&Gas, Agriculture, Cybersecurity, Biotechnology, and Dactyloscopy . To see what types of problems he is working, please visit the list of my publications or see above his research interests. Currently, Loyola-González has advised and continuous as advisor of several undergraduate and postgraduate students.ñ

PhD Students:

  • [Collaborating, 2021-2025] -> Javad Khodadoust, Student in Progress. Research topic: A minutiae-based indexing algorithm for latent palmprints.
  • [Co-Advisor, 2019-2023] -> Luis Daniel Samper Escalante, Student in Progress. Research topic: Graph-based Classification for Bot Detection on Twitter.
  • [Collaborating, 2019-2023] -> Ismay Pérez Sánchez, Student in Progress. Research topic: Fuzzy clustering.

MSc Students:

  • [Advisor, 2020-2022] -> Gabriel Ichcanziho Pérez Landa, Graduate Student. Research topic: An explainable artificial intelligence model for detecting xenophobic Tweets.
  • [Co-Advisor, 2020-2022] -> Edwin Montiel Vázquez, Graduate Student. Research topic: Detecting Empathy on textual communication.
  • [Co-Advisor, 2020-2022] -> Ernesto Ramírez Sáyago, Graduate Student. Research topic: Combining measures for assessing split candidates in decision tree induction.
  • [Co-Advisor, 2020-2022] -> Dachely Otero Argote, All But Dissertation. Research topic: A novel autoencoder proposal based on deep regressors for anomaly detection.
  • [Advisor, 2020-2022] -> Guillermo Soto Gómez, All But Dissertation. Research topic: Generative adversarial networks for improving the quality of latent fingerprints.
  • [Advisor, 2019-2021] -> Leslie Marjorie Gallegos Salazar, Graduate Student. Research topic: Contrast Pattern-based Classification on Sentiment Features for Detecting People with Mental Disorders on Social Media.
  • [Co-Advisor, 2019-2021] -> Diana Laura Aguilar Cervantes, Graduate Student. Research topic: An Interpretable Autoencoder for Semi-Supervised Anomaly Detection.
  • [Advisor, 2019-2021] -> Michael Alexander Zenkl Galaz, All But Dissertation. Research topic: An Interpretable Outlier Generation-based Outlier Detector for Categorical Databases.

Undergraduate Students:

  • [Advisor, Feb. - Jun., 2020] -> Ernesto Ramírez Sáyago, Graduate Student. Research topic: Developing contrast pattern-based classifiers for one-class and multi-class classification.
  • [Advisor, Aug. - Dec., 2019] -> Ernesto Ramírez Sáyago, Graduate Student. Research topic: Deep Learning model for denoising and inpainting latent fingerprints.
  • [Advisor, Jan. - May., 2019] -> Angel Roberto Ruíz Mendoza, Graduate Student. Research topic: Fuzzy decision tree-based Classification.
  • [Advisor, Jan. - May., 2019] -> Carlos Augusto Amador Manilla, Graduate Student. Research topic: Fuzzy decision tree-based Classification.
  • [Co-advisor, Aug. - Dec., 2018] -> Ian Fernando Neumann Sánchez, Graduate Student. 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. Graduate Student. Research topic: A review of evaluation measures for node splitting criteria in decision tree induction.
  • [Postdoctoral Fellow, 2017-2019] -> Jorge Rodríguez Ruiz, PhD. Graduate Student. Research topic: Latent Palmprint Identification.
  • [Msc, 2017-2019] -> Ismay Pérez Sánchez, Msc. Graduate Student. Research topic: Latent Fingerprint Indexing.
  • [Msc, 2017-2018] -> Leonardo Mauricio Cañete Sifuentes, Msc. Graduate Student. Research topic: Classification Based on Multivariate Contrast Patterns.
  • [PhD, 2017-2018] -> Danilo Valdes Ramirez, Graduate Student. Research topic: Latent Fingerprint Identification.