Artificial Intelligence Executive Manager
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).
Apr. 2024 - Now
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
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
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
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
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
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
Software development and researchs for creating Automated Fingerprint Identification System (AFIS) and Ultraviolet spectra identification (AUVIS)
Jan. 2005 - Aug. 2013
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)
Feb. - Aug. 2018
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
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
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
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
IP: "Pablo Elvio Pérez Cabrera"
Graduated with Honors in Accounting, Finance, and Audit.
- Botnet Identification on Twitter: A Novel Clustering Approach based on Similarity, IEEE Access, 2024.
- Towards improving decision tree induction by combining split evaluation measures, Knowledge-Based Systems, 2023.
- Process mining: software comparison, trends, and challenges, International Journal of Data Science and Analytics, 2022.
- Special issue on artificial intelligence-based techniques and applications for intelligent IoT systems, Neural Computing and Applications, 2022.
- An Explainable Artificial Intelligence Approach for Detecting Empathy in Textual Communication, Applied Sciences, 2022.
- A secure and robust indexing algorithm for distorted fingerprints and latent palmprints, Expert Systems with Applications, 2022.
- Towards an interpretable autoencoder: A decision-tree-based autoencoder and its application in anomaly detection, Transactions on Dependable and Secure Computing, 2022.
- IOGOD: An Interpretable Outlier Generation-based Outlier Detector for Categorical Databases, Expert Systems With Applications, 2022.
- Blockchain-based online education content ranking, Education and Information Technologies, 2021.
- An Explainable Approach Based on Emotion and Sentiment Features for Detecting People with Mental Disorders on Social Networks, Applied Sciences, 2021.
- An Explainable Artificial Intelligence Model for Detecting Xenophobic Tweets, Applied Sciences, 2021.
- PBC4occ: A novel contrast pattern-based classifier for one-class classification, Future Generation Computer Systems, 2021.
- An Indexing Algorithm Based on Clustering of Minutia Cylinder Codes for Fast Latent Fingerprint Identification, IEEE Access, 2021.
- Impact of Minutiae Errors in Latent Fingerprint Identification: Assessment and Prediction, Applied Sciences, 2021.
- A Review of Fuzzy and Pattern-Based Approaches for Class Imbalance Problems, Applied Sciences, 2021.
- Bot Datasets on Twitter: Analysis and Challenges, Applied Sciences, 2021.
- Semi-supervised anomaly detection algorithms: A comparative summary and future research directions, Knowledge-Based Systems, 2021.
- A practical tutorial for decision tree induction: evaluation measures for candidate splits and opportunities, ACM Computing Surveys, 2021.
- A One-Class-Classification Approach to Creating a Stress-level Curve Plotter through Wearable Measurements and Behavioral Patterns, International Journal on Iteractive Design and Manufacturing, 2021.
- A contrast pattern-based scientometric study of the QS world university ranking, IEEE Access, 2020.
- A Review of Supervised Classification based on Contrast Patterns: Applications, Trends, and Challenges, Journal of Grid Computing, 2020.
- An Explainable Artificial Intelligence Model for Clustering Numerical Databases, IEEE Access, 2020.
- A one-class classification approach for bot detection on Twitter, Computers & Security, 2020.
- Cluster validation in clustering-based one-class classification, Expert Systems, 2019.
- Black-box vs. white-box: understanding their advantages and weaknesses from a practical point of view, IEEE Access, 2019.
- Pattern-Based and Visual Analytics for Visitor Analysis on Websites, Applied Sciences, 2019.
- Bagging-RandomMiner: A One-class classifier for file accesses-based masquerade detection, Machine Vision and Application, 2019.
- Cost-sensitive pattern-based classification for class imbalance problems, IEEE Access, 2019.
- Classification based on multivariate contrast patterns, IEEE Access, 2019.
- A survey on minutiae-based palmprint feature representations, and a full analysis of palmprint feature representation role in latent identification performance, Expert Systems With Applications, 2019.
- A review of fingerprint feature representations and their applications for latent fingerprint identification: Trends, and evaluation, IEEE Access, 2019.
- Contrast Pattern-based Classification for Bot Detection on Twitter, IEEE Access, 2019.
- A pattern-based approach for detecting pneumatic failures on temporary immersion bioreactors, Sensors, 2019.
- Fusing Approaches of Pattern Discovery and Visual Analytics on Tweet Propagation, Information Fusion, 2019.
- Evaluation of quality measures for contrast patterns by using unseen objects, Expert Systems with Applications, 2017.
- PBC4cip: A New Contrast Pattern-based Classifier for Class Imbalance Problems, Knowledge-Based Systems, 2017.
- Effect of Class Imbalance on Quality Measures for Contrast Patterns: An Empirical Study, Information Sciences, 2016.
- Study of the impact of resampling methods for contrast pattern based classifiers in imbalanced databases, Neurocomputing, 2016.
- Latent fingerprint identification using deformable minutiae clustering, Neurocomputing, 2016.
- Identification of Discriminant Factors after Exposure of Maize and Common Bean Plantlets to Abiotic Stresses, Not Bot Horti Agrobo, 2015.
- Inducing Decision Trees based on a Cluster Quality Index, IEEE Latin America Transactions, 2015.
- An Empirical Comparison among Quality Measures for Pattern Based Classifiers, Intelligent Data Analysis, 2014.
- Integrated criteria to identify the best treatment in plant biotechnology experiments, Acta Physiologia Plantarum, 2013.
- Enhancing latent palmprints using frequency domain analysis, Intelligent Systems with Applications, 2024.
- A novel indexing algorithm for latent palmprints leveraging minutiae and orientation field, Intelligent Systems with Applications, 2024.
- A Novel Survival Analysis-Based Approach for Predicting Behavioral Probability of Default, Lecture Notes in Computer Science, 2022.
- Single and Multiple Imputation Techniques to Treat Missing Numerical Variables (MNV) in Perspectives of Data Science Project - A Case Study, International Journal of Engineering Trends and Technology, 2022.
- Towards inpainting and denoising latent fingerprints: a study on the impact in latent fingerprint identification, Lecture Notes in Computer Science, 2020.
- Image Annotation as Text-Image Matching: Challenge Design and Results, Computación y Sistema, 2019.
- Understanding the criminal behavior in Mexico city through an explainable artificial intelligence model, Lecture Notes in Computer Science, 2019.
- The Mexican Conference on Pattern Recognition after ten editions: A scientometric study, Lecture Notes in Computer Science, 2019.
- An approach based on contrast patterns for bot detection on web log files, Lecture Notes in Computer Science, 2018.
- A Novel Contrast Pattern Selection Method for Class Imbalance Problems, Lecture Notes in Computer Science, 2017.
- Detecting Pneumatic Failures on Temporary Immersion Bioreactors, Lecture Notes in Computer Science, 2016.
- Correlation of Resampling Methods for Contrast Pattern Based Classifiers, Lecture Notes in Computer Science, 2015.
- Introducing an Experimental Framework in C# for Fingerprint Recognition, Lecture Notes in Computer Science, 2014.
- Comparing Quality Measures for Contrast Pattern Classifiers, Lecture Notes in Computer Science, 2013.
- An Empirical Study of Oversampling and Undersampling Methods for LCMine an Emerging Pattern Based Classifier, Lecture Notes in Computer Science, 2013.
- A Framework in C# for Fingerprint Verification, The Code Project, 2010 [Rating: 4.95 / 5 from 276 votes | Views: 1.5M | Downloads: 150K | Bookmarked: 660].
- Cyber Security Intelligence and Analytics: Proceedings of the 2023 International Conference on Cyber Security Intelligence and Analytics (CSIA 2023), Volume 1. Springer International Publishing. ISBN: 978-3-031-31860-3. Pages 578. 2023.
- Cyber Security Intelligence and Analytics: Proceedings of the 2023 International Conference on Cyber Security Intelligence and Analytics (CSIA 2023), Volume 2. Springer International Publishing. ISBN: 978-3-031-31775-0. Pages 584. 2023.
- Cyber Security Intelligence and Analytics: Proceedings of the 2022 International Conference on Cyber Security Intelligence and Analytics (CSIA 2022), Volume 1. Springer International Publishing. ISBN: 978-3-030-96907-3. Pages 1061. 2022.
- Cyber Security Intelligence and Analytics: Proceedings of the 2022 International Conference on Cyber Security Intelligence and Analytics (CSIA 2022), Volume 2. Springer International Publishing. ISBN: 978-3-030-97873-0. Pages 1070. 2022.
- Cyber Security Intelligence and Analytics: Proceedings of the 2021 International Conference on Cyber Security Intelligence and Analytics (CSIA 2021), Volume 1. Springer International Publishing. ISBN: 978-3-030-70041-6. Pages 879. 2021.
- Cyber Security Intelligence and Analytics: Proceedings of the 2021 International Conference on Cyber Security Intelligence and Analytics (CSIA 2021), Volume 2. Springer International Publishing. ISBN: 978-3-030-69998-7. Pages 950. 2021.
- Cyber Security Intelligence and Analytics: Proceedings of the 2020 International Conference on Cyber Security Intelligence and Analytics (CSIA 2020), Volume 1. Springer International Publishing. ISBN: 978-3-030-43306-2. Pages 740. 2020.
- Cyber Security Intelligence and Analytics: Proceedings of the 2020 International Conference on Cyber Security Intelligence and Analytics (CSIA 2020), Volume 2. Springer International Publishing. ISBN: 978-3-030-43309-3. Pages 707. 2020.
- Induction of Decision Trees: Inducing Decision Trees based on a Cluster Quality. Editorial Académica Española. Academic Publishing GmbH & Co. KG. ISBN: 978-3-659-00468-1. Pages 88. 2012 (Spanish version)..
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.