Research

My research focuses on applying Deep Learning to solve real-world problems, with a particular interest in signal analysis and AI systems that can make a meaningful impact. I work at the intersection of neuroscience and computing, as well as cybersecurity, and a few industrial applications, wherever there’s a complex signal to decode, I’m usually interested.

I am a member of Mexico’s National System of Researchers (SNII) Rank 1, and a Research Professor in the Advanced AI group at Tecnologico de Monterr

For my full publication list, see:

Google Scholar

ORCiD

Neuroscience & Healthcare

I believe that studying how biological neural systems work will drive the next breakthroughs in AI. Our work applies deep learning to analyze neurological signals (EEG, fMRI) and brain imaging.

Recent publications:

  • 2025 – Data Collection for Automatic Depression Identification in Spanish Speakers Using Deep Learning Algorithms: Protocol for a Case-Control Study. Brenes, L. F., Trejo, L. A., Cantoral-Ceballos, J. A., Aguilar-De León, D., & Hernández-Moreno, F. P. JMIR Res Protoc, vol. 14, e60439. https://doi.org/10.2196/60439.
  • 2025 – Beyond Neurofibrillary Tangles: Explainable AI for Microscopic Tauopathy Classification in Immunofluorescence Imaging. López-Barrios, J. D., Ontiveros-Torres, M. A., & Cantoral-Ceballos, J. A. In Proceedings of the Computer Vision and Pattern Recognition (CVPR) Workshops, pp. 4758-4768.
  • 2024 – Unlocking Security for Comprehensive Electroencephalogram-Based User Authentication Systems. Khalil, A. E. K., Perez-Diaz, J. A., Cantoral-Ceballos, J. A., & Antelis, J. M. Sensors, vol. 24, no. 7919. https://doi.org/10.3390/s24247919.
  • 2022 – Interpretable Classification of Tauopathies with a Convolutional Neural Network Pipeline Using Transfer Learning and Validation against Post-Mortem Clinical Cases of Alzheimer’s Disease and Progressive Supranuclear Palsy. Diaz-Gomez, L., Gutierrez-Rodriguez, A. E., Martinez-Maldonado, A., Luna-Muñoz, J., Cantoral-Ceballos, J. A., & Ontiveros-Torres, M. A. Current Issues in Molecular Biology, vol. 44, pp. 5963-5985. https://doi.org/10.3390/cimb44120406.
  • 2022 – A Novel Automatic Quantification Protocol for Biomarkers of Tauopathies in the Hippocampus and Entorhinal Cortex of Post-Mortem Samples Using an Extended Semi-Siamese U-Net. Campero-Garcia, L. A., Cantoral-Ceballos, J. A., Martinez-Maldonado, A., Luna-Muñoz, J., Ontiveros-Torres, M. A., & Gutierrez-Rodriguez, A. E. Biology, vol. 11, no. 8.https://doi.org/10.3390/biology11081131.
  • 2022 – Motor Imagery Analysis from Extensive EEG Data Representations Using Convolutional Neural Networks. Lomelin-Ibarra, V. A., Gutierrez-Rodriguez, A. E., & Cantoral-Ceballos, J. A. Sensors, vol. 22, no. 16.https://doi.org/10.3390/s22166093.

Cybersecurity & Anomaly Detection

Our group develops AI-driven systems to protect digital infrastructure, from Internet routing to financial transactions and IoT networks.

Recent publications:

  • 2026 – Extending Memory-Based Obfuscated Malware Detection with Network Behavior. Jhon F. Mercado; Josue Genaro Almaraz-Rivera; Sergio Armando Gutierrez; Jesus Arturo Perez-Diaz; Luis A. Fletscher; Jose Antonio Cantoral-Ceballos. IEEE Open Journal of the Communications Society. https://doi.org/10.1109/OJCOMS.2026.3667851.
  • 2025 – A Multimodal Learning Approach for Protecting the Metro System of Medellin Colombia Against Corrupted User Traffic Data. Almaraz-Rivera, J.G.; Cantoral-Ceballos, J.A.; Botero, J.F.; Muñoz, F.J.; Martinez, B.D. Smart Cities 2025, 8, 198. https://doi.org/10.3390/smartcities8060198
  • 2025 – Hyphatia: A Card-Not-Present Fraud Detection System Based on Self-Supervised Tabular Learning. Almaraz-Rivera, J. G., Cantoral-Ceballos, J. A., Botero, J. F., Munoz, F. J., & Martinez, B. D. IEEE Open Journal of the Computer Society. https://doi.org/10.1109/OJCS.2025.3570600.
  • 2025 – A Hybrid Model for BGP Anomaly Detection Using Median Absolute Deviation and Machine Learning. Romo-Chavero, M. A., Alatorre, G. D. L. R., Cantoral-Ceballos, J. A., Pérez-Díaz, J. A., & Martinez-Cagnazzo, C. IEEE Open Journal of the Communications Society, vol. 6, pp. 2102-2116. https://doi.org/10.1109/OJCOMS.2025.3550010.
  • 2024 – Median Absolute Deviation for BGP Anomaly Detection. Romo-Chavero, M. A., Cantoral-Ceballos, J. A., Pérez-Díaz, J. A., & Martinez-Cagnazzo, C. Future Internet, vol. 16, no. 146. https://doi.org/10.3390/fi16050146.
  • 2023 – Enhancing IoT Network Security: Unveiling the Power of Self-Supervised Learning against DDoS Attacks. Almaraz-Rivera, J. G., Cantoral-Ceballos, J. A., & Botero, J. F. Sensors, vol. 23, no. 8701. https://doi.org/10.3390/s23218701.
  • 2023 – A Novel Multi-Factor Authentication Algorithm Based on Image Recognition and User Established Relations. Carrillo-Torres, D., Pérez-Díaz, J. A., Cantoral-Ceballos, J. A., & Vargas-Rosales, C. Applied Sciences, vol. 13, no. 1374. https://doi.org/10.3390/app13031374.
  • 2022 – Toward the Protection of IoT Networks: Introducing the LATAM-DDoS-IoT Dataset. Almaraz-Rivera, J. G., Perez-Diaz, J. A., Cantoral-Ceballos, J. A., Botero, J. F., & Trejo, L. A. IEEE Access, vol. 10, pp. 106909–106920. https://doi.org/10.1109/ACCESS.2022.3211513.

Industry & Precision Agriculture

Bridging the gap between academic research and industrial applications, particularly in quality management and manufacturing.

Recent publications:

  • 2025 – Deep Learning Algorithms for Defect Detection on Electronic Assemblies: A Systematic Literature Review. Montoya Magaña, B.; Hernández-Uribe, Ó.; Cárdenas-Robledo, L.A.; Cantoral-Ceballos, J.A. Mach. Learn. Knowl. Extr. 2026, 8, 5. https://doi.org/10.3390/make8010005
  • 2025 – Capsicum Counting Algorithm Using Infrared Imaging and YOLO11. Mendez, E.; Escobedo Cabello, J.A.; Gómez-Espinosa, A.; Cantoral-Ceballos, J.A.; Ochoa, O. Agriculture 2025, 15, 2574. https://doi.org/10.3390/agriculture15242574
  • 2025 – Quality 4.0: Learning quality control, the evolution of SQC/SPC. Escobar, C. A., Cantoral-Ceballos, J. A., & Morales-Menendez, R. Quality Engineering, pp. 1–26. https://doi.org/10.1080/08982112.2024.2356519.
  • 2024 – Implementation of a Long Short-Term Memory Neural Network-Based Algorithm for Dynamic Obstacle Avoidance. Mulás-Tejeda, E., Gómez-Espinosa, A., Escobedo Cabello, J. A., Cantoral-Ceballos, J. A., & Molina-Leal, A. Sensors, vol. 24, no. 3004. https://doi.org/10.3390/s24103004.
  • 2024 – Maturity Recognition and Fruit Counting for Sweet Peppers in Greenhouses Using Deep Learning Neural Networks. Viveros Escamilla, L. D., Gómez-Espinosa, A., Escobedo Cabello, J. A., & Cantoral-Ceballos, J. A. Agriculture, vol. 14, no. 331. https://doi.org/10.3390/agriculture14030331.
  • 2022 – Extended reality applications in industry 4.0. – A systematic literature review. Cárdenas-Robledo, L. A., Hernández-Uribe, Ó., Reta, C., & Cantoral-Ceballos, J. A. Telematics and Informatics, vol. 73. https://doi.org/10.1016/j.tele.2022.101863.
  • 2022 – Link Quality Estimation for Wireless ANDON Towers Based on Deep Learning Models. Cortes-Aguilar, T. A., Cantoral-Ceballos, J. A., & Tovar-Arriaga, A. Sensors, vol. 22, no. 17. https://doi.org/10.3390/s22176383.

Talks & Recognition

  • Keynote Speaker, LatinX in AI Workshop @ NeurIPS 2025, San Diego — “Mind the Gaps: Challenges and Opportunities for a Thriving AI Ecosystem in Latin America”
  • Best Poster Award, LatinX in AI (ICCV) Workshop, 2023
  • Best Technical Presentation, World Congress of Industrial Process Tomography, 2013
  • Member, Mexico’s National System of Researchers (SNII)