NCBL
NCBL

University of alberta

Beatriz Sanabria Barradas

ABOUT ME

I am a biomedical engineer and neuroengineering researcher focused on brain–computer interfaces, EEG signal processing, and machine learning applications for clinical and pediatric populations. I earned a B.Sc. in Biomedical Engineering from Tec de Monterrey (2017) and a Ph.D. in Biomedical Sciences from Universidad Veracruzana (2022). My doctoral research focused on classifying and characterizing EEG and N170 signals in children with autism and included a research stay at Nottingham Trent University in the United Kingdom. In addition to my academic pursuits, I have led clinical engineering teams in hospital environments in Mexico, overseeing medical technology management and regulatory compliance. I am currently a Postdoctoral Fellow at the NCBLab, University of Alberta, where I am developing a data-driven framework to personalize neurotechnology access for children with motor disabilities.

Supervisor

  • Dr. Hossein Rouhani

RESEARCH INTERESTS

  • Brain–computer interfaces and hybrid BCI design

  • EEG acquisition, signal processing, and machine learning

  • Assistive and rehabilitation neurotechnology

  • User-centred and co-design with clinicians and families

Postdoctoral Fellow (2026 – Present)

NCBL, University of Alberta

Project: A data-driven decision framework to personalize neurotechnology access for children with motor disabilities

Lecturer Professor (2024 – Present)

Tec de Monterrey, Mexico — EIC Mechatronics

• Instructs courses on Design and Development in Neuroengineering

Clinical Engineering Manager (2024 – 2025)

Hospital Ángeles Health System, Mexico

• Directed cross-functional teams across 26 hospitals to ensure safe operation of medical equipment and to standardize policies and inventories for regulatory compliance, including Joint Commission International and Accreditation Canada processes.

Research Assistant, Doctoral Level (2018 – 2022)

Psychobiology Laboratory, Universidad Veracruzana, Mexico

• Developed machine learning algorithms for EEG classification in autism research and constructed a comprehensive EEG–stimulus synchronization pipeline using Neuroscan Synamps RT and Trigger Station.

Research Internship (2021 – 2022)

Nottingham Trent University, UK — Supervisor: Prof. Saeid Sanei

• Developed computational methods for EEG processing and identification of autism utilizing subspace analysis and brain connectivity measures.

Publications

  • Granados-Ramos, D. E., Altamirano-Díaz, P. A., & Sanabria-Barradas, B. (2023). Interacciones mediante el juego en diadas madre-hijo con Trastorno del Espectro Autista (TEA). Interdisciplinaria, 40(3).

  • Sanabria-Barradas, B., Sanei, S., & Granados-Ramos, D. E. (2022). A hybrid tensor factorization – singular spectrum analysis approach for ERP-based assessment of autism in children. 30th EUSIPCO, 1193–1197.

  • Sanabria-Barradas, B., Gallardo-Beatriz, L. S., Palma-Jacinto, J. A., & Calderón-Garcidueñas, A. L. (2021). The pathogenesis of autism spectrum disorder. Revista Mexicana de Neurociencia, 22(6).

  • Granados-Ramos, D. E., López-Sánchez, J. D., Figueroa-Rodríguez, S., & Sanabria-Barradas, B. (2019). EEG coherence and intelligence in elementary school children. Journal of Psychology and Behavioral Science, 7(2).

  • Sanabria-Barradas, B., Linares Márquez, P., & Granados Ramos, D. E. (2018). Consentimiento informado en la discapacidad: trastorno del espectro autista. Revista Latinoamericana de Bioética, 19(36-1), 13–26.