Lead Data Scientist (Neurosciences + Digital Health) | Applied AI Research Engineer

e-mail: sirenia.mondragon (at) icm-institute.org

I am an applied research engineer and lead data scientist (neuroscience + digital health) , who was initially trained as an engineer in mechatronics and robotics (double degree) with a background in artificial intelligence (AI), and who later turned to neuroscience and digital health.

I work at the intersection of neuroscience and digital health, designing AI/ML systems that transform diverse data: from brain signals and imaging to pose-based video analysis, wearable sensors, and clinical records into insights that advance research and improve patient care. I lead projects from concept to implementation, bridging research and technology to build scalable, human-centered solutions.

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Publications and patents

Peer-reviewed journals

  • [8] Mondragón-González, S.L., Schreiweis, C. & Burguière, E. (2024). Closed-loop
    recruitment of striatal interneurons prevents compulsions
    Nature Neuroscience (2024)
  • [7] Lamothe, H., Schreiweis, C., Mondragón-González, S.L., Rebbah, S., Lavielle, O.,
    Mallet, L., & Burguière, E. (2023). The Sapap3−/− mouse reconsidered as a comorbid
    model expressing a spectrum of pathological repetitive behaviours.
    Translational Psychiatry, 13(1), 26.
  • [6] Mondragón-González, S. L., & Burguière, E. (2017). Bio-inspired benchmark generator
    for extracellular multi-unit recordings. Scientific reports, 7(1), 43253.
  • [5] Muñiz-Hernández, S., González del Carmen, M., Mondragón, M., Mercier, C.,
    Cesbron, M. F., Mondragón-González, S.L & Mondragón, R. (2011). Contribution of
    the residual body in the spatial organization of Toxoplasma gondii tachyzoites within the parasitophorous vacuole. BioMed Research International, vol 2011.

Patent

  • [4] Mondragón-González, S. L., & Burguière, E. Brevet européen (2022)
    no. 22 305 177.2 Method and device for physiological signal processing.

Book Chapter

  • [3] Mondragón-González, S. L., Burguière, E., & N’diaye, K. (2023). Mobile Devices,
    Connected Objects, and Sensors. Machine Learning for Brain Disorders, 355-388.

Pre-print

  • [2] Mondragón-González, S. L., Schreiweis C, C., & Burguière E, E. (2022). Closed-loop
    recruitment of striatal parvalbumin interneurons prevents the onset of compulsive
    behaviours. bioRxiv, 2022-01.

Doctoral dissertation

  • [1] Mondragón-González, S. L.(2019) Combining a real-time closed-loop system withneuromodulation: and integrative approach to prevent pathodological repetitivebahviours. Sorbonne Université