Research CV (Last Updated: January, 2025)

Ph.D. Research Topic: Digital Biomarkers for Neurodegenerative Diseases: Identifying Associations Between Neural Circuitry from MRIs and Human Movement Disturbances from Videos

Advisory Committee: Ehsan Adeli, Ph.D., Kilian M. Pohl, Ph.D., Dorsa Sadigh, Ph.D., John Pauly, Ph.D. | @ Stanford Translational AI (STAI) Lab

I am interested in using AI to discover digital biomarkers for neurodegenerative diseases such as Alzheimer’s and Parkinson’s that could be non-invasively and frequently measured with trackable trajectories. To do this, I apply graph theory, computer vision, and large language models to neuroimaging and recorded, human videos to find associations between brain patterns and movement impairment. Ultimately, this work lays the foundation for the discovery of trackable digital biomarkers of progression and differentiation of neurodegenerative disorders of aging.  It will help improve the mechanistic understanding, diagnosis, and treatment of neuropsychiatric disorders from neuroimages. My work is divided into three aims:

  1. Develop novel machine learning methods to objectively identify dynamic patterns of brain functional connectivity associated with Parkinson’s disease, Alzheimer’s disease, and Mild Cognitive Impairment;

  2. Correlate those patterns with movement-linked disturbances (e.g., tremor, postural instability, gait difficulty, stooped posture while walking) acquired from video recordings of patients while performing clinical tests (such as Short Physical Performance Battery tests) defining digital biomarkers;

  3. Use digital biomarkers and neural correlates to define different motor subtypes of neurodegenerative diseases.

Highlighted Works:

Digital Biomarkers for Neurodegenerative Diseases (@Stanford)

  1. Nerrise, F., Heiman, A. L., & Adeli, E. (2024). GAMMA-PD: Graph-based Analysis of Multi-Modal Motor Impairment Assessments in Parkinson's Disease. In MICCAI GRAIL Open Proceedings (Springer Nature Switzerland).

  2. Endo, M., Nerrise, F., Zhao, Q., Sullivan, E. V., Fei-Fei, L., Henderson, V. W., ... & Adeli, E. (2024). Data-driven discovery of movement-linked heterogeneity in neurodegenerative diseases. Nature Machine Intelligence, 6(9), 1034-1045.

  3. Nerrise, F., Zhao, Q., Poston, K.L., Pohl, K.M., Adeli, E (2023). An Explainable Geometric-Weighted Graph Attention Network for Identifying Functional Networks Associated with Gait Impairment. (2023 Medical Image Computing and Computer Assisted Interventions MICCAI conference).

  4. Nerrise, F., Pohl, K.M., Adeli, E. The Emergence of Digital Biomarkers for Neurodegenerative Diseases in the Age of AI. (Submitted).

Calibration of Aeromagnetic Compensation in Magnetic Navigation Systems (@SandboxAQ)

  1. Angappan, R., Nerrise, F., & Moore, K. (2024). Navigating through Magnetic Interference from Magnetospheric-Ionospheric Signals with AI. In AGU Fall Meeting Abstracts 24.

  2. Nerrise, F., Sosanya, A. S., & Neary, P. (2023). Physics-Informed Calibration of Aeromagnetic Compensation in Magnetic Navigation Systems using Liquid Time-Constant Networks. In NeuRIPS 2023 Machine Learning and the Physical Sciences workshop. arXiv preprint arXiv:2401.09631.

Novelty Detection for In-Situ Mars Exploration (@NASA JPL)

1.     Nerrise, F., Kerner, H. R., Wagstaff, K., et al. (2020, December). Evaluation of Machine Learning Methodologies for Novelty-based Target Selection in Planetary Imaging Data Sets: Examples from the Mars Science Laboratory Mission. In AGU Fall Meeting Abstracts (Vol. 2020, pp. P004-0007).

2. Wissler, S., Verma, V., Rebbapragada, U., Phillips, C., Nerrise, F., Lu, S., ... & Wagstaff, K. (2020). Machine Learning for Space and Planetary Exploration. NASA Jet Propulsion Laboratory Open Repository.

Research Labs

  • STAI Lab logo

    Graduate Research Assistant, Stanford Translational AI (STAI) Lab

    Deriving AI-driven, digital biomarkers to predict movement-linked disturbances of people with neurodegenerative diseases, under the mentorship of Ehsan Adeli, Ph.D.

    More on the STAI Lab.
  • SandboxAQ Logo

    AI/ML Ph.D. Resident —Quantum Sensing (AQNav), SandboxAQ

    Developing an alternate navigation system to GPS using Earth's magnetic field, AI, and quantum sensing techniques, in collaboration with Patrick Neary and Regupathi Angappan.

    More on SandboxAQ.