Summary
Favour Nerrise is a PhD-trained electrical engineer and research-focused AI scientist with a decade of hands-on experience building ML systems across academia and industry in the San Francisco Bay Area. Currently a Graduate Research Assistant at Stanford Translational AI Lab, she develops AI-driven digital biomarkers and geometric deep learning models to detect movement-linked disturbances in neurodegenerative disease using multi-modal imaging and computer vision. Her background spans applied roles at Amazon, Meta, SandboxAQ, and NASA-affiliated labs where she has deployed LLM pipelines for protein modeling, physics-informed AI for magnetic navigation, and Bayesian uncertainty methods to cut carbon-footprint estimation. Comfortable moving from low-level signal processing and quantum sensing to large-scale deep learning and production microservices, she blends rigorous research with product-minded engineering. Notably, her work consistently targets real-world impact—medical diagnostics, navigation alternatives to GPS, and sustainability analytics—demonstrating a rare mix of domain breadth and translational focus.
10 years of coding experience
4 years of employment as a software developer
High School General Studies, High School General Studies at Academy of Health Sciences at PGCC
Associate’s Degree General Studies, Associate’s Degree General Studies at Prince George's Community College
Bachelor’s Degree Computer Engineering, Bachelor’s Degree Computer Engineering at University of Maryland
Girls Who Code
Doctor of Philosophy - PhD Electrical Engineering, Doctor of Philosophy - PhD Electrical Engineering at Stanford University