Engineering Data-backed Solutions
My work integrates data-acquisition, statistical analysis, and algorithmic modeling to build systems grounded in measurable evidence. Insights extracted from data guide system design, automate decision processes, and enable continuous performance improvements across engineering applications.
Applied Machine Learning & Data -Inensive Systems Architecture
Research centers on high dimensional representation learning, temporal feature extraction, multimodal fusion, and robust inference within complex, noisy data regimes.
Embedded Systems, Sensing, & Human-Centered Interfaces
Engineering involves ultra low power sensing platforms, deterministic real time processing, adaptive control mechanisms, and signal conditioning under computational constraints.
Global Education, Equity, & Technology for Social Systems
Research examines sociotechnical learning infrastructures, computational access modeling, instructional analytics, and scalable digital interventions supporting large population level educational systems.
Algorithmic Optimization, Statistical AI Learning
Work explores gradient based optimization behavior, probabilistic modeling, convergence properties, and statistical learning dynamics across complex high dimensional AI systems.
About
My engineering journey began long before college growing up between two worlds, I learned early how access, design, and technology shape people’s lives. Today, I blend data science, engineering, and global education to build systems that serve people.
I’ve designed projects that span EEG-controlled mobility, physiological modeling, environmental prediction, educational data systems, and accessibility-focused solutions. Outside of research, I write books, mentor students, and lead a nonprofit STEM initiative serving classrooms abroad.
I care about problems that affect real communities. My work is powered by curiosity, empathy, and a commitment to engineering a better future.