Welcome

My Mission

My mission is to harness the power of data science, artificial intelligence, machine learning, and spatial modeling to generate actionable insights that improve education and health outcomes, advance equity, build and strengthen AI and data science workforce, and transform education in underserved and geographically isolated communities — beginning with the U.S. Virgin Islands and extending to the broader Caribbean and beyond.

What I Believe

First, I believe that the most important questions in public health are not purely clinical — they are spatial, social, and structural. Non-communicable diseases do not distribute randomly; they cluster in communities shaped by history, geography, and systemic inequity. Understanding and disrupting those patterns requires not only statistical sophistication, but deep community partnership, interdisciplinary collaboration, and a commitment to translating complex findings into tools that communities can actually use.

Second, I believe that data science education is a form of empowerment. When students at minority-serving institutions gain mastery over AI and data science, they become capable not only of entering a growing workforce — but of directing that workforce’s attention toward the problems that matter most to their own communities.

Third, I believe that geographically isolated communities like the U.S. Virgin Islands are not peripheral to the great questions of health, technology, and equity — they are laboratories of insight, where the limitations of one-size-fits-all systems are most clearly visible, and where innovative, context-sensitive solutions can be born.

What I Am Building

My current research program at UVI reflects these convictions in action. I am building AI-driven spatio-temporal models to predict and mitigate non-communicable disease burden across the USVI — integrating environmental, socioeconomic, and health system data to identify high-risk geographic clusters and model disease trajectories over time. I am translating those findings into interactive decision-support dashboards that place analytical power directly in the hands of local health agencies and policymakers.

Alongside this, I am leading a National Science Foundation (NSF)-targeted initiative to redesign undergraduate AI and data science education at UVI — building a scalable institutional model for AI-ready workforce development that is explicitly designed for minority-serving and geographically isolated academic contexts.

I am also expanding my methodological reach into computational social science — exploring how digital trace data, social media discourse, and network analysis can complement traditional epidemiological data to reveal the social dimensions of disease risk in Caribbean island communities.

Who I Serve

First, my work ultimately serves communities that are too often invisible in national data systems and absent from research conversations — communities that bear a disproportionate burden of chronic disease, that face geographic and infrastructural isolation, and that deserve research partnerships that are responsive to their realities rather than extractive of their data.

Second, I serve students who are capable of becoming the next generation of data scientists and AI practitioners, but who need institutions, curricula, and mentors that see their potential and invest in their preparation.

Third, I serve fellow researchers, collaborators, and policymakers who are committed to evidence-based approaches to public health — and who understand that the best evidence is generated not from the center, but from every corner of the human experience.

“Data is everywhere. Insight is power. Impact is purpose.” — Dr. Owen Mtambo