About Me
I am a biological anthropologist and data scientist whose career has been defined by solving problems that sit at the intersection of rigorous science and real-world decision-making. Across academic research, federal agencies, and industry, I have led technical projects that translate complex biological, social, and policy questions into actionable findings for diverse stakeholders.
My scientific research has addressed fundamental gaps in how we understand human adaptation and health. In introduced resilience theory to the field bioarchaeology as a cultural parallel to biological models of stress. I applied it to prehistoric skeletal populations in Japan — establishing a framework the field has since adopted broadly. I and my colleague applied bioarchaeological methods to living populations to measure the longitudinal health consequences of market integration in Hadza hunter-gatherers, producing the first biological evidence of sex-differentiated health outcomes in market transition for hunter-gatherers engaging in remote bush economies. Across projects spanning skull biomechanics, genetic epidemiology, developmental stress, and olfactory evolution, my contributions have consistently opened new methodological and theoretical territory rather than confirming existing frameworks.
Since 2020, I have applied that same problem-driven approach to science policy and applied analytics. Recognizing that international science organizations lacked rigorous quantitative tools for evaluating research landscapes, I built analytical pipelines for benchmarking national research impact, forecasting global R&D leadership under demographic pressure, and mapping federal funding dependency at R1 universities across fifty years. These projects were designed from the outset to inform institutional strategy and policy decisions, not just to describe trends. In parallel, I have evaluated emerging AI systems — auditing facial recognition technology for demographic bias, building morph attack detection classifiers, and designing serverless document validation pipelines — bringing the same evidence-based rigor to technology assessment that I apply to scientific questions.
My technical toolkit includes R, Python, and SQL, with expertise in Bayesian methods, machine learning, geospatial analysis, NLP, network analysis, and interactive data visualization. I build reproducible, end-to-end analytical workflows that are documented, transferable, and designed to outlast any single project.
I have coordinated multi-institutional research teams, mentored researchers across career stages, and communicated complex findings to audiences ranging from academic peers to policy stakeholders and executive leadership. I am most effective when the problem is complicated, the audience is mixed, and the answer has to be both rigorous and clear.
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