Portage, Michigan, United States
I’m a Healthcare Data Scientist and AI/ML expert with deep experience in transforming complex clinical data into scalable, intelligent systems. My work bridges data engineering, cloud computing, and machine learning to enable evidence-driven insights that improve patient outcomes. Passionate about clinical AI innovation, I focus on building interoperable data pipelines, developing trustworthy models, and advancing precision healthcare through responsible, data-centric AI.
As Chief AI Officer (CAIO), I set and execute the company’s AI strategy, translating business and clinical priorities into a governed, scalable AI roadmap. I lead the end-to-end AI operating model across product, engineering, data, security, and compliance, ensuring our Multi-Agent Health Digital Twin platform delivers measurable clinical and commercial impact. My role spans executive decision-making on architecture and model strategy, MLOps and data interoperability (including Epic/Cerner integrations), responsible AI controls, and team leadership, driving adoption from prototype to production with clear outcomes and accountability.
As Head of AI/ML at March Health, I have the privilege to lead and collaborate within a multidisciplinary team of scientists and engineers developing the Multi-Agent Health Digital Twin (HDT), an ambitious AI framework designed to transform clinical intelligence through coordinated, specialty-aware reasoning. In this role, I direct the design, planning, and implementation of AI/ML and data infrastructure initiatives, overseeing the end-to-end lifecycle from EHR data extraction, structuring, and harmonization (including Epic/Cerner systems) to model readiness, orchestration, and evaluation. My focus bridges strategic leadership and technical execution, ensuring that every layer of the HDT ecosystem, from data pipelines to model architecture, is scalable, interoperable, and aligned with real-world clinical objectives.
I am honored to support a cohort of brilliant, forward-thinking professionals who are pioneering AI/ML applications for population health. I guide them in harnessing complex health datasets, integrating community-driven insights, and building cutting-edge AI solutions that drive health equity, as a mentor in the "AIM-AHEAD ScHARe Equity in Population Health AI: Beyond EHR Training Program". Together, we shape innovative approaches to ethical AI, ensuring scalable, secure, and impactful advancements in underrepresented communities.
I have the wonderful opportunity to collaborate with exceptional researchers to harness AI/ML for uncovering and mitigating health disparities, particularly in dental care access. We apply cutting-edge machine learning to vast population health datasets, driving ethical AI innovations that inform equitable healthcare policies and reshape the future of bias-aware health analytics.
As a judge for The Curiosity Cup, a global SAS student competition, I have the privilege of evaluating groundbreaking projects where brilliant student teams showcase their expertise in statistical analysis, predictive AI models, and data-driven problem-solving. Witnessing their innovative approaches to real-world challenges is truly inspiring, and I am honored to support the next generation of data scientists pushing the boundaries of analytics and AI.
• Principal Scientific Consultant applying bioinformatics and data science to single-cell proteomics (CyToF), specializing in biomarker discovery for fetal anomalies. • Led multi-omics data integration and advanced computational analysis for precision healthcare, with a strong focus on identifying key biomarkers to improve patient outcomes.