Healthcare Data Science & AI

I manage the Advanced Analytics team at UCLA Health IT, where we develop, evaluate, and scale AI and machine learning solutions to help improve patient care, clinical workflows, and operational performance across the health system.

Before moving into management, I worked on the Advanced Analytics team as a data scientist, building and evaluating custom machine learning models and vendor solutions for real-world healthcare challenges. This work included risk-based models, natural language processing, and large language models applied to clinical text and workflow improvement.

My work in healthcare AI spans the full lifecycle, from initial feasibility and prototype development, to evaluation with clinical and operational stakeholders, and into operational use with attention to performance, safety, and real-world impact.

Responsible AI in Healthcare

I have helped build core components of a responsible AI program at UCLA Health, including clear model documentation practices and contributions to the Health AI Council model review process. I now lead the team in designing and implementing responsible AI practices that support evaluation of clinical relevance, fairness, risk, and ongoing monitoring.

I regularly speak on topics related to responsible AI in healthcare, with a focus on practical approaches to documentation, evaluation frameworks, governance, and deployment considerations. See my my 2023 Data Day talk at UCLA for more details.