I am a Senior Data Scientist at the University of Pennsylvania’s Perelman School of Medicine, where I develop and evaluate machine learning approaches to improve healthcare prediction, policy, and decision-making.
My research focuses on developing and evaluating machine learning and AI-driven methods to address complex healthcare challenges. My work includes improving the accuracy and equity of Medicare risk adjustment through predictive modeling, as well as leveraging natural language processing and deep learning to systematically analyze clinical conversations.
An Interdisciplinary Approach to Healthcare
With experience spanning academic research, healthcare technology, and industry, I combine technical expertise with an interdisciplinary perspective to translate complex data into meaningful insights.
My background in cognitive science, psychology, and behavioral research shapes how I approach healthcare data science. I believe that developing useful AI requires both technical sophistication and a good understanding of the people, systems, and decisions behind the data.
Areas of Expertise
Healthcare Machine Learning & AI
Healthcare Policy
Predictive Analytics / Statistical Modeling
Clinical NLP
Behavioral Science / Human-Centered Research
Data Science Education
19
publications and proceedings articles
40+
invited lectures and conference presentations & posters
8
classes taught at the college level