Research

My research program uses clinical bioinformatics and technology-driven methods to improve care for people with Parkinson's disease.

Core Areas

• Disease Trajectories & Progression — Modeling disease progression and clinical outcomes in Parkinson's disease using longitudinal cohorts, survival analysis, and clinically grounded prediction frameworks.
• Clinical Bioinformatics & NLP — Clinical bioinformatics and natural language processing to extract meaningful outcomes from electronic health records.
• Technology-Enabled Outcomes — Technology-enabled and patient-centered outcome measurement in movement disorders.

Current Projects

• Longitudinal analysis of fall frequency, risk factors, and outcomes in Parkinson's disease
• Natural language processing for automated extraction of falls and progression markers from electronic health records
• Translation of technology-enabled outcomes into practical clinical and trial workflows

Training and Support

This work is supported by NIH T32 training in Neuroengineering and Medicine, alongside graduate training in Translational Research with a concentration in bioinformatics.