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Assistant Professor, Genetics 

Research Interests

Keywords: real-world data, wearables, machine learning, mental health, digital phenotyping 

My research focuses on early detection and enhanced monitoring of disease leveraging multimodal real-world data. My work draws on several data sources, including wearables, electronic health records, and self-reported phenotyping for biostatistical and machine learning analysis. I am especially interested in applications related to mental health and digital phenotyping, with the goal of translating passive data collection into tools that support early intervention and personalized care.

Mentor Training:

Training Program Affiliations:

Publications

Eric Hurwitz in UNC Genetics News

Eric Hurwitz
  • Genetics