BIO

Chris Dharma is a Research Assistant Professor in the Survey Methodology Program within the Survey Research Center at the Institute for Social Research, University of Michigan. He earned his PhD from the University of Toronto, supported by the Vanier Canada Graduate Scholarship (2021–2024), and was a visiting scholar at Columbia University in 2023. Prior to joining the University of Michigan, he completed postdoctoral training in artificial intelligence and health informatics at the University of Toronto’s Data Science Institute.

As a biostatistician and epidemiologist, his work integrates multiple sources of secondary data, including administrative records, complex population health surveys, and unstructured web-based text and image data. His methodological research focuses on bias mitigation, psychometric evaluation, synthetic data generation, and multiple imputation. He also develops evaluation frameworks for large language model (LLM) outputs and LLM as a judge methodologies to support social science and mental health applications. Substantively, he collaborates across clinical, psychological, and social disciplines, applying these methodological tools to investigate mental health, sexual health, youth digital technology use, and behavioral addictions including substance use and gambling.