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INFORMATION FOR

    Christopher Fields

    he/him/his
    Associate Research Scientist

    About

    Titles

    Associate Research Scientist

    Biography

    Christopher Fields, Ph.D. is an Associate Research Scientist in the Department of Psychiatry at the Yale School of Medicine. His research examines how social stressors impact brain health. By combining advanced neuroimaging techniques with community-based participatory research (CBPR), Dr. Fields seeks to develop more equitable, context-sensitive models of psychiatric prediction and care.

    Dr. Fields earned his Ph.D. in Neuroscience from Georgia State University, where his work explored the interplay between immune signaling and behavioral regulation. He holds a B.A. in Biochemistry, with honors, from Washington University in St. Louis. He completed a postdoctoral fellowship in molecular psychiatry at Yale, supported by a prestigious NIMH F32 award, and currently contributes to multiple NIH-funded projects aimed at addressing algorithmic bias and racialized variance in neuroimaging research.

    A frequent speaker at national and international conferences, Dr. Fields has published in journals such as Journal of Adolescent Health, Frontiers in Digital Health, and Biology of Sex Differences. He is a strong advocate for diversifying neuroscience research and integrating sociohistorical frameworks into both experimental design and data interpretation.

    Last Updated on October 06, 2025.

    Education & Training

    PhD
    Georgia State University, Neuroscience
    MS
    Rockefeller University
    BA
    Washington University, Biochemistry

    Research

    Research at a Glance

    Yale Co-Authors

    Frequent collaborators of Christopher Fields's published research.

    Publications

    2025

    2024

    2022

    Academic Achievements & Community Involvement

    Activities

    • activity

      Racialized Heteroscedasticity in Predictive Modeling: Variance, Uncertainty, and Structural Risk in the ABCD Study

    • activity

      Racialized Variance in Psychiatric Prediction: Addressing Algorithmic Biases in Neuroimaging, and Cognitive Measures, while Building Parity through New Community Engagement Models

    • activity

      Racialized Variance in Psychiatric Prediction Models: Building Equity Through Community Engagement

    • activity

      Pediatrics

    • activity

      Journal of Racial and Ethnic Health Disparities

    Honors

    • honor

      National Institute of Mental Health R36 Dissertation Grant

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