School of Medicine


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  • Josefina Flores Morales

    Josefina Flores Morales

    Postdoctoral Scholar, Epidemiology

    BioJosefina (she/her/ella) is a Propel Postdoctoral Scholar in the Department of Epidemiology and Population Health in the School of Medicine with Dr. Mathew Kiang’s lab. Her research is about health and socioeconomic inequities across the life course. She is interested in diverging outcomes across race/ethnicity and documentation status. Josefina earned her B.A. in psychology with a public health minor from the University of California, Los Angeles (UCLA). She pursued her doctoral education in sociology at UCLA as well. Her doctoral studies were supported by the Health Policy Research Scholars program, a program by the Robert Wood Johnson Foundation.

  • Cellas Ari'ka Hayes

    Cellas Ari'ka Hayes

    Postdoctoral Scholar, Epidemiology

    BioCellas is currently a postdoctoral fellow/Propel scholar at Stanford University in the Department of Neurology and Neurological Sciences in a laboratory utilizing longitudinal data analysis and neuroimaging modalities to understand the aging brain, neuropathology, cognition, and Alzheimer’s Disease. Postdoctoral experience includes using R, Linux, and Python to perform data preprocessing, multivariate statistical analysis, and applying novel models for longitudinal continuous outcomes. Cellas received his Bachelor’s in Biology (2015-2019) and Doctor of Philosophy in Pharmaceutical Sciences with an emphasis in Pharmacology (2019-2022) from the University of Mississippi. As a doctoral candidate, his research focused on using both in vitro and in vivo approaches to further elucidate how neuroendocrine modulation specifically insulin-like growth factor-1 alters learning and memory performance along with ischemic stroke outcomes. Skills gained during doctoral training included in vitro cell culture, pharmacological experimental design of both in vitro and in vivo studies, development of transgenic mouse models, a wide array of rodent behavioral paradigms, stereotaxic surgery, photothrombosis, and numerous ex vivo cellular, molecular, and microscopy techniques.
    My primary interests lie at the intersection of aging, neurodegenerative disease, and using longitudinal epidemiological data sets to investigate hypotheses. All around neuroscientist seeking sci-comm, industry, and academic opportunities to strengthen skills to become an independent investigator.

  • Tracy Lam-Hine

    Tracy Lam-Hine

    Postdoctoral Scholar, Epidemiology

    BioTracy Lam-Hine (he/him), DrPH, MBA, is a postdoctoral research fellow mentored by Dr. David Rehkopf in the Stanford Medicine Department of Epidemiology and Population Health and the Stanford Center for Population Health Sciences. His research focuses on improving the measurement of structural racism in epidemiologic studies, the cardiopulmonary and mental health of Multiracial people in the United States, and the application of methods in social epidemiology to racial health inequities. Dr. Lam-Hine also collaborates with state and local health jurisdictions in California and Hawaii in applied epidemiology and surveillance projects on topics including structural racism, adolescent health, and COVID-19.

  • Alexis Reeves

    Alexis Reeves

    Postdoctoral Scholar, Epidemiology

    BioAlexis is a Propel postdoctoral scholar in the Department of Epidemiology and Population Health in the School of Medicine with Dr. Michelle Odden’s lab. Her research is broadly focused on the causes and consequences of racial disparities in accelerated aging. She is particularly interested in the interplay of structural and interpersonal racism, and the psychobiological mechanisms in which they produce early health declines in minoritized populations. Her work to date has focused on the health of Black women as they enter into life-stages, such as the midlife menopausal transition, where cardio-metabolic risk is high. Alexis also has a strong interest in causal inference, and applies causal inference theory and methods to these areas of research to mitigate and quantify bias.