Bio

Evelyn Wong (she/her) is pursuing an MD at Stanford School of Medicine, and a PhD in the labs of Dr. Longzhi Tan (Biophysics) and Dr. Zhenan Bao (Chemical Engineering).

She graduated summa cum laude from Harvard University with a major in neuroscience and a minor in Spanish literature. Evelyn received the Herchel Smith Fellowship for her thesis project at the MIT McGovern Institute, developing a next-generation protein sequencing platform. In 2020, she founded CovEducation, a nonprofit bridging the academic achievement gap, which earned recognition from the Clinton Foundation for advancing educational equity in K-12 communities. As a Marshall Scholar, Evelyn earned an MPhil in the Division of Medicine at University College London, where she optimized existing neurotechnologies to investigate cortical brain function.

Evelyn is a recipient of the Knight-Hennessy Scholarship (2023) and the Paul & Daisy Soros Fellowship for New Americans (2024), supporting her dual-degree training. Her current research focuses on developing flexible electrodes to record neural signals from deep brain structures. She also serves as co-director of the Stanford Asylum Collaborative, providing medical and psychological evaluations for individuals seeking asylum in the United States. Evelyn aspires to be a physician-neuroengineer, working at the intersection of asylee health and neurotechnology to address both technical and structural barriers to neuropsychiatric care.

Education & Certifications

  • Bachelor of Arts, Harvard University, Neuroscience (2021)
  • Master of Philosophy, University College London (2023)

Contact

  • Academic
    University - Student Department: BioPhysics Position: Graduate
    University - Student Department: School of Medicine Position: Graduate, Medicine

Additional Info

Links

All Publications

  • Bridging the Digital Divide: A Practical Roadmap for Deploying Medical Artificial Intelligence Technologies in Low-Resource Settings. Population health management Wong, E., Bermudez-Cañete, A., Campbell, M. J., Rhew, D. C. 2025

    Abstract

    In recent decades, the integration of artificial intelligence (AI) into health care has revolutionized diagnostics, treatment customization, and delivery. In low-resource settings, AI offers significant potential to address health care disparities exacerbated by shortages of medical professionals and other resources. However, implementing AI effectively and responsibly in these settings requires careful consideration of context-specific needs and barriers to equitable care. This article explores the practical deployment of AI in low-resource environments through a review of existing literature and interviews with experts, ranging from health care providers and administrators to AI tool developers and government consultants. The authors highlight 4 critical areas for effective AI deployment: infrastructure requirements, deployment and data management, education and training, and responsible AI practices. By addressing these aspects, the proposed framework aims to guide sustainable AI integration, minimizing risk, and enhancing health care access in underserved regions.

    View details for DOI 10.1089/pop.2024.0222

    View details for PubMedID 39899377

  • Meta-Analysis: Prevalence of Youth Mental Disorders in Sub-Saharan Africa CAMBRIDGE PRISMS-GLOBAL MENTAL HEALTH Jakobsson, C. E., Johnson, N. E., Ochuku, B., Baseke, R., Wong, E., Musyimi, C. W., Ndetei, D. M., Venturo-Conerly, K. E. 2024; 11

    View details for DOI 10.1017/gmh.2024.82.pr6

    View details for Web of Science ID 001354566700001

https://orcid.org/0000-0002-0265-8514