Bio

Evelyn is pursuing an MD-PhD in the Medical Scientist Training Program (MSTP), jointly advised by 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, working with Dr. Edward Boyden to develop a next-generation protein sequencing technology. As a Marshall Scholar, Evelyn earned an MPhil in the Neural Computation Lab at University College London, where she optimized existing all-optical interrogation techniques 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 bioelectronics for multi-modal recording and neural stimulation, as well as 3D microphysiological systems for probing neural-tumor interactions.

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

  • Mail Code: 5151

Current Research and Scholarly Interests

Soft bioelectronics for multi-modal sensing and neural stimulation

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