Summer 2024, Bar Harbor, Acadia.

           


RESEARCH AREAS:
  • AI for healthcare
  • Digital psychiatry
  • Natural Language Processing
  • Clinical Informatics

    • AFFILIATIONS:
  • Department of Epidemiology, Harvard School of Public Health
  • Department of Neurology, Mass General Brigham
  • Division of Digital Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School
    •





    Hi, I’m Yining (Nin) Hua, a third-year PhD student in Epidemiology at the Harvard T.H. Chan School of Public Health (neuropsychiatric track). I work on healthcare AI and computational methods, with training in NLP, biomedical informatics, epidemiology, and biostatistics. My current focus is on reliable LLMs for healthcare: training and evaluation, bias identification/mitigation, causal reasoning (DAGs), and study design.

    I am advised by Prof. Lori Chibnik, Prof. John Torous, and Prof. Marzyeh Ghassemi. I was previously advised by Prof. Li Zhou and Prof. David Bates during my master’s at Harvard Medical School. Additional collaborators are listed in my CV.

    I actively advise students from Harvard and MIT, and I welcome collaboration and supervision inquiries from researchers with foundational experience or well-formed ideas. Please reach out by email.



    Timeline

    PhD in Population Health Sciences, Harvard T.H. Chan School of Public Health, Boston, MA    Fall 2023 – May 2027
    • PhD Intern: Dandelion Health, Boston, MA   [Jul 2025 – Present]
    • PhD Research Intern: Squirrel AI, Seattle, WA (Remote)   [Jun 2025 – Present]
    • Researcher: Department of Digital Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA   [2024 – Present]
    • Student Researcher: Department of Neurology, Massachusetts General Hospital, Boston, MA   [Oct 2025 – Present]
    • Research Assistant II: Department of Urology, Boston Children’s Hospital, Boston, MA   [Spring 2023 – Fall 2024]
    Master of Biomedical Informatics, Harvard Medical School, Boston, MA    Fall 2021 - Spring 2022
    • Research Assistant I & II: Department of Internal Medicine, Brigham Women's Hospital   [Fall 2021 - Flall, 2024]
    • Research Assistant II: Department of Anesthesia, Beth Israel Deaconess Medical Center   [Summer 2022]
    Undergraduate Visiting Student Program, Harvard College, Cambridge, MA    Fall 2020 - Spring 2021
    • Research Assistant: Language Learning Lab @Boston College with Joshua Hartshorne   [Fall 2020 - Fall 2021]
    • Research Intern: Mass General Hospital with Jennifer Haas   [Summer 2020 - Spring 2021]
    • Research Assistant : Harvard Medical School with Tianxi Cai   [Summer 2020 - Spring 2021]
    Bachelor of Arts, Smith College, Northampton, MA    Fall 2017 - Spring 2021

    Conference Talks (presenting)

    • 11/2025 — Charting the Evolution of AI Mental Health Chatbots from Rule-Based Systems to Large Language Models. AMIA Annual Symposium, Atlanta, GA.
    • 03/2024 — One Model Fits All? Multi-task UTD classification from neonatal US reports (NLP). AMIA Informatics Summit, Boston, MA.
    • 03/2024 — Wise instance selection reduces annotation for multi-task UTD prediction. AMIA Informatics Summit, Boston, MA.
    • 03/2024 — Identifying psychosis in admission notes: rules vs. ML vs. PLMs. AMIA Informatics Summit, Boston, MA.
    • 12/2023 — Benchmarking LLMs on CMExam (Chinese medical exams). NeurIPS, New Orleans, LA.
    • 06/2023 — Deep learning for social-media IR in public health. IEEE ICHI, Houston, TX.
    • 06/2023 — DL approach to identify transgender/gender-diverse patients in EHRs. IEEE ICHI, Houston, TX.
    • 04/2023 — Contemporary treatment and outcomes of myasthenia gravis (U.S.). AAN Annual Meeting, Boston, MA.
    • 11/2022 — Identifying transgender/gender-diverse individuals in EHRs. AMIA Annual Symposium, Washington, DC.
    • 11/2022 — Public perceptions of COVID-19 drugs on Twitter. AMIA Annual Symposium, Washington, DC.
    • 12/2021 — Quantifying bilingual (dis)advantage in vocabulary acquisition. Asia-Pacific Babylab Constellation Conference, Hong Kong.

    Awards, Fellowships & Funding

    • ACL 2025: Best Short Paper.
    • NeurIPS 2022: Spotlight (long paper); NeurIPS 2023: Travel Award.
    • IEEE ICHI 2023: Best Poster; AMIA 2022: Distinguished Poster.
    • Harvard T.H. Chan: Rose Traveling Fellowship (2024); Brian & Heidi MacMahon Epidemiology Educational Fund (2023–2024).
    • Sigma Xi 2021: Outstanding Student Researcher nominee.

    Review Service

    • Nature Portfolio: Nature Medicine (2024–2025), Nature Mental Health (2025), npj Digital Medicine (2024–2025).
    • JMIR Family (digital health): JMIR, JMIR Mental Health, JMIR Public Health and Surveillance (2024–2025).
    • Medical Informatics journals & conferences: JAMIA (2023–2024), International Journal of Medical Informatics (2022, 2024), AMIA Annual Symposium (2022–2023), AMIA Informatics Summit (2023).
    • ML/AI venues: NeurIPS (2023–2024), ML4H (2023), COLING (2022).

    Teaching

    • EPI 288: Intro to ML & Risk Prediction; Harvard T.H. Chan (Spring 2025).
    • PHS 2000A: Quantitative Research Methods; Harvard T.H. Chan (Fall 2024).
    • BMI 707 / EPI 290: Deep Learning for Biomedical Data; Harvard Medical School (Spring 2023).
    • S-043 / Stat 151: Multilevel & Longitudinal Models; Harvard GSAS (Summer 2021).

    Miscellaneous

    Examining the Impact of QuickReads Technology and Print Formats on Fluency, Comprehension, and Vocabulary Development for Elementary Students.
    Summarized by Yining Hua, directed by Luke W. Miratrix
    JREE 2021
    [Summerization]


    Last edited: 05/02/2025