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Junyi Gao (高峻逸)

junyii.gao AT gmail DOT com

PhD Student

Biography

I’m a PhD student at the University of Edinburgh funded by the HDR UK-Turing Wellcome PhD Programme supervised by Prof. Ewen Harrison. Previously, I was a PhD student at the University of Illinois at Urbana-Champaign supervised by Prof. Jimeng Sun. Before UIUC, I worked closely with Prof. Yasha Wang and Dr. Liantao Ma at Peking University as a research assistant.

My research focuses on individual-level clinical predictions, population-level spatio-temporal epidemiology predictions, clinical trial optimizations and medical foundation models. I also work on developing toolkits and platforms for medical researchers and clinical practice usage.

News

  • I gave a talk about Building trustworthy and accessible clinical predictive models: from deep learning to LLMs in the University of Edinburgh CMI Seminar.
  • Three paper accepted in KDD workshop!
  • I gave a talk about Real-World Knowledge-Infused Pandemic Prediction (Chinese) in the Health Data Science seminar. Thank Peking University and Health Data Science journal for the invitation.

Education

  • PhD Student, 2022 - Present

    Funded by the HDR UK-Turing Wellcome PhD Programme

    University of Edinburgh

  • Master of Computer Science (Transferred from the PhD program), 2020 - 2022

    University of Illinois at Urbana-Champaign

  • Bachelor of Engineering in Software Engineering, 2015 - 2019

    Honored Graduate

    Beihang University

Experience

 
 
 
 
 

Research assistant

University of Illinois at Urbana-Champaign

Aug 2020 – May 2022 IL, United States Advisor: Prof. Jimeng Sun
Individual-level clinical predictions and populatio-level spatio-temporal epidemiology predictions
 
 
 
 
 

Machine learning research intern

Analytics Center of Excellence, IQVIA

May 2019 – Dec 2023 Beijing, China Advisor: Dr. Cao Xiao
Clinical trial optimizations and spatio-temporal predictions
 
 
 
 
 

Research assistant

Software Engineering Insisute, Peking University

Jan 2017 – Aug 2020 Beijing, China Advisor: Prof. Yasha Wang
Deep computational phenotyping and developing interpretable predictive models for healthcare

Publications

* for equal contributions
+ for corresponding author

Media coverage & Professional service

  • Guest editor of spj journal Health Data Science
  • Co-organizer of KDD'24 workshop Artificial Intelligence and Data Science for Healthcare:Bridging Data-Centric AI and People-Centric Healthcare
  • Program Committee member for ICML'24; ICLR'24,25; NeurIPS'23,24; KDD'23,24,25; AAAI'25; AMIA Annual Symposium'23,24; AMIA Informatics Summit'24,25; ML4H'22,23,24; SDM'24
  • Reviewer for
    - The Lancet Regional Health
    - The New England Journal of Medicine AI (NEJM AI)
    - IEEE Journal of Biomedical and Health Informatics (JBHI)
    - IEEE Transactions on Knowledge and Data Engineering (TKDE)
    - Journal of the American Medical Informatics Association (JAMIA)
    - Health Data Science (HDS)
    - IEEE Transactions on Signal and Information Processing over Networks (IEEE SIPN)
    - BMJ Surgery
    - International Journal of Digital Earth (IJDE)
  • Invited talk for Building trustworthy and accessible clinical predictive models: from deep learning to LLMs at University of Edinburgh CMI Seminar, 2024.09.
  • Invited talk for Real-World Knowledge-Infused Pandemic Predictions (Chinese) at the Health Data Science seminar, hosted by Peking University and the Health Data Science Journal, 2024.04.
  • Invited talk for the High Risk Breast Cancer Prediction Challenge at ML4H 2022, 2022.11.
  • The MedML paper is invited to present at the N3C Fourm, 2022.10.
  • Invited talk on AI Time Seminar in Tsinghua University, 2020.09.
  • Our paper AdaCare and project Dr. Vis were covered by CCTV-1 news, 2020.07.

Awards & Grants

  • OpenAI researcher grant (PI), 2024 - 2025
  • Reviewer Award, AMIA 2024
  • 3rd prize, Predicting High Risk Breast Cancer: a Nightingale OS & AHLI data challenge (Top 3 out of all teams)
  • HDRUK-Wellcome PhD Funding (~£100,000)
  • 3rd prize, Big Ten Augmented Intelligence Bowl (Top 3 out of all teams from US universities)
  • Honored Graduate of Beihang University
  • AAAI 2020 Student Travel Award
  • 2018 MCM/ICM Meritorious Winner (10%)
  • 2018 Beihang University Science and Technology Competition Scholarship (Top 1%)
  • 2018 Beihang University Academic Excellence Scholarship (Top 5%)
  • 2017 Beihang University Science and Technology Competition Scholarship (Top 1%)
  • 2016 Beihang University Feng Ru Cup Technology Innovation Competition 1st prize (10 out of candidates of all majors)

Academic Services & Misc.

  • Teaching Assistant, Foundations of software development in health and social care, 2024
  • Panel member of The HDR UK-Wellcome Biomedical Vacation Scholarship (BVS) programme recruitment team, 2024
  • Panel member of HDRUK PhD program recruitment team, 2023
  • Teaching Assistant, HealthR Course, 2023
  • Teaching Assistant, Technical Writing for Graduate, Fall & Spring 2018
  • Teaching Assistant, Program Design, Summer 2017

Patents

  • A method and device of determining potentially important information of patients, CN 202010946290.4, filed Oct 09, 2020.
  • A method and system for sound wave and image-based food volume measurement on smart phone, CN 202010862933.7, filed Aug 25, 2020.