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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 deep-based clinical predictive modeling with electronic health record (EHR) data, population-level spatio-temporal healthcare predictions and clinical trial optimizations.

News

Research Interests

  • Artificial Intelligence
  • Data Mining
  • Healthcare

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

My research includes:

  • Predictive modeling with knowledge graph
  • Population-level spatio-temporal prediction
 
 
 
 
 

Machine learning research intern

Analytics Center of Excellence, IQVIA

May 2019 – Present Beijing, China Advisor: Dr. Cao Xiao, Prof. Jimeng Sun

My research includes:

  • Deep computational phenotyping
  • Patient trial matching
 
 
 
 
 

Research assistant

Software Engineering Insisute, Peking University

Jan 2017 – Aug 2020 Beijing, China Advisor: Prof. Yasha Wang

My research includes:

  • Deep computational phenotyping
  • Interpretable predictive models for healthcare

Publications

Junyi Gao, Joerg Heintz, Christina Mack, Lucas Glass, Adam Cross, Jimeng Sun (2023). Evidence-Driven Spatio-Temporal COVID-19 Hospitalization Prediction with Ising Dynamics. Nature Communications.

PDF Code DOI

Junyi Gao, Yinghao Zhu, Wenqing Wang, Yasha Wang, Wen Tang, Liantao Ma (2023). A Comprehensive Benchmark For COVID-19 Predictive Modeling Using Electronic Health Records in Intensive Care. AMIA. [Abstract, Oral]

PDF Code Slides

Chaoqi Yang*, Zhenbang Wu*, Patrick Jiang, Zhen Lin, Junyi Gao, Benjamin Danek, Jimeng Sun (2023). PyHealth: A Deep Learning Toolkit For Healthcare Applications. KDD. [Tutorial]

Code

Junyi Gao*, Yinghao Zhu*, Wenqing Wang*, Yasha Wang, Wen Tang, Liantao Ma (2022). A Comprehensive Benchmark for COVID-19 Predictive Modeling Using Electronic Health Records in Intensive Care: Choosing the Best Model for COVID-19 Prognosis. arXiv preprint.

PDF Code Project

Estee Y. Cramer, et al. [US COVID-19 Forecast Hub Consortium, including Junyi Gao] (2022). The United States COVID-19 Forecast Hub dataset. Nature Scientific Data.

PDF Code Dataset DOI

Junyi Gao, Chaoqi Yang, George Heintz, Scott Barrows, Elise Albers, Mary Stapel, Sara Warfield, Adam Cross, Jimeng Sun (2022). MedML: Fusing Medical Knowledge and Machine Learning Models for Early Pediatric COVID-19 Hospitalization and Severity Prediction. Cell iScience.

PDF Code Video DOI

Junyi Gao, Cao Xiao, Lucas Glass, Jimeng Sun (2022). PopNet: Real-Time Population-Level Disease Prediction with Data Latency. WWW.

PDF Code

Junyi Gao, Rakshith Sharma, Cheng Qian, Lucas M. Glass, Jeffrey Spaeder, Justin Romberg, Jimeng Sun, Cao Xiao (2021). STAN: Spatio-Temporal Attention Network for Pandemic Prediction Using Real World Evidence. JAMIA.

PDF Code DOI

Liantao Ma, Xinyu Ma, Junyi Gao, Chaohe Zhang, Zhihao Yu, Xianfeng Jiao, Wenjie Ruan, Yasha Wang, Wen Tang, Jiangtao Wang (2021). CovidCare: Transferring Knowledge from Existing EMR to Emerging Epidemic for Interpretable Prognosis. WWW. [Oral]

PDF

Cao Xiao, Junyi Gao, Lucas M. Glass, Jimeng Sun, Christina Mack (2020). Two Machines Are Better Than One: Using Multi-Agent Reinforcement in Machine Learning to Simulate A Clinical Second Opinion. Pharmacoepidemiology and Drug Safety. [Abstract]

See all publications

Application Projects

Vaccine Hero

Machine Learning Powered Mobile HealthCare Unit for Addressing Childhood Vaccination Disparities

Dr. Vis

A visualization tool to help clinicians identify risky patients and cohorts

Healthcare platform for chronic diseases

A healthcare management platform that can automatically recognize food intake and lab test report

MUSEFood

Estimate food and nutrition intake by taking photos using your smartphone

Patents

  • A method and device of determining potentially important information of patients, CN 202010946290.4, (Under verification)
  • A method and system for sound wave and image-based food volume measurement on smart phone, CN 202010862933.7, (Under verification)

Media coverage & Professional service

Awards

  • 3rd prize, Predicting High Risk Breast Cancer: a Nightingale OS & AHLI data challenge (Top 3 out of all teams)
  • 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)

Teaching

I have served as a teaching assistant for the following courses at Beihang University:

  • Technical Writing for Graduate, Fall & Spring 2018
  • Program Design, Summer 2017