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Junyi Gao (高峻逸)

junyii.gao AT gmail DOT com

PhD Student

Biography

I’m a PhD student in the Health Data Research UK (HDRUK) program. Before HDRUK, I was a PhD student at the University of Illinois at Urbana-Champaign supervised by Prof. Jimeng Sun.

My work focuses on developing machine learning and deep learning models to solve real world healthcare challenges. My passion for data science stems from my faith in technology to tackle practical problems. I hope my research can improve equity in healthcare.

News

  • Our work MedML for pediatric COVID-19 hospitalization and severity prediction was accepted by Cell iScience!
  • I have quitted my PhD program at UIUC and graduated with a MS degree because of the visa issue (the US 10043 Proclamation). I'll continue my PhD research in the Health Data Research UK (HDRUK) program.
  • Our work PopNet for population-level disease prediction with data latency was accepted by WWW 2022!

Research Interests

  • Artificial Intelligence
  • Data Mining
  • Healthcare

Education

  • PhD Student, 2022 - Present

    the Health Data Research UK

  • Master of Computer Science (Transferred from 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, 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. Pharmacoepidemiology and Drug Safety.

Junyi Gao, Cao Xiao, Lucas Glass, Jimeng Sun (2020). Dr. Agent: Clinical Predictive Model via Mimicked Second Opinions. JAMIA.

PDF Code DOI

Junyi Gao, Cao Xiao, Lucas Glass, Jimeng Sun (2020). COMPOSE: Cross-Modal Pseudo-Siamese Network for Patient Trial Matching. KDD. [Oral]

PDF Code Slides Video DOI

Cao Xiao, Junyi Gao, Lucas Glass, Jimeng Sun (2020). Patient trial matching using pseudo-siamese network. JCO.

DOI

Junyi Gao, Cao Xiao, Yasha Wang, Lucas Glass, Wen Tang, Jimeng Sun (2020). StageNet: Stage-Aware Neural Networks for Health Risk Prediction. WWW. [Oral]

PDF Code Slides Video DOI

Liantao Ma, Junyi Gao, Yasha Wang, Chaohe Zhang, Jiangtao Wang, Wenjie Ruan, Wen Tang, Xin Gao and Xinyu Ma (2020). AdaCare: Explainable Clinical Health Status Representation Learning via Scale-Adaptive Feature Extraction and Recalibration. AAAI. [Oral]

PDF Code Video Media coverage

Liantao Ma, Chaohe Zhang, Yashang Wang, Wenjie Ruan, Jiangtao Wang, Wen Tang, Xinyu Ma, Xin Gao, Junyi Gao (2020). ConCare: Personalized Clinical Feature Embedding via Capturing the Healthcare Context. AAAI.

PDF Code Poster

Jingyue Gao, Xiting Wang, Yasha Wang, Zhao Yang, Junyi Gao, Jiangtao Wang, Wen Tang, Xing Xie (2019). CAMP: Co-Attention Memory Networks for Diagnosis Prediction in Healthcare. ICDM. [Oral]

PDF Code

Junyi Gao*, Weihao Tan*, Liantao Ma, Yasha Wang and Wen Tang (2019). MUSEFood: Multi-sensor-based Food Volume Estimation on Smartphones. IEEE UIC. [Oral]

PDF Code Dataset Slides Video

Wen Tang, Junyi Gao, Xinyu Ma, Chaohe Zhang, Liantao Ma, Yasha Wang (2019). Applications of Recurrent Neural Network in Clinical Prognosis Prediction of Peritoneal Dialysis. Journal of Peking University, Health sciences.

PDF DOI PubMed

Zhengtong Shi, Junyi Gao, Liantao Ma, Yasha Wang, Jiangtao Wang, Wen Tang (2018). Multi-sensor integrated food volume measurement based on smartphone. PCC. [Oral]

PDF

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)

Talks, Media coverage & Professional service

  • Reviewer for JAMIA, AAAI, TKDE, IEEE-TSIPN
  • 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

  • 3rd prize, Big Ten Augmented Intelligence Bowl (Top 3 out of 14 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