Research

You can also find my articles on my Google Scholar profile.

Working Papers

Machine learning for deceased donor kidney allocation
Nikhil Agarwal, Itai Ashlagi, Grace Guan, Paulo Somaini, and Jiacheng Zou (alphabetical)
Preliminary version in NeurIPS 2022 Workshop on Learning from Time Series for Health (spotlight presentation).

Conference Publications

Predicting sick patient volume in a pediatric outpatient setting using time series analysis
Grace Guan, Barbara Engelhardt
MLHC 2019: Proceedings of Machine Learning Research, 2019, 106:271-287
[paper] [code]
🏆 Won 2020 NCWIT Collegiate Award Honorable Mention

Journal Publications

Resource utilization and costs associated with approaches to identify infants with early onset sepsis
Grace Guan, Neha S. Joshi, Adam Frymoyer, Grace D. Achepohl, Rebecca Dang, N. Kenji Taylor, Joshua A. Salomon, Jeremy D. Goldhaber-Fiebert, and Douglas K. Owens
Medical Decision Making: Policy & Practice, 2024, 9(1)
[paper]

Higher sensitivity monitoring of reactions to COVID-19 vaccination using smartwatches
Grace Guan, Merav Mofaz, Gary Qian, Tal Patalon, Erez Shmueli, Dan Yamin, and Margaret L. Brandeau
NPJ Digital Medicine, 2022, 5(1): 140
[paper] [code]

Self-reported and physiological reactions to the third BNT162b2 mRNA COVID-19 (booster) vaccine dose
Merav Mofaz, Matan Yechezkel, Grace Guan, Margaret L. Brandeau, Tal Patalon, Sivan Gazit, Dan Yamin, and Erez Shmueli
Emerging Infectious Diseases, 2022, 28(7):1375-1383
[paper]

Early detection of COVID-19 outbreaks using human mobility data
Grace Guan, Yotam Dery, Matan Yechezkel, Irad Ben-Gal, Dan Yamin, and Margaret L. Brandeau
PLoS ONE, 2021, 16(7):e0253865
[paper] [code]
🏆 Won 2022 NCWIT Collegiate Award Honorable Mention

Theses

Empirical characteristics of Affordable Care Act risk transfers
Grace Guan, advised by Mark Braverman
Princeton Computer Science Senior Thesis
[paper]
🏆 Won Outstanding Computer Science Senior Thesis Prize
🏆 Won Princeton’s Choice Award at Princeton Research Day 2018

Non-Archival Conference Talks and Posters

• “Machine learning for deceased donor kidney allocation”
  • INFORMS Annual Meeting, Phoenix, AZ, 2023 [talk]
  • INFORMS Healthcare, Toronto, Canada, 2023 [talk]
  • NeurIPS Learning from Time Series for Health Workshop, New Orleans, LA, 2022 [spotlight talk]
  • INFORMS Annual Meeting, Indianapolis, IN, 2022 [talk by coauthor]
• “Higher sensitivity monitoring of reactions to COVID-19 vaccination using smartwatches”
  • SMDM Annual Meeting, Seattle, WA, 2022 [poster]
  • INFORMS Annual Meeting, Indianapolis, IN, 2022 [talk]
• “Empirical characteristics of Affordable Care Act risk transfers”
  • INFORMS Healthcare, Virtual, 2021 [talk]
  • Princeton Research Day, Princeton, NJ, 2018 [poster]
• “Resource utilization and costs associated with approaches to identify infants with early onset sepsis”
  • The Decision Sciences for Child Health Collaborative at SMDM, Virtual, 2021 [invited talk]
  • SMDM Annual Meeting, Virtual, 2021 [poster]
  • Pediatric Hospital Medicine Conference, Virtual, 2021 [poster]
• “Early detection of COVID-19 outbreaks using human mobility data”
  • INFORMS Annual Meeting, Virtual, 2021 [talk]
  • INFORMS Healthcare Conference, Virtual, 2021 [talk]