CTYPE html> Publications | Ruishan Liu

Selected Publications

AI for healthcare and biomedicine.

  1. Systematic analysis of off-label and off-guideline cancer therapy usage in a real-world cohort of 165,912 US patients [PDF]
    Ruishan Liu, Lisa Wang, Shemra Rizzo, Marius Rene Garmhausen, Navdeep Pal, Sarah Waliany, Sarah McGough, Yvonne G Lin, Zhi Huang, Joel Neal, and  others
    Cell Reports Medicine (2024).
  2. Systematic pan-cancer analysis of mutation–treatment interactions using large real-world clinicogenomics data [PDF]
    Ruishan Liu, Shemra Rizzo, Sarah Waliany, Marius Rene Garmhausen, Navdeep Pal, Zhi Huang, Nayan Chaudhary, Lisa Wang, Chris Harbron, Ryan Neal, and James Zou
    Nature Medicine (2022). Best Poster Award at BBSW meeting.
  3. Dynamical Systems Model of RNA Velocity Improves Inference of Single-cell Trajectory, Pseudo-time and Gene Regulation [PDF]
    Ruishan Liu, Angela Oliveira Pisco, Emelie Braun, Sten Linnarsson, and James Zou
    Journal of Molecular Biology (2022).
  4. Evaluating eligibility criteria of oncology trials using real-world data and AI [PDF]
    Ruishan Liu, Shemra Rizzo, Samuel Whipple, Navdeep Pal, Arturo Lopez Pineda, Michael Lu, Brandon Arnieri, Ying Lu, William Capra, Ryan Copping, and James Zou
    Nature (2021). Top Ten Clinical Research Achievement 2022; Finalist for Global Pharma Award 2021.
  5. Modeling spatial correlation of transcripts with application to developing pancreas [PDF]
    Ruishan Liu, Marco Mignardi, Robert Jones, Martin Enge, Seung K Kim, Stephen R Quake, and James Zou
    Scientific reports (2019).

Machine learning.

  1. Data-driven subgroup identification for linear regression [PDF]
    Zachary Izzo,  Ruishan Liu, and James Zou
    ICML (2023).
  2. Data sculpting: interpretable algorithm for end-to-end cohort selection [PDF]
    Ruishan Liu, and James Zou
    IEEE Asilomar (2022). Best Student Paper Finalist.
  3. Learning transport cost from subset correspondence [PDF]
    Ruishan Liu, Akshay Balsubraman, and James Zou
    ICLR (2020).
  4. The effects of memory replay in reinforcement learning [PDF]
    Ruishan Liu, and James Zou
    IEEE Allerton (2018). Best Poster Award at BayLearn Symposium 2017.
  5. Model compression with generative adversarial networks [PDF]
    Ruishan Liu, Nicolo Fusi, and Mackey Mackey
    NeurIPS Smooth Games Optimization and Machine Learning Workshop (NeurIPS SGO&ML) (2018).