Ruoqi Liu

Short Biography

I’m a second-year Ph.D. student at the Department of Computer Science and Engineering, The Ohio State University (OSU). I’m fortunately working with Prof. Ping Zhang in AIMed (Artificial Intelligence in Medicine) Lab. My research interests focus on data mining, causal inference and their applications in healthcare.

News

• [Jan 2021] Our paper “A deep learning framework for drug repurposing via emulating clinical trials on real world patient data” is published on Nature Machine Intelligence, which is featured at OHIO STATE NEWS.
• [Nov 2020] Our paper “A deep learning framework for drug repurposing via emulating clinical trials on real world patient data” is accepted to Nature Machine Intelligence.
• [Aug 2020] Our paper “Estimating Individual Treatment Effects with Time-Varying Confounders” is accepted to ICDM 2020.
• [May 2020] Our paper “Identifying sepsis subphenotypes via time-aware multi-modal auto-encoder” is accepted to KDD 2020.

Publications

• A deep learning framework for drug repurposing via emulating clinical trials on real world patient data
  Ruoqi Liu, Lai Wei, Ping Zhang
  Nature Machine Intelligence, Jan. 2021.
  [Paper] [Code]
  Selected media coverage: IN BRIEF of Nature Reviews Drug Discovery, Headline of OHIO STATE NEWS, Top 5% of all research ouputs scores by Altmetric

• Estimating Individual Treatment Effects with Time-Varying Confounders
  Ruoqi Liu, Changchang Yin, Ping Zhang
  IEEE International Conference on Data Mining. ICDM 2020. (Acceptance rate: 91/930 = 9.8%, regular paper, oral presentation)
  [Paper] [Code]

• When deep learning meets causal inference: a computational framework for drug repurposing from real-world data
  Ruoqi Liu, Lai Wei, Ping Zhang
  arXiv Preprint.
  [Paper] [Code]

• Identifying sepsis subphenotypes via time-aware multi-modal auto-encoder
  Changchang Yin, Ruoqi Liu, Dongdong Zhang, Ping Zhang
  ACM SIGKDD Conference on Knowledge Discovery and Data Mining. KDD 2020. (Acceptance rate: 216/1279 = 16.9%, research track)
  [Paper] [Code] [Video]

• Clinical connectivity map for drug repurposing: using laboratory tests to bridge drugs and diseases
  Qianlong Wen*, Ruoqi Liu*, Ping Zhang (*equal contributions)
  International Conference on Intelligent Biology and Medicine. ICIBM 2020.
  [Paper] [Code]

• Towards early detection of adverse drug reactions: combining pre-clinical drug structures and post-market safety reports
  Ruoqi Liu, Ping Zhang
  BMC Medical Informatics and Decision Making (19:279, 2019)
  [Paper] [Code]

• Predicting drug-disease associations by using similarity constrained matrix factorization
  Wen Zhang, Xiang Yue, Weiran Lin, Wenjian Wu, Ruoqi Liu, Feng Huang, Feng Liu
  BMC Bioinformatics (19:233, 2018)
  [Paper] [Web Server][Code]

• Predicting drug-disease associations and their therapeutic function based on the drug-disease association bipartite network
  Wen Zhang, Xiang Yue, Feng Huang, Ruoqi Liu, Yanlin Chen, Feng Huang, Chunyang Ruan
  Methods (145:51-59, 2018)
  [Paper]

Services

• Conference sub reviewer: KDD, IJCAI, AAAI, ICML, ICDM, SDM.
• Journal sub reviewer: Patterns, Nature Communication, BMC Bioinformatics.
• Conference reviewer: AMIA
• Journal reviewer: BMC Medical Informatics and Decision Making

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