Jiacheng Miao

I am a HAI/Data Science Postdoc Fellow at Stanford University, working with Jonathan Pritchard and James Zou.

I am building AI agents for scientific discovery, especially:

• How do we make scientific knowledge agent-native?
• How might AI agents change or distort science?

Email me at jcmiao[at]stanford.edu. See my Google Scholar for a full list of my work.

Research  /  Data  /  Software  /  Github  /  Twitter

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Selected Papers

AI agents & AI/ML for scientific discovery

• The Agentic Garden of Forking Paths
  Miao J., Pritchard J.K., Zou J. 2026.
• Paper2Agent: Reimagining Research Papers As Interactive and Reliable AI Agents [code]
  Miao J., Davis J., Zhang Y., Pritchard J., Zou J. 2025. (2.2k Github stars)
• Valid inference for machine learning-assisted genome-wide association studies
  Miao J., Wu Y., Sun Z., Miao X., Lu T., Zhao J., Lu Q. Nature Genetics, 2024.
• Assumption-lean and data-adaptive post-prediction inference
  Miao J.*, Miao X.*, Wu Y., Zhao J., Lu Q. Journal of Machine Learning Research, 2025.
• Task-agnostic machine-learning-assisted inference
  Miao J. and Lu Q. NeurIPS, 2024.

Statistical & AI methods for human genetics

• Understanding nature and nurture: Statistical and AI innovations uncover how genes and environment shape human health
  Miao J. Science, 2025.
• Polygenic prediction of treatment efficacy with causal transfer learning
  Miao J.*, Mu J.*, Yang X., Fletcher J., Schmitz L., Lu Q. In revision at Nature Genetics, 2025.
• PIGEON: a statistical framework for estimating gene-environment interaction for polygenic traits
  Miao J., Song G., Wu Y., et al. Nature Human Behaviour, 2025.
• Quantifying portable genetic effects and improving cross-ancestry genetic prediction with GWAS summary statistics
  Miao J.*, Guo H.*, Song G., Zhao Z., Hou L., Lu Q. Nature Communications, 2023.
• A quantile integral linear model to quantify genetic effects on phenotypic variability
  Miao J., Lin Y., Wu Y., Zheng B., Schmitz L., Fletcher J., Lu Q. PNAS, 2022.