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Hi! I am Jiacheng, a data science postdoctoral fellow at Stanford University, working with Jonathan Pritchard and James Zou. I am building AI co-scientists to reshape how science is communicated and applied, and characterizing the omnigenic architecture of complex diseases using Perturb-seq.

Previously, I received my Ph.D. at the University of Wisconsin–Madison, advised by Qiongshi Lu and Lauren Schmitz. I completed my B.S. in Department of Mathematics at Nanjing University. During my Ph.D., I developed methods and theory for trustworthy use of AI/ML-generated data in scientific analyses and for understanding how genes and the environment jointly influence human complex traits. Here are my selected papers, software, google scholar, and CV.

E-mail: jcmiao at stanford dot edu

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News

• [Nov 2025]: Excited to see "Understanding nature and nurture: Statistical and AI innovations uncover how genes and environment shape human health" published in Science Magazine.
• [Nov 2025]: New preprint: M-Learner for predicting treatment efficacy from germline genetic variations with causal transfer learning.
• [Oct 2025]: Excited to see Paper2Agent was featured by Anthropic as one of the partnerships powered by Claude.
• [Sep 2025]: Excited to share my first postdoc work: we release Paper2Agent that reimagines static research papers into interactive AI agents (>1.8k Github stars)

More news...

• [Sep 2025]: PSPA published in Journal of Machine Learning Research (JMLR) for method and theory for trustworthy scientific data analysis using AI/ML-generated data.
• [Aug 2025]: Excited to receive the NOMIS & Science Young Explorer Award.
• [Jun 2025]: Starting my postdoc at Stanford! I will work on building reliable AI co-scientists to accelerate scientific discovery and interpreting disease-associated genes using Perturb-seq.
• [May 2025]: PIGEON published in Nature Human Behaviour for understanding the joint role of genes and the environment in human complex traits.
• [Sep 2024]: POP-GWAS published in Nature Genetics for the reliable use of AI/ML-generated data to accelerate genetic discovery.
• [Sep 2024]: PSPS accepted by NeurIPS 2024 for task-agnostic scientific data analysis using AI/ML-generated data.
• [May 2024]: Won the 2024 ICSA Student Paper Award with POP-GWAS.
• [Aug 2023]: Had a very fun internship at the Regeneron Genetic Center.
• [Feb 2023]: X-Wing published in Nature Communications to identify portable genetic effects and improve genetic risk prediction in different populations.
• [Sep 2022]: QUAIL published in PNAS to identify genetic associations with phenotypic variability.
• [Jan 2022]: Won the 2022 ASA Section on Statistics in Genomics and Genetics Student Paper Award with QUAIL.

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Selected Publications

• Paper2Agent: Reimagining Research Papers As Interactive and Reliable AI Agents
  Miao J., Davis J., Pritchard J., Zou J. (2025) [Preprint] [Software]
• [Nature Genetics] Valid inference for machine learning-assisted genome-wide association studies
  Miao J., Wu Y., Sun Z., Miao X., Lu T., Zhao J., Lu Q. (2024) [Journal] [Software]
• [Journal of Machine Learning Research] Assumption-lean and data-adaptive post-prediction inference
  Miao J.*, Miao X.*, Wu Y., Zhao J., Lu Q. (2025) [Journal] [Software]
• [Nature Human Behaviour] PIGEON: a statistical framework for estimating gene-environment interaction for polygenic traits
  Miao J., Song G., Wu Y., et al. (2025) [Journal] [Software]

More publications...

• [NeurIPS] Task-agnostic machine-learning-assisted inference
  Miao J. and Lu Q. (2024) [Paper] [Software]
• [Nature Communications] 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. (2023) [Journal] [Software]
• [PNAS] 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. (2022) [Journal] [Software]