Jiacheng Miao
I am a Postdoc at Stanford University, working with Jonathan Pritchard and James Zou. 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.
My research focuses on building reliable AI co-scientists to accelerate scientific discovery and interpreting disease-associated genes using Perturb-seq.
During my PhD, I developed methods and theory to ensure the trustworthy use of AI/ML-generated data in scientific data analyses and to understand how genes and the environment jointly influence complex traits.
Here are the selected papers, software I develoepd, google scholar, and CV.
E-mail: jcmiao at stanford.edu
News
[08/2025]: Excited to receive the NOMIS & Science Young Explorer Award!
[06/2025]: PSPA accepted at Journal of Machine Learning Research (JMLR) for assumption-lean and data-adaptive ML-assisted statistical inference.
[05/2025]: PIGEON published in Nature Human Behaviour for polygenic gene-environment interaction inference using GWIS summary statistics.
[09/2024]: POP-GWAS published in Nature Genetics for the reliable use of AI/ML to accelerate genetic discovery; PSPS accepted by NeurIPS 2024 for task-agnostic ML-assisted statistical inference.
[05/2024]: Won the 2024 ICSA Student Paper Award with POP-GWAS.
[11/2023]: Check out PSPA for assumption-lean and data-adaptive ML-assisted statistical inference.
[08/2023]: Had a very fun internship at the Regeneron Genetic Center.
[02/2023]: X-Wing published in Nature Communications to identify portable genetic effects and improve genetic risk prediction in ancestrally diverse populations.
[09/2022]: QUAIL published in PNAS to identify genetic associations with phenotypic variability.
[01/2022]: Won the 2022 ASA Section on Statistics in Genomics and Genetics Student Paper Award with QUAIL.