Jiacheng Miao
Hi, I am a fifth year Ph.D. candidate in Biomedical Data Science at University of Wisconsin-Madison, advised by Prof. Qiongshi Lu and Lauren Schmitz. Previously, I got my undergraduate degree in Statistics from Nanjing University.
I am interested in the reliable use of AI/ML to accelerate genetic and scientific discovery, and in understanding the mechanisms and implications of treatment and genetic effect heterogeneity.I develop theory, methods, and software for dissecting how genetic variation impact human complex traits and diseases, with a focus on accelerating drug discovery and advancing precision medicine.
Here are my selected papers, google scholar, and CV.
News
09/24: 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.
09/24: 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.
05/24: Jiacheng won the 2024 ICSA Student Paper Award with POP-GWAS.
11/23: Check out PSPA for assumption-lean and data-adaptive ML-assisted statistical inference.
09/23: Yixuan, an undergraduate student mentored by Jiacheng, won the 2023 Charles J. Epstein Trainee Award for Excellence in Human Genetics Research Semifinalist.
08/23: Jiacheng had a very fun internship at the Regeneron Genetic Center.
02/23: X-Wing published in Nature Communications to identify portable genetic effects and improve genetic risk prediction in ancestrally diverse populations.
12/22: Check out PIGEON for polygenic gene-environment interaction inference using GWIS summary statistics.
09/22: QUAIL published in PNAS to identify genetic associations with phenotypic variability.
01/22: Jiacheng won the 2022 ASA Section on Statistics in Genomics and Genetics Student Paper Award with QUAIL.