Papers

Notes: * stands for equal contributions; $^\dagger$ stands for students that I mentored.

Preprints

MORPH Predicts the Single-cell Outcome of Genetic Perturbations across Various Data Modalities
Chujun He*, Jiaqi Zhang*, Munther Dahleh, Caroline Uhler.
[bioRxiv] [code] [bibtex]

On the Number of Conditional Indepdence Tests in Constraint-based Causal Discovery
Marc Franquesa Monés$^\dagger$*, Jiaqi Zhang*, Caroline Uhler.

Learning Genetic Perturbation Effects with Variational Causal Inference
Emily Liu$^\dagger$*, Jiaqi Zhang*, Caroline Uhler.
[bioRxiv] [code] [bibtex]

Faithfulness and Intervention-Only Causal Discovery
Bijan Mazaheri, Jiaqi Zhang, Caroline Uhler.
[workshop]

Meta-Dependence in Conditional Independence Testing
Bijan Mazaheri, Jiaqi Zhang, Caroline Uhler.
[arXiv] [code] [bibtex]

Publications

Can Diffusion Models Disentangle? A Theoretical Perspective
Liming Wang, Muhammad Jehanzeb Mirza, Yishu Gong, Yuan Gong, Jiaqi Zhang, Brian H. Tracey, Katerina Placek, Marco Vilela, James R. Glass. NeurIPS, 2025.

Probabilistic Factorial Experimental Design for Combinatorial Interventions
Divyal Shyamal$^\dagger$*, Jiaqi Zhang*, Caroline Uhler. ICML (Spotlight, < 2.6%), 2025.
[arXiv] [conference] [bibtex]

Identifiabiltiy Guarantees of Causal Disentanglement from Purely Observational Data
Ryan Welch$^\dagger$*, Jiaqi Zhang*, Caroline Uhler. NeurIPS, 2024.
[arXiv] [code] [conference] [bibtex]

Causal Discovery with Fewer Conditional Independence Tests
Kirankumar Shiragur*, Jiaqi Zhang*, Caroline Uhler. ICML, 2024.
[arXiv] [code] [bibtex]

Towards Causal Foundation Model: on Duality between Causal Inference and Attention
Jiaqi Zhang*, Joel Jennings, Agrin Hilmkil, Nick Pawlowski, Cheng Zhang, Chao Ma*. ICML, 2024.
[arXiv] [code] [bibtex]

Membership Testing in Markov Equivalence Classes via Independence Query Oracles
Jiaqi Zhang*, Kirankumar Shiragur*, Caroline Uhler. AISTATS (Oral Presentation, <3%), 2024.
[arXiv] [conference] [bibtex]

Meek Separators and Their Applications in Targeted Causal Discovery
Kirankumar Shiragur*, Jiaqi Zhang*, Caroline Uhler. NeurIPS, 2023.
[arXiv] [code] [conference] [bibtex]

Identifiability Guarantees for Causal Disentanglement from Soft Interventions
Jiaqi Zhang, Kristjan Greenewald, Chandler Squires, Akash Srivastava, Karthikeyan Shanmugam, Caroline Uhler. NeurIPS, 2023.
[arXiv] [code] [conference] [bibtex]

Active Learning for Optimal Intervention Design in Causal Models
Jiaqi Zhang, Louis Cammarata, Chandler Squires, Themistoklis P Sapsis, Caroline Uhler. Nature Machine Intelligence, 2023.
[arXiv] [code] [journal] [bibtex]

Machine-learning-optimized Cas12a Barcoding Enables the Recovery of Single-cell Lineages and Transcriptional Profiles
Nicholas W Hughes, Yuanhao Qu*, Jiaqi Zhang*, Weijing Tang*, Justin Pierce*, Chengkun Wang, Aditi Agrawal, Maurizio Morri, Norma Neff, Monte M Winslow, Mengdi Wang, Le Cong. Molecular Cell, 2022.
[code] [journal] [bibtex]

Stochastic Augmented Projected Gradient Methods for the Large-Scale Precoding Matrix Indicator Selection Problem
Jiaqi Zhang, Zeyu Jin, Bo Jiang, Zaiwen Wen. IEEE Transactions on Wireless Communications, 2022.
[journal] [bibtex]

Matching a Desired Causal State via Shift Interventions
Jiaqi Zhang, Chandler Squires, Caroline Uhler. NeurIPS, 2021.
[arXiv] [code] [conference] [bibtex]