AMICI: Attention Mechanism Interpretation of Cell-cell Interactions
Justin Hong*, Khushi Desai*, Tu Duyen Nguyen, Achille Nazaret, Nathan Levy, Can Ergen, George Plitas, and Elham Azizi.
bioRxiv (2025), pp. 2025–09. [URL].

Domain-Invariant Feature Learning for Patient-Level Phenotype Prediction from Single-Cell Data
Mathias Perez*, Justin Hong*, Aaron Zweig, and Elham Azizi.
AI for Science workshop, NeurIPS 2025 (2025). [URL].

Deep generative modeling of sample-level heterogeneity in single-cell genomics
Pierre Boyeau*, Justin Hong*, Adam Gayoso, Martin Kim, José L McFaline-Figueroa, Michael I Jordan, Elham Azizi, Can Ergen, and Nir Yosef.
Nature Methods (2025). [URL].

The CausalBench challenge: A machine learning contest for gene network inference from single-cell perturbation data
Mathieu Chevalley, ..., Justin Hong, ..., and Patrick Schwab.
Fourth Conference on Causal Learning and Reasoning (CLeaR 2025) (2025). [URL].

Mapping multimodal phenotypes to perturbations in cells and tissue with CRISPRmap
Jiacheng Gu, ..., Justin Hong, ..., and Jellert T Gaublomme.
Nature Biotechnology (2024). [URL].

Stable Differentiable Causal Discovery
Achille Nazaret*, Justin Hong*, Elham Azizi, and David Blei.
Proceedings of the 41st International Conference on Machine Learning (ICML) (2024). [URL].

A heterogeneous pharmaco-transcriptomic landscape induced by targeting a single oncogenic kinase
Ross M Giglio, ..., Justin Hong, ..., and Jose L McFaline-Figueroa.
bioRxiv (2024). [URL].

BetterBoost-Inference of Gene Regulatory Networks with Perturbation Data
Achille Nazaret and Justin Hong.
GSK.ai CausalBench Challenge, Machine Learning for Drug Discovery (MLDD) Workshop at ICLR, 1st Place Prize, Oral Presentation (2023). [URL].

Deep generative modeling of transcriptional dynamics for RNA velocity analysis in single cells
Adam Gayoso, ..., Justin Hong, ..., and Nir Yosef.
Nature Methods (2023). [URL].

Deep generative modeling for quantifying sample-level heterogeneity in single-cell omics
Pierre Boyeau*, Justin Hong*, Adam Gayoso, Michael Jordan, Elham Azizi, and Nir Yosef.
Machine Learning in Computational Biology (MLCB), Oral Presentation (2022). [URL].

A Python library for probabilistic analysis of single-cell omics
Adam Gayoso*, Romain Lopez*, Galen Xing*, ..., Justin Hong, ..., and Nir Yosef.
Nature Biotechnology (2022). [URL].

Likelihood-based deconvolution of bulk gene expression data using single-cell references
Dan D. Erdmann-Pham*, Jonathan Fischer*, Justin Hong, and Yun S. Song.
Genome Research (2021). [URL].

A Likelihood-based Deconvolution of Bulk Gene Expression Data Using Single-cell References
Justin Hong, Dan D. Erdmann-Pham, Jonathan Fischer, and Yun S. Song.
Master’s Thesis. University of California, Berkeley, 2021. [URL].

Robust Federated Learning in a Heterogeneous Environment
Avishek Ghosh*, Justin Hong*, Dong Yin, and Kannan Ramchandran.
ICML Workshop on Privacy and Security in ML (2019)[URL].