Publications & Preprints

Authors are listed alphabetically, unless otherwise indicated.

Manuscripts Under Review and Revision

1. GPT Choi, K Dao Duc, S Faigenbaum-Golovin, K Habermann, E Hartman, C von Tycowicz, C Zhang, W Zhao, and F Zhou.
   Learning the Geometry of Data: A Mathematical Review of Shape Space Analysis (preprint) In revision

2. W Zhao.
   Learning Stochastic Agent Dynamics from Pooled Population Snapshots (preprint) In revision

3. W Zhao, E Fertig, and G Stein-O'Brien.
   Inferring Cyclic Dynamics from Unordered Single-Cell Snapshots via Invariant Measures In revision

4. W Zhao, A Plaza-Rodriguez, P Luanpaisanon, EX Wang, L Gyllingberg, R Singh, E Fertig, and G Stein-O'Brien.
   Inferring the Regulation Dynamics of Oscillatory Networks from scRNA-seq Data (preprint) (GitHub) In revision

5. W Zhao and Y Ma.
   Cell-type–anchored Latent Modeling Reconstructs Spatiotemporal Tissue Dynamics In review

Published and Accepted

1. AD Lipnick, EG Tabak, G Trigila, Y Wang, X Ye, and W Zhao.
   The Monge Optimal Transport Barycenter Problem (preprint) International Statistical Review (2026), accepted

2. EG Tabak, G Trigila, and W Zhao.
   The Hierarchical Barycenter: Conditional Probability Simulation with Structured and Unobserved Covariates (preprint) Machine Learning (2026), accepted

3. W Zhao, DJ Sutherland, and K Dao Duc.
   Fast and Interpretable Quantification of Biological Shape Heterogeneity via Stratified Wasserstein Kernel (preprint) (GitHub) (publication) PLOS Computational Biology (2026)

4. S Magana, W Zhao, and K Dao Duc.
   Learning Continuous Morphological Trajectories via Latent Principal Curves (preprint) (OpenReview) Learning Meaningful Representations of Life (LMRL) Workshop at ICLR (2026)

5. W Zhao, E Fertig, and G Stein-O'Brien.
   CycleGRN: Inferring Gene Regulatory Networks from Cyclic Flow Dynamics in Single-Cell RNA-seq (preprint) (GitHub) RECOMB (2026). Invited submission to Cell Systems (fewer than 5% selected)

6. S Yu, A Kushner, E Teasell, W Zhao, S Srebnik, and K Dao Duc.
   Advanced Coarse-grained Model for Fast Simulation of Nascent Polypeptide Chain Dynamics within the Ribosome (preprint) (publication) (GitHub) Biophysical Journal (2026)

7. W Zhao, E Larschan, B Sandstede, and R Singh.
   Optimal Transport Reveals Dynamic Gene Regulatory Networks via Gene Velocity Estimation (preprint) (publication) (GitHub) PLOS Computational Biology (2025)

8. W Zhao, S Maffa, and B Sandstede.
   Data-driven Continuation of Patterns and their Bifurcations (poster) (preprint) (publication) (GitHub) SIAM Journal on Applied Dynamical Systems (2025)

9. W Zhao and EG Tabak.
   Adaptive Kernel Conditional Density Estimation (preprint) (publication) (GitHub) Information and Inference: A Journal of the IMA (2025)

10. EG Tabak, G Trigila, and W Zhao.
    The Conditional Barycenter Problem, its Data-Driven Formulation and its Solution through Normalizing Flows (preprint) (publication) Communications in Mathematical Sciences (2024)

11. H Zhang and W Zhao.
    A Memory-Efficient Neural Ordinary Differential Equation Framework Based on High-Level Adjoint Differentiation (preprint) (publication) (GitHub) IEEE Transactions on Artificial Intelligence (2022)

12. EG Tabak, G Trigila, and W Zhao.
    Distributional Barycenter Problem through Data-Driven Flows (preprint) (publication) Pattern Recognition (2022)

13. EG Tabak, G Trigila, and W Zhao.
    Data Driven Conditional Optimal Transport (preprint) (publication) Machine Learning (2021)

14. EG Tabak, G Trigila, and W Zhao.
    Conditional Density Estimation and Simulation through Optimal Transport (preprint) (publication) Machine Learning (2020)

Working Papers

1. S Chang, W Zhao, Y Ma, B Sandstede, and R Singh.
   Cell Type-Specific Gene Regulatory Network Inference from Single Cell Transcriptomics with ctOTVelo (preprint) Poster at RECOMB 2026