Research

List of publications and preprints

(*Equal contribution)

Yao D.*, Huang S.*, Cadei R., Zhang K., Locatello F. (2025). “The Third Pillar of Causal Analysis? A Measurement Perspective on Causal Representations”. arXiv preprint arXiv:2505.17708. doi. (Accepted at NeurIPS2025).

Huang S., Pfister N., Bowden J. (2025). “Sparse Causal Effect Estimation using Two-Sample Summary Statistics in the Presence of Unmeasured Confounding”. In Proceedings of The 28th International Conference on Artificial Intelligence and Statistics (AISTATS), 3394–3402. PMLR. link. arxiv.

Huang S., Peters J., Pfister N. (2024). “Causal Change Point Detection and Localization”. arXiv preprint arXiv:2403.12677. doi.

Huang S., Ailer E., Kilbertus N., Pfister N. (2023). “Supervised learning and model analysis with compositional data”. PLOS Computational Biology. doi.

Huang S., Wolkowicz H. (2018). “Low-rank matrix completion using nuclear norm minimization and facial reduction”. Journal of Global Optimization. doi.

El Khatib A., Huang S., Ghodsi A., Karray F. (2018). “Nonnegative matrix factorization using autoencoders and exponentiated gradient descent”. In 2018 International Joint Conference on Neural Networks (IJCNN), 1–8. IEEE. doi.

Presentations

Huang S. (2022). “Supervised Learning and Model Analysis with Compositional Data”. ICSDS 2022, Florence, Italy (slides). Recipient of Student Travel Award.

Huang S. (2023). “Causal change point detection and localization”. EMS 2023, Warsaw, Poland (slides).

Reviews

I have reviewed at:

• The Journal of Machine Learning Research (JMLR)
• Transactions on Machine Learning Research (TMLR)
• NeurIPS 2025 Workshops (UniReps and CauScien)
• AISTATS 2023

Theses

Huang S. (2018). “Empirical Likelihood Quantile Regression for Right‐Censored Data”. Master’s thesis. Advisor: Martin Lysy. Link.

Huang S. (2024). “Causal Inference for Complex Data Structures”. PhD thesis. Advisors: Niklas Pfister and Jonas Peters. Link.