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.

Huang S., Pfister N., Bowden J. (2024). “Sparse Causal Effect Estimation using Two-Sample Summary Statistics in the Presence of Unmeasured Confounding”. arXiv preprint arXiv:2410.12300. doi. (Accepted at AISTATS 2025).

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”. 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)
• AISTATS 2023