About Me

I obtained my PhD degree in Machine Learning from Machine Learning Center (ML@GT) and School of Mathematics, Georgia Institute of Technology, Atlanta, GA. I am fortunate to be advised by Prof. Mark Davenport and Prof. Negar Kiyavash (now at EPFL). I also work closely with Prof. Kun Zhang.

My research interest mainly lies in causal discovery and causal structure learning: Identifiability and algorithms. In particular:


Publications

Y. Yang, M. Nafea, N. Kiyavash, K. Zhang, and A. Ghassami. "Causal Discovery in Linear Models with Unobserved Variables and Measurement Error".
Preprint.
[arxiv]

Y. Yang, S. Salehkaleybar and N. Kiyavash. "Learning Unknown Intervention Targets in Structural Causal Models from Heterogeneous Data".
Proceedings of the 27th International Conference on Artificial Intelligence and Statistics (AISTATS 2024) .
[proceedings] [arxiv] [poster] [code]
[short version at NeurIPS 2023 CRL Workshop]

Y. Yang, A. Ghassami, M. Nafea, N. Kiyavash, K. Zhang, and I. Shpitser. "Causal Discovery in Linear Latent Variable Models Subject to Measurement Error".
Advances in Neural Information Processing Systems 35 (NeurIPS 2022) .
[proceedings] [arxiv] [poster] [code]

Y. Yang, M. Nafea, A. Ghassami, and N. Kiyavash. “Causal Discovery in Linear Structural Causal Models with Deterministic Relations”.
Proceedings of the first Conference on Causal Learning and Reasoning (CLeaR 2022) .
[proceedings] [arxiv] [poster] [code]


Experiences

Work Experiences

Applied scientist intern, Amazon.
Fall 2023.
Research scientist intern, Siemens Technnology.
Summer 2022, Summer 2023.

Teaching Experiences

ECE 6254: Statistical Machine Learning
TA, Spring 2024.
MATH 1552: Integral Calculus
TA, Fall 2018, Spring 2019, Fall 2021.
MATH 1553: Intro to Linear Algebra
TA, Summer 2021.

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