I’m a Ph.D. student in the OPTML Group at Michigan State University, guided by Prof. Sijia Liu. Before that, I obtained my M.S. in Computer Science from Tongji University, where I was advised by Prof. Kai Yang, and my B.S. from Hohai University.

During my master’s studies, my research focused on the intersection of sequential data analysis and optimization. In particular, I worked on developing change point detection algorithms with theoretical guarantees for engineering problems arising from real-world applications. Currently, I am conducting research in the area of machine unlearning. You can find my CV here: Curriculum Vitae.

Publications

• Huang, Y., Yang, K., Zhu, Z., & Chen, L. Triadic-OCD: Asynchronous Online Change Detection with Provable Robustness, Optimality, and Convergence. In Forty-first International Conference on Machine Learning.
• Huang, Y., Yang, K., Qiu, C., Zhang, J., & Wang, X. Uncertainty-Aware Quickest Change Detection. IJCAI Workshop on AI4TS. [Best Paper Honors Mention].