Scholar
Yu Yao
Google Scholar ID: OkcaMKAAAAAJ
Lecturer in the University of Sydney
Citations & Impact
Citations
641
H-index
11
i10-index
11
Publications
20
Co-authors
7
list available
Contact
Publications
Resume (English only)
Academic Achievements
- - Awarded Outstanding Area Chair for ICML'25
- - Awarded Outstanding Reviewer for UAI'25
- - Three papers accepted to ICML'25
- - Serving as an Area Chair for NeurIPS'25
- - Honored to serve as an Oral Session Chair for ICLR'25
- - Four papers accepted to ICLR'25
- - Serving as an Area Chair for ICML'25
- - Two papers accepted to NeurIPS'24
- - Serving as an Area Chair for ICLR'25
- - Serving as an Action Editor for TMLR
- - Joined the University of Sydney as a Lecturer in 2023
- - Two papers accepted to NeurIPS'23
- - Awarded Outstanding Reviewer for NeurIPS'23
- - One paper accepted to ICML'23
- - Awarded Outstanding Reviewer for ICLR'23
Research Experience
- - Worked as a postdoctoral fellow at Mohamed bin Zayed University of Artificial Intelligence and Carnegie Mellon University, collaborating with Prof. Tongliang Liu and Prof. Kun Zhang.
Education
- Completed doctoral studies at The University of Sydney, supervised by Prof. Tongliang Liu and Prof. Dacheng Tao.
Background
- Research interests include the reliability and alignment with human understanding of machine learning systems. Specific directions include:
- - Robustness: How can we build ML systems that are robust to different types of noise in different data modalities? How can we improve ML systems' adaptability to changing environments? How can we design evaluation methods for existing ML systems in real-world settings?
- - Interpretable Representation: How can we explain the representation learned by different ML methods? What would be the necessary assumptions for developing disentangled representations under different cases? How can we use multimodal data together to encourage disentanglement? What empirical methods are needed to effectively achieve such disentanglement?
Miscellany
- Supervised students include:
- - Boye Niu (Honors Student in Statistics, 2024-Present)
- - Kai Lian (Master Student in Computer Science, 2024-Present)
- - Ruojing Dong (Ph.D. Candidate in Computer Science, co-advised with Prof. Tongliang Liu, 2024-Present)
- - Jiyang Zheng (Ph.D. Candidate in Computer Science, co-advised with Prof. Tongliang Liu, 2023-Present)
- - Yexiong Lin (Ph.D. Candidate in Computer Science, co-advised with Prof. Tongliang Liu, 2023-Present)
