Biography

I’m currently a Research Fellow at Nanyang Technological University (NTU), working with Prof. Hanwang Zhang.

I obtained my Ph.D. degree in The Chinese University of Hong Kong (CUHK), supervided by Prof. Jiaya Jia and Prof. Bei Yu in 2022. Before that, I received my B.E. degree from the Computer Science Department of ShanDong University in 2018.

Research

Data-centric AI opens the door to Artificial General Intelligence (AGI). However, data biases inevitably exist in large-scale data, like data imbalance, spurious correlations among classes, and annotation noise. I’m interested in fundamental research of model generalization and robustness on different data distributions, realizing effective usage of large-scale data and that the trained models do not suffer from data biases. It usually involves problems in machine learning and computer vision, like distribution shifts, adversarial robustness, fairness, and out-of-distribution generalization.

Additionally, I aim to understand the behaviors of large models, such as Stable Diffusion models, LLMs, and VLMs, and their applications in downstream tasks.

I am excited to explore new machine learning problems, including AI for science and 3D modeling challenges.

Publications [Google Scholar]

* represents equal contributions

Experiences

  • SmartMore, ShenZhen, China.
    Research Intern
    Mentor: Shu Liu
    Time: 2020.03 - 2021.12

  • YouTu X-Lab, Tencent, ShenZhen, China.
    Research Intern
    Mentor: Xiaoyong Shen
    Time: 2018.09 - 2020.02

  • Reviewer for Journals
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI).
    International Journal of Computer Vision (IJCV).
    IEEE Transactions on Image Processing (TIP).
    IEEE Transactions on Neural Networks and Learning Systems (TNNLS).

  • Reviewer for Conferences
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
    IEEE International Conference on Computer Vision (ICCV).
    European Conference on Computer Vision (ECCV).
    International Conference on Learning Representations (ICLR).
    Neural Information Processing Systems (NeurIPS).
    International Conference on Machine Learning(ICML).