Biography


I am a Presidential Postdoctoral Fellow (PPF, Principal Investigator) at Nanyang Technological University (NTU) in Singapore. In 2023, I completed his Ph.D. in NTU under Alibaba Talent Program, supervised by Prof. Hanwang Zhang. During Ph.D., I did an internship in Sea working under Dr. Pan Zhou. Prior to that, I received his bachelor's degree from NTU in 2017 under MOE SM2 scholarship.
My research is primarily about machine generalization, which aims to train models that perform well on new, unseen data that was not included in their training set. Broadly speaking, I am interested in representation learning that unveils the hidden generative mechanism behind observations in the world; and robust downstream learning that mitigates spurious correlations in the training data, e.g., by causal intervention or invariant learning. I have published papers in top AI/computer vision conferences such as NeurIPS, CVPR and ICCV on a wide range of generalization tasks, including unsupervised learning, zero-/few-shot learning, unsupervised domain adaptation, open-set recognition, etc.

News

  • [10, 2023]    I started a research internship in Sea.
  • [09, 2023]    1 paper about unsupervised domain adaptation accepted by NeurIPS 2023.
  • [08, 2023]    Awarded Wallenberg-NTU Presidential Postdoctoral Fellowship.
  • [07, 2023]    2 papers about open-world detection and fair face recognition are accepted by ICCV 2023.
  • [03, 2023]    1 paper about video anomaly detection accepted by CVPR 2023.
  • [08, 2022]    Received 2022 PREMIA Best Student Paper Awards (The Gold Award).
  • [09, 2021]    1 paper about self-supervised learning accepted by NeurIPS 2022 (Spotlight).
  • [07, 2021]    1 paper about unsupervised domain adaptation accepted by ICCV 2021 (Oral).
  • [03, 2021]    1 paper about zero-shot learning accepted by CVPR 2021.
  • [09, 2020]    1 paper about few-shot learning accepted by NeurIPS 2020.
  • [05, 2020]    Joined Alibaba Talent Program to do a Ph.D. in NTU.

Publications [Google Scholar]


Make the U in UDA Matter: Invariant Consistency Learning for Unsupervised Domain Adaptation

Zhongqi Yue, Hanwang Zhang, Qianru Sun
Conference on Neural Information Processing Systems (NeurIPS), 2023.
ICON WILDS 2.0 Leaderboard 1st Place (with unlabeled data). 🔥Project Page🔥
Invariant Feature Regularization for Fair Face Recognition

Jiali Ma, Zhongqi Yue, Tomoyuki Kagaya, Tomoki Suzuki, Karlekar Jayashree, Sugiri Pranata, Hanwang Zhang
International Conference on Computer Vision (ICCV), 2023.
🔥Project Page🔥
Random Boxes Are Open‑world Object Detectors

Yanghao Wang, Zhongqi Yue, Xian‑Sheng Hua, Hanwang Zhang
International Conference on Computer Vision (ICCV), 2023.
🔥Project Page🔥
Unbiased Multiple Instance Learning for Weakly Supervised Video Anomaly Detection

Hui Lv, Zhongqi Yue, Qianru Sun, Bin Luo, Zhen Cui, Hanwang Zhang
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
🔥Project Page🔥
Self-Supervised Learning Disentangled Group Representation as Feature

Tan Wang, Zhongqi Yue, Jianqiang Huang, Qianru Sun, Hanwang Zhang
Conference on Neural Information Processing Systems (NeurIPS), 2021.
Spotlight Presentation 260/9122; 2022 PREMIA Best Student Paper. 🔥Project Page🔥
Transporting Causal Mechanisms for Unsupervised Domain Adaptation

Zhongqi Yue, Qianru Sun, Xian‑Sheng Hua, Hanwang Zhang
International Conference on Computer Vision (ICCV), 2021.
Oral Presentation 210/6236. 🔥Project Page🔥
Counterfactual Zero‑Shot and Open‑Set Visual Recognition

Zhongqi Yue*, Tan Wang*, Qianru Sun, Xian‑Sheng Hua, Hanwang Zhan
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
🔥Project Page🔥
Interventional Few‑Shot Learning

Zhongqi Yue, Hanwang Zhang, Qianru Sun, Xian‑Sheng Hua
Conference on Neural Information Processing Systems (NeurIPS), 2020.
🔥Project Page🔥
© Zhongqi Yue | Last updated: 12/12/2023