Yaoyao Liu

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Education

• PhD, Computer Science, Max Planck Institute for Informatics
• BS, Electronic Information Engineering, Tianjin University

Biography

Yaoyao Liu is an assistant professor in the School of Information Sciences at the University of Illinois Urbana-Champaign. He is also affiliated with the Siebel School of Computing and Data Science. Previously, he completed his PhD in computer science at Max Planck Institute for Informatics and his BS in electronic information engineering at Tianjin University. He also spent time at Johns Hopkins, Oxford VGG, and National University of Singapore. His research lies at the intersection of computer vision and machine learning—with a special focus on building intelligent visual systems that are continual and data-efficient. His research interests include continual learning, few-shot learning, semi-supervised learning, generative models, 3D geometry models, and medical imaging.

Academic Positions

• Assistant Professor, School of Information Sciences
• Affiliate Assistant Professor, Siebel School of Computing and Data Science

Other Professional Activities

• Area Chair: CVPR 2024-2025, ECCV 2024, NeurIPS 2024, ICML 2025, ICLR 2024-2025, AISTATS 2023-2025, UAI 2023-2025, ACM MM 2024, BMVC 2024-2025.
• Senior Program Committee: AAAI 2025, IJCAI 2021.

Graduate Research Opportunities

I am actively looking for self-motivated Ph.D. students with interests in computer vision and machine learning. If you are interested, please send me an email. You may see details here.

Research Interests

• Computer Vision
• Machine Learning
• Medical Image Analysis

Articles in Conference Proceedings

• Wufei Ma, Guofeng Zhang, Qihao Liu, Guanning Zeng, Adam Kortylewski, Yaoyao Liu, Alan Yuille. "ImageNet3D: Towards General-Purpose Object-Level 3D Understanding," Neural Information Processing Systems (NeurIPS), 2024 (Datasets and Benchmarks Track).
• Yuanhao Cai, Zihao Xiao, Yixun Liang, Minghan Qin, Yulun Zhang, Xiaokang Yang, Yaoyao Liu, Alan Yuille. "HDR-GS: Efficient High Dynamic Range Novel View Synthesis at 1000x Speed via Gaussian Splatting," Neural Information Processing Systems (NeurIPS), 2024.
• Tom Fischer, Yaoyao Liu, Artur Jesslen, Noor Ahmed, Prakhar Kaushik, Angtian Wang, Alan Yuille, Adam Kortylewski, Eddy Ilg. "iNeMo: Incremental Neural Mesh Models for Robust Class-Incremental Learning," European Conference on Computer Vision (ECCV), 2024.
• Wufei Ma*, Qihao Liu*, Jiahao Wang*, Angtian Wang, Xiaoding Yuan, Yi Zhang, Zihao Xiao, Guofeng Zhang, Beijia Lu, Ruxiao Duan, Yongrui Qi, Adam Kortylewski, Yaoyao Liu, Alan Yuille. "Generating Images with 3D Annotations Using Diffusion Models," International Conference on Learning Representations (ICLR), 2024 (Spotlight).
• Yaoyao Liu, Yingying Li, Bernt Schiele, Qianru Sun. "Wakening Past Concepts without Past Data: Class-Incremental Learning from Online Placebos," IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2024.
• Yixiao Zhang, Xinyi Li, Huimiao Chen, Alan Yuille, Yaoyao Liu, Zongwei Zhou. "Continual Learning for Abdominal Multi-Organ and Tumor Segmentation," International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2023.
• Yaoyao Liu, Bernt Schiele, Andrea Vedaldi, Christian Rupprecht. "Continual Detection Transformer for Incremental Object Detection," IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
• Zilin Luo, Yaoyao Liu, Bernt Schiele, Qianru Sun. "Class-Incremental Exemplar Compression for Class-Incremental Learning," IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
• Yaoyao Liu, Yingying Li, Bernt Schiele, Qianru Sun. "Online Hyperparameter Optimization for Class-Incremental Learning," AAAI Conference on Artificial Intelligence (AAAI), 2023 (Oral Presentation).
• Yaoyao Liu, Bernt Schiele, Qianru Sun. "RMM: Reinforced Memory Management for Class-Incremental Learning," Neural Information Processing Systems (NeurIPS), 2021.
• Yaoyao Liu, Bernt Schiele, Qianru Sun. "Adaptive Aggregation Networks for Class-Incremental Learning," IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
• Yaoyao Liu, Bernt Schiele, Qianru Sun. "An Ensemble of Epoch-wise Empirical Bayes for Few-shot Learning," European Conference on Computer Vision (ECCV), 2020.
• Yaoyao Liu, Yuting Su, An-An Liu, Bernt Schiele, Qianru Sun. "Mnemonics Training: Multi-Class Incremental Learning without Forgetting," IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020 (Oral Presentation).
• Xinzhe Li, Qianru Sun, Yaoyao Liu, Shibao Zheng, Qin Zhou, Tat-Seng Chua, Bernt Schiele. "Learning to Self-Train for Semi-Supervised Few-Shot Classification," Neural Information Processing Systems (NeurIPS), 2019.
• Qianru Sun*, Yaoyao Liu*, Tat-Seng Chua, Bernt Schiele. "Meta-Transfer Learning for Few-Shot Learning," IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019.