We  are  exploring  the  unknown  but  wonderful  world!


I work as an AI Research Scientist at Skywork AI under the direction of Shuicheng Yan. I am pursuing my Ph.D. degree in Computer Science at the National University of Singapore under the supervision of Jiashi Feng and Bryan Hooi. I received my master's degree from South China University of Technology,  where I collaborated closely with Mingkui Tan and Peilin Zhao. 

My research lies in generalizable machine learning against shifting data distributions, and advancing the reuse of foundation models (e.g., generative models, multi-modality models) in real-world applications.  My dedication has led to publications in NeurIPS, ICML, ICLR, CVPR, KDD, IEEE TPAMI, IEEE TIP, etc. In recognition of my achievements, I have been honored with Google PhD Fellow, DAAD AInet Fellow, and NUS Dean's Graduate Research Excellence Award.

Email: yifan.zhang@u.nus.edu


Selected Publications (Google Scholar)

Expanding Small-Scale Datasets with Guided Imagination

Yifan Zhang, Daquan Zhou, Bryan Hooi, Kai Wang, Jiashi Feng

Neural Information Processing Systems (NeurIPS), 2023

[PDF] / [Code] / [Slides] / [Poster] / [机器之心

Deep Long-Tailed Learning: A Survey

Yifan Zhang, Bingyi Kang, Bryan Hooi, Shuicheng Yan, Jiashi Feng

IEEE Transaction on Pattern Analysis and Machine Intelligence (TPAMI), 2023

[PDF] / [Code] / [Slides] / [机器之心]  / [新智元

Disentangling Writer and Character Styles for Handwriting Generation  

Gang Dai*, Yifan Zhang*, Qingfeng Wang, Qing Du, Zhuliang Yu, Zhuoman Liu, Shuangping Huang 

Computer Vision and Pattern Recognition (CVPR), 2023

[PDF] / [Code] / [Poster] / [机器之心

Towards Stable Test-Time Adaptation in Dynamic Wild World

Shuaicheng Niu*, Jiaxiang Wu*, Yifan Zhang*, Zhiquan Wen, Yaofo Chen, Peilin Zhao, Mingkui Tan

International Conference on Learning Representations (ICLR), 2023

[PDF] / [Code] / [Slides] / [Poster] / [机器之心

Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition

Yifan Zhang, Bryan Hooi, Lanqing Hong, Jiashi Feng

Neural Information Processing Systems (NeurIPS), 2022

[PDF] / [Code] / [Slides] / [Poster] / [机器之心

Efficient Test-Time Model Adaptation without Forgetting

Shuaicheng Niu*, Jiaxiang Wu*, Yifan Zhang*, Yaofo Chen, Shijian Zheng, Peilin Zhao, Mingkui Tan 

International Conference on Machine Learning (ICML), 2022

[PDF] / [Code] / [Poster

Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regularized Fine-Tuning

Yifan Zhang, Bryan Hooi, Dapeng Hu, Jian Liang, Jiashi Feng

Neural Information Processing Systems (NeurIPS), 2021

[PDF] / [Code] / [Slides] / [Poster]

Source-Free Domain Adaptation via Avatar Prototype Generation and Adaptation 

Zhen Qiu*, Yifan Zhang*, Hongbin Lin, Shuaicheng Niu, Yanxia Liu, Qing Du, Mingkui Tan 

International Joint Conference on Artificial Intelligence (IJCAI), 2021

[PDF] / [Code] / [Slides] / [Poster]

Collaborative Unsupervised Domain Adaptation for Medical Image Diagnosis

Yifan Zhang, Ying Wei, Peilin Zhao, Shuaicheng Niu, Qingyao Wu, Mingkui Tan, Junzhou Huang

IEEE Transaction on Image Processing (TIP), 2020

NeurIPS workshop, 2019

[TIP] / [NeurIPS workshop] / [Code]

From Whole Slide Imaging to Microscopy: Deep Microscopy Adaptation Network for Histopathology Cancer Image Classification

Yifan Zhang, Hanbo Chen, Ying Wei, Peilin Zhao, Jiezhang Cao, Qingyao Wu, Mingkui Tan, Junzhou Huang, etc

International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2019

[PDF] / [Slides] / [Poster]

Online Adaptive Asymmetric Active Learning  for Budgeted Imbalanced Data

Yifan Zhang, Peilin Zhao, Jiezhang Cao, Wenye Ma, Junzhou Huang,  Qingyao Wu,  Mingkui Tan

ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD), 2018

IEEE Transaction on Knowledge and Data Engineering (TKDE), 2019

[KDD] / [TKDE] / [Code] / [Slides] / [Poster]

Professional Services

Awards and Scholarships

Thanks  for  your  attention !