Brief Biography

I am currently employed at Amazon Web Services AI, focusing on foundation models related research, opensource projects, and products. Before this role, I was a postdoctoral researcher in the Department of Computer Science at ETH Zurich, under the guidance of Prof. Ce Zhang. I received a PhD degree from the school of computer science and engineering of UNSW Sydney, advised by Prof. Lina Yao, and my PhD study was also supported by CSIRO’s Data61 PhD Scholarship. I obtained a Bachelor degree from Nanjing University.

My primary areas of focus include LLMs, multimodal foundation models, information retrieval, graph machine learning, etc. I am a recipient of the Best Paper Award runner-up at WSDM 2020, the Outstanding Paper Award at ICLR 2021, and the Best of the Best conference Paper Award at the Global Marketing Conference (GMC) 2023. I have served as the area chair for ACL Rolling Review 2024, area chair for WiML (Women in Machine Learning) Workshop at NeurIPS 2022, senior PC for IJCAI 2021 and CIKM 2021, session chair for CIKM 2021, and guest editor for Frontiers in Big Data. At Amazon, I have contributed to projects such as Amazon Titan, AutoGluon, D2L, and OpenSearch. My research has garnered attention from the media, including coverage by outlets like Australian Fintech.

Selected Publications

CaMML: Context-Aware Multimodal Learner for Large Models
Yixin Chen*, Shuai Zhang*, Boran Han, Tong He, Bo Li.
ACL 2024. The 62nd Annual Meeting of the Association for Computational Linguistics. website

Transferring Knowledge From Large Foundation Models to Small Downstream Models
Shikai Qiu, Boran Han, Danielle C. Maddix, Shuai Zhang, Bernie Wang, Andrew Gordon Wilson.
ICML 2024. Forty-first International Conference on Machine Learning.

Bridging Sources in Geospatial Sensing with Cross Sensor Pretraining
Boran Han, Shuai Zhang, Xingjian Shi, Markus Reichstein
CVPR 2024. The IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR)

Prompt Pre-Training with Twenty-Thousand Classes for Open-Vocabulary Visual Recognition
Shuhuai Ren, Aston Zhang, Yi Zhu, Shuai Zhang, Shuai Zheng, Mu Li, Alex Smola, Xu Sun.
NeurIPS 2023 . Thirty-seventh Conference on Neural Information Processing Systems. code

Data-Informed Geometric Space Selection
Shuai Zhang, Wenqi Jiang.
NeurIPS 2023 . Thirty-seventh Conference on Neural Information Processing Systems code.

xFraud: Explainable Fraud Transaction Detection
Susie Xi Rao, Shuai Zhang, Zhichao Han, Zitao Zhang, Wei Min, Zhiyao Chen, Yinan Shan, Yang Zhao, Ce Zhang.
VLDB 2022 . The Proceedings of the VLDB Endowment. code

Neural Methods for Logical Reasoning over Knowledge Graphs
Alfonso Amayuelas, Shuai Zhang, Susie Xi Rao, Ce Zhang.
ICLR 2022 . The International Conference on Learning Representations. code

Beyond Fully-Connected Layers with Quaternions: Parameterization of Hypercomplex Multiplications with 1/n Parameters
Aston Zhang, Yi Tay, Shuai Zhang, Alvin Chan, Anh Tuan Luu, Siu Hui, Jie Fu.
ICLR 2021. The International Conference on Learning Representations. code
Outstanding Paper Award.

Self-Instantiated Recurrent Units with Dynamic Soft Recursion
Aston Zhang, Yi Tay, Yikang Shen, Alvin Chan, Shuai Zhang
NeurIPS 2021 . Thirty-fifth Conference on Neural Information Processing Systems. code

HyperML: A Boosting Metric Learning Approach in Hyperbolic Space for Recommender Systems
Lucas Vinh Tran, Yi Tay, Shuai Zhang, Gao Cong, Xiaoli Li.
WSDM 2020. The 13th ACM International Conference on Web Search and Data Mining code.
Best Paper Award Runner-up.

Quaternion Knowledge Graph Embeddings
Shuai Zhang, Yi Tay, Lina Yao, Qi Liu.
NeurIPS 2019. Thirty-third Conference on Neural Information Processing Systems code.