I’m a CS PhD student (3rd year) at Universtiy of Waterloo, supervised by Professor Jimmy Lin. Before that, I received my MSc in Computer Science from University of Toronto under the supervision of Danijar Hafner and Professor Jimmy Ba. I completed my undergraduate study at Sun Yat-Sen University advised by Professor Weishi Zheng.

I am interested in building efficient, scalable, and robust neural models for information retrieval and its downstream applications. My research goal is to design task-aware retrievers to help large language models efficiently aggregate knowledge from large, unstructured databases.

News

• 2023-10-09: New paper alert! Our paper How to Train Your DRAGON: Diverse Augmentation Towards Generalizable Dense Retrieval has been accepted to EMNLP 2023! Check out this super robust and easy-to-use dense retriever here and try it out yourself!
• 2023-09-18: I start my internship at Meta FAIR Lab as a Research Scientist intern hosted by Victoria Lin.
• 2023-08-22: I’m awarded with the Waterloo Apple PhD Fellowship in Data Science and Machine Learning.
• 2023-06-22: I start my internship at Google Research as a Student Researcher under the supervision of Honglei Zhuang
• 2023-05-02: Our paper CITADEL is accepted in ACL 2023! Check out this efficient multi-vector retriever which i about 40x faster than ColBERT-v2 on GPUs.
• 2022-02-13: New paper is out! SLIM manages to reduce the latency and storage of ColBERT while being fully compatible with Pyserini (Lucene-based). Codes will be released soon!
• 2022-02-13: New paper is out! We find that adding contextualized late interaction could be helpful for cross-encoders on out-of-domain generalization. Check out the paper and some discussion on twitter.