I am currently an applied scientist 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’s degree from Nanjing University.

My primary areas of focus include LLMs, multimodal foundation models, information retrieval, graph machine learning, etc. I have served as the area chair for ACL Rolling Review 2024, organizer for ROEGEN of RecSys2024, and reviewer for leading AI/ML conferences/journals. At Amazon, I have contributed to products & projects such as Amazon Titan, AWS Glue, AutoGluon, D2L, and OpenSearch, and led the project AutoGluon-RAG. My research has garnered attention from the media, including coverage by outlets like Australian Fintech.

You can find more about me on my CV.

Selected Honors and Awards

• Area Chair’s Award, ACL 2024
• Best of the Best conference Paper Award, Global Marketing Conference (GMC) 2023
• Outstanding Paper Award, ICLR 2021
• Best Paper Award runner-up, WSDM 2020
• World’s Top 2% Most Cited Scientist, 2021, 2022, 2023

Latest News

• PipeRAG accepted at KDD 2025.
• One paper accepted by NeurIPS 2024.