I'm an Sr. Applied Science Manager in Search and Information Retrieval, currently working on improving ranking systems using large language models and deep learning.
My work focuses on developing more robust and effective ranking models for large-scale search applications. I'm particularly interested in improving the reliability of language model-based rankers under distribution shifts and developing techniques that can work well with limited labeled data. Some of my recent research has explored bi-encoder architectures, behavioral representations for dense retrieval, and methods to handle conditional distribution shifts in ranking systems.
I have experience working on both academic research and industrial applications, with publications at top conferences like WWW, CIKM and SIGIR. My research aims to bridge theoretical advances in machine learning with practical challenges in building large-scale search systems.
Nan Jiang, Chen Luo, V. Lakshman, Yesh Dattatreya, Yexiang Xue
The Web Conference 2022