xiangren [at] usc.edu
Andrew and Erna Viterbi Early Career Chair
Assistant Professor, USC Computer Science
Visiting Research Scientist, AI2
Research Team Leader, USC ISI
Director, USC INK Research Lab
Information Director, SIGKDD
Forbes' Asia 30 Under 30
I'm an Assistant Professor in Computer Science and the Andrew and Erna Viterbi Early Career Chair at USC, where I'm the PI of the Intelligence and Knowledge Discovery (INK) Research Lab. I also hold appointment as a Research Team Leader in Information Sciences Institute (ISI) and serve as a member of the USC NLP Group, USC Machine Learning Center and ISI Center on Knowledge Graphs. Outside of my USC work, I spend time at Allen Institute for AI (AI2) working on machine common sense. Previously I was a Data Science Advisor at Snapchat. Prior to USC, I did my PhD work in computer science at UIUC. I've also spent time with the NLP group and the SNAP group at the Stanford University.
My research seeks to build generalizable natural language processing (NLP) systems that can handle a wide variety of language tasks and situations, to broaden the scope of model generality. I work on new algorithms and datasets to make NLP models cheaper to build and maintain, arm AI models with common sense, and improve model's transparency and reliability to build user trust. My group (INK Lab) recently focuses on: (1) creating evaluation methods and datasets that expose the state-of-the-art NLP systems in various human reasoning scenarios; (2) building novel learning algorithms and model architectures to augment NLP systems with commonsense and factual knowledge; (3) developing graph neural network methods for relational reasoning; and (4) verifying and enhancing the robustness of NLP models. We're also interested in extract machine-actionable knowledge from natural language data, perform neural-symbolic knowledge reasoning for intelligent applications, and learning (to adapt and improve) from human explanations and instructions. Please check out the our group website for more information.
Our research work is funded by NSF (CAREER award, SciSIP #1829268), DARPA (MCS, KMASS, INCAS, SCORE, GAILA, SAIL-ON), IARPA (HIATUS, BETTER), and gifts from industry partners including Google, Amazon, Meta, JP Morgan, Adobe, Sony, and Snapchat. A summary of my PhD work on label-efficient NLP can be found in the book "Mining Structures of Factual Knowledge from Text: An Effort-Light Approach".