Assistant Professor of Computer Science
- 2017, Doctoral Degree, Computer Science, University of Illinois at Urbana-Champaign
- 2015, Master's Degree, Computer Science, University of Illinois at Urbana-Champaign
Xiang Ren is an assistant professor of Computer Science at the University of Southern California (USC) with affiliated appointment at USC Information Sciences Institute (ISI). He is also the director of Intelligence and Knowledge Discovery (INK) Research Lab, the Information Director of ACM Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD), and member of USC Machine Learning Center, CAIS Center for AI in Society, and ISI Center on Knowledge Graphs. Priorly, he was a research scholar at Stanford University, and received his Ph.D. in Computer Science from University of Illinois Urbana-Champaign. Prof. Ren's research leads to a book entitled "Mining Structures of Factual Knowledge from Text: An Effort-Light Approach" and over 50 research publications in top conferences and journals, was covered in over 10 conference tutorials (KDD, WWW, NAACL). Technologies he developed has been transferred to US Army Research Lab, National Institute of Health, Microsoft, Yelp and TripAdvisor.
Xiang Ren's research interests span machine learning and natural language processing, with a focus on developing label-efficient, prior-informed models that extract machine-actionable knowledge (e.g., compositional, graph-structured representations) from natural-language text data, as well as performing neural reasoning over symbolic knowledge. I'm particularly excited about problems in the space of modeling sequential/graph-structured data with weak supervision and prior knowledge. This includes neural-symbolic learning, learning with noisy data, zero/few-shot learning, and transfer learning.
- 2019 Amazon Faculty Research Award
- 2019 JP Morgan AI Research Award
- 2019 Google Faculty Research Award
- 2019 Adobe Data Science Research Award
- 2019 Forbes' Asia 30 Under 30
- 2018 SIGKDD Doctoral Dissertation Award
- 2017 Google PhD Fellowship