Xin Luna Dong (born 1975)[1] is a Chinese-American computer scientist and database researcher whose research topics include knowledge graphs, knowledge fusion, and intelligent assistants. She is a principal scientist at Meta Reality Labs.

Education and career

Dong studied computer science and international finance at Nankai University in Tianjin, China, graduating with a bachelor's degree in 1998. After a master's degree in computer science in 2001 at Peking University, she came to the University of Washington for doctoral study in computer science, earning a second master's degree in 2003 and completing her Ph.D. in 2007.[2] Her dissertation, Providing Best Effort Services in Dataspace Systems, concerned databases and was supervised by Alon Halevy.[3]

She became a researcher for AT&T Research from 2007 to 2012, for Google from 2013 to 2016, and for Amazon from 2016 to 2021, before taking her present position at Meta in 2021.[2] Her work at Google and Amazon involved the Google Knowledge Graph and Amazon Product Knowledge Graph, respectively.[4]

Recognition

Dong was the 2016 recipient of the VLDB Early Career Award,[5] "for advancing the state of the art of knowledge fusion".[4] She is the 2023 recipient of the VLDB Women in Database Research Award.[6]

She was named an IEEE Fellow, in the 2024 class of fellows, "for contributions to knowledge graph construction and data integration".[7] She is also a Distinguished Member of the Association for Computing Machinery.[4]

References

  1. ↑ Birth year from Library of Congress catalog entry, retrieved 2023-12-12
  2. 1 2 Curriculum vitae (PDF), retrieved 2023-12-12
  3. ↑ Xin Luna Dong at the Mathematics Genealogy Project
  4. 1 2 3 "Industry Leaders in Signal Processing and Machine Learning: Luna Dong", Inside Signal Processing Newsletter, IEEE Signal Processing Society, December 2021, retrieved 2023-12-12
  5. ↑ VLDB Early Career Award, Very Large Data Bases Endowment Inc., retrieved 2023-12-12
  6. ↑ "Conference awards", 49th International Conference on Very Large Data Bases, retrieved 2023-12-12
  7. ↑ 2024 Fellow Class (PDF), IEEE, retrieved 2023-12-12
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