Wang-Chiew Tan

Wang-Chiew Tan is a Singaporean computer scientist specializing in data management and natural language processing. Her work in data management includes data provenance (or data lineage) and data integration. She is currently the Director of Research at Megagon Labs in Mountain View, California.[1]

Wang-Chiew Tan
Alma materUniversity of Pennsylvania
Known fordata lineage and data integration
AwardsACM Fellow
Scientific career
FieldsComputer Science
InstitutionsMegagon Labs
Doctoral advisorPeter Buneman and Sanjeev Khanna
Websitewangchiew.github.io

At Megagon Labs, Tan was the lead researcher on a study with the University of Tokyo that concluded that the company of other people is more effective than pets at making people happy.[2]

Education and career

Tan earned her bachelor's degree in computer science (first-class) at the National University of Singapore, and completed her Ph.D. at the University of Pennsylvania.[1] Her 2002 dissertation, Data Annotations, Provenance, and Archiving, was jointly supervised by Peter Buneman and Sanjeev Khanna.[3][4]

Before working at Megagon, she has been a professor of computer science at the University of California, Santa Cruz beginning in 2002,[5] and, from 2010 to 2012, was on leave from Santa Cruz as a researcher at IBM Research - Almaden.[1]

Recognition

Tan was named a Fellow of the Association for Computing Machinery in 2015 "for contributions to data provenance and to the foundations of information integration".[6]

References
  1. Wang-Chiew Tan, Director of Research, Megagon Labs, retrieved 2018-10-16
  2. Foley, Katherine Ellen (March 3, 2018), "Pets don't make humans immediately happy the way other people do", Quartz
  3. "Data annotations, provenance, and archiving", ACM Digital Library, Association for Computing Machinery, retrieved 2018-10-16
  4. Wang-Chiew Tan at the Mathematics Genealogy Project
  5. "New Faculty", UC Santa Cruz Currents, January 20, 2003
  6. "Wang-Chiew Tan Wang-Chiew", ACM Fellows, Association for Computing Machinery, retrieved 2018-10-16
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