Singaporean computer scientist
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 a Research Scientist at Facebook AI ,[ 1] and was previously the Director of Research at Megagon Labs in Mountain View, California .[ 2]
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.[ 3]
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 .[ 2]
Her 2002 dissertation, Data Annotations, Provenance, and Archiving , was jointly supervised by Peter Buneman and Sanjeev Khanna .[ 4] [ 5]
Before working at Megagon, she has been a professor of computer science at the University of California, Santa Cruz beginning in 2002,[ 6] and, from 2010 to 2012, was on leave from Santa Cruz as a researcher at IBM Research - Almaden .[ 2]
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".[ 7]
References
^ "Wang-Chiew Tan's Homepage" . wangchiew.github.io .
^ a b c Wang-Chiew Tan, Director of Research , Megagon Labs, retrieved 2018-10-16
^ Foley, Katherine Ellen (March 3, 2018), "Pets don't make humans immediately happy the way other people do" , Quartz
^ "Data annotations, provenance, and archiving" , ACM Digital Library , Association for Computing Machinery , retrieved 2018-10-16
^ Wang-Chiew Tan at the Mathematics Genealogy Project
^ "New Faculty" , UC Santa Cruz Currents , January 20, 2003
^ "Wang-Chiew Tan Wang-Chiew" , ACM Fellows , Association for Computing Machinery , retrieved 2018-10-16
External links