User:Kwchang

Kai-Wei Chang is an assistant professor in the Department of Computer Science at the University of California Los Angeles. His research interests include designing robust machine learning methods for large and complex data and building fair and accountable language processing technologies for social good applications. Kai-Wei has published broadly in natural language processing, machine learning, and artificial intelligence. His research has been widely cited and covered by news media such as Wires, NPR, and MIT Tech Review. He has been involved in developing several machine learning libraries, including LIBLINEAR (the backend of LinearSVC in Skikit Learn) and structured models in Vowpal Wabbit. His awards include the EMNLP Best Long Paper Award (2017), the KDD Best Paper Award (2010), the Rep4NLP Best Paper Award (2016), the Yahoo! Key Scientific Challenges Award (2011), and the Okawa Research Grant Award (2018). His research is supported by several DARPA and NSF grants, as well as by industrial partners. Kai-Wei obtained his Ph.D. from the University of Illinois at Urbana-Champaign in 2015 and was a post-doctoral researcher at Microsoft Research in 2016. He served as a meta-reviewer or area chair in NAACL, ACL, EMNLP, ICML, AAAI, and IJCAI. Additional information is available at http://kwchang.net.