Bio

Fei worked as a Senior Research Scientist at Bosch Research, Palo Alto, California, one of the largest German companies providing intelligent car systems and home appliances. Fei received her Ph.D. in Computer Science from the University of Texas at Dallas in 2011, supported by Erik Jonsson Distinguished Research Fellowship.

Prior to that, she obtained her Bachelors and Masters degrees in Computer Science from Fudan University, Shanghai, China. Feihas published over twenty peer reviewed articles, and she serves as a referee for leading journals and conferences.

Natural Language Processing, Machine Learning, Social Media, Summarization

Summarizing Information in Big Data: Algorithms and Applications

Information floods the lives of modern people, and we find it overwhelming. Summarization systems that identify salient pieces of information and present it concisely can help. I will discuss both algorithmic and application perspectives of summarization. Algorithm-wise, I will describe keyword extraction, sentence extraction, and summary generation, including a range of techniques from information extraction to semantic representation of data sources; application-wise, I focus on summarizing human conversations, social media contents, and news articles.

The data sources span low-quality speech recognizer outputs and social media chats to high-quality content produced by professional writers. A special focus of my work is exploring multiple information sources. In addition to better integration across sources, this allows abstraction to shared research challenges for broader impact. Finally, I try to identify the missing links in cross-genre summarization studies and discuss future research directions.