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Xiaofeng Yang is a PhD student in the Database Systems and Data Mining programs at Northeastern University’s College of Computer and Information Science, advised by Professor Mirek Riedewald. She is currently working on graph sampling on social networks and its application on distributed database systems. In 2013, Xiaofeng received her bachelor’s degree in mathematics and engineering from Tsinghua University in China.
- BEng, Tsinghua University – China
- BS in Mathematics, Tsinghua University – China
- Hometown: Jilin, China
- Field of Study: Database Systems and Data Mining
- PhD Advisor: Mirek Riedewald
What are your research interests?
I work on efficient and interactive algorithms to support top-k searches on large scale social networks. Such networks are information-rich, containing graph structure (how users are connected), attributes and tags. My thesis topic is about using these information to provide faster and precise answer to data mining questions, and prove a low cost of prioritizing the most relevant answers.
What aspect of what you do is most interesting?
I find it fascinating that based on simple assumptions, I can prove bounds showing that searching interactively can be done cost-efficiently. This can potentially change how pattern-search applications are currently implemented in large networks.
What are your research or career goals, going forward?
I will further study techniques to improve graph search performance in the future. It will be exciting to look at the problem from both the theoretical aspect and the system aspect. In addition to developing algorithms and testing them in experimental settings, I would also want to push the algorithms into real-world products, see how well they deal with unexpected and practical challenges, and solve new problems from there.