He research group presents at KDD2020

Jingrui He
Jingrui He, Associate Professor

Members of Associate Professor Jingrui He's research group, the iSAIL Lab, will present their research at the 26th SIGKDD Conference on Knowledge Discovery and Data Mining (KDD2020), which will be held virtually August 22-27. The conference, hosted by the Association for Computing Machinery's Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD), is the premier international forum for data mining researchers and practitioners from academia, industry, and government to share ideas, research, and experiences. The group will present the following papers:

  • Dawei Zhou, PhD student in computer science, will present "A Data Driven Graph Generative Model for Temporal Interaction Networks," co-authored with He; Lecheng Zheng, PhD student in computer science; and Jiawei Han, Michael Aiken Chair in the Department of Computer Science.
  • Jian Kang, PhD student in computer science, will present "InFoRM: Individual Fairness on Graph Mining," co-authored with He; Hanghang Tong, associate professor of computer science; and Ross Maciejewski, associate professor at Arizona State University.
  • Yikun Ban, PhD student in computer science, will present "Generic Outlier Detection in Multi-Armed Bandit," co-authored with He.
  • Dongqi Fu, PhD student in computer science, will present "Local Motif Clustering on Time-Evolving Graphs," co-authored with Zhou and He. 

He's general research theme is to design, build, and test a suite of automated and semi-automated methods to explore, understand, characterize, and predict real-world data by means of statistical machine learning. She received her PhD in machine learning from Carnegie Mellon University.

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