(P.C. my friend Chi Zhang)

Jian Kang

Email: jiank2 [at] illinois [dot] edu

I am currently a 4th-year PhD student in the Department of Computer Science at University of Illinois at Urbana-Champaign (UIUC) and a member of iDEA Lab leaded by Dr. Hanghang Tong. My research interests mainly lie in large-scale data mining and machine learning on graphs.

Before joining UIUC, I obtained my BEng degree in Communications Engineering at Beijing University of Posts and Telecommunications and MCS degree in Computer Science at University of Virginia. Then I spent two years at Arizona State University as a PhD student in School of Computing, Informatics, and Decision Systems Engineering.

Publications

Journal Paper:

Meijia Wang, Jian Kang, Nan Cao, Yinglong Xia, Wei Fan, Hanghang Tong. Graph Ranking Auditing: Problem Definitions and Fast Solutions. In IEEE Transactions on Knowledge and Data Engineering (TKDE), 2020. [Paper]

Conference Papers:

Jian Kang, Jingrui He, Ross Maciejewski, Hanghang Tong. InFoRM: Individual Fairness on Graph Mining. In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD), 2020. [Paper] [Slides] [Code]
Jian Kang, Hanghang Tong. N2N: Network Derivative Mining. In Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM), 2019. [Paper] [Slides] [Code]
Jian Kang*, Scott Freitas*, Haichao Yu, Yinglong Xia, Nan Cao, Hanghang Tong. X-Rank: Explainable Ranking in Complex Multi-layered Networks. In Proceedings of the 27th ACM International Conference on Information and Knowledge Management (CIKM), 2018. [Paper]
Jian Kang, Meijia Wang, Nan Cao, Yinglong Xia, Wei Fan, Hanghang Tong. AURORA: Auditing PageRank on Large Graphs. In Proceedings of 2018 IEEE International Conference on Big Data (Big Data), 2018. [Paper] [Slides] [Code]
(check out the updated results in our TKDE paper)
Haichao Yu, Jian Kang, Yonglong Xia, Nan Cao, Hanghang Tong. Visual Mining of Multi-sourced Networks. In Proceedings of the 5th China Visualization and Visual Analytics Conference (ChinaVis), 2018.

(* indicates equal contribution)

PhD (Computer Science), University of Illinois at Urbana-Champaign. 2019.8 - present
PhD (Computer Science), Arizona State University. 2017.8 - 2019.5
MCS (Computer Science), University of Virginia. 2015.8 - 2016.12
BEng (Communications Engineering), Beijing University of Posts and Telecommunications. 2010.9 - 2014.6

Teaching Assistant, CS412: Introduction to Data Mining, Hanghang Tong. University of Illinois at Urbana-Champaign, Fall 2020
Teaching Assistant, CSE575: Statistical Machine Learning, Hanghang Tong. Arizona State University, Fall 2018

Program Committee: AAAI (2021), DLG-AAAI (2021), ICLR(2021), ICML (2020, 2021), IJCAI (2021)
External Reviewer: AAAI (2019), ACMMM (2018), CIKM (2018), DASFAA (2018, 2019), DSAA (2018), ICML (2019), IJCAI (2019), KDD (2018, 2019), NeurIPS (2020), PAKDD (2019), TheWebConf (formerly WWW, 2018, 2020, 2021), WSDM (2019, 2020)
Journal Reviewer: CACM, TKDD, TKDE