Boxin Du

Boxin Du

Email: boxindu2 AT illinois DOT edu

I am currently a PhD student in the Department of Computer Science at the University of Illinois at Urbana-Champaign (UIUC), and a member of iDEA Lab led by Dr. Hanghang Tong. I received my B.Eng from Beijing Jiaotong University and MS degree from CIDSE, Arizona State University.

My main research interest is large-scale graph data mining. My research domains include multi-network mining, subgraph matching, network embedding, knowledge graph, recommender system, etc.

Publications

[Google scholar] [DBLP]
  • (New) Zhe Xu, Boxin Du, Hanghang Tong, Graph Sanitation with Application to Node Classification. Proceedings of the 31st conference in the International World Wide Web Conference. 2022. [paper link]
  • (New) Boxin Du, Changhe Yuan, Robert Barton, Tal Neiman, Hanghang Tong, Hypergraph Pre-training with Graph Neural Networks. 2021. [paper link]
  • (New) Boxin Du, Lihui Liu, Hanghang Tong, Sylvester Tensor Equation for Multi-Way Association. Proceedings of the 27th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 2021. [paper link]
  • (New) Lihui Liu, Boxin Du, Heng Ji, Chengxiang Zhai, Hanghang Tong, Neural-Answering Logical Queries on Knowledge Graphs. Proceedings of the 27th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 2021. [paper link]
  • (New) Lihui Liu, Boxin Du, Yi Fung, Heng Ji, Jiejun Xu, Hanghang Tong, KompaRe: A Knowledge Graph Comparative Reasoning System. Proceedings of the 27th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 2021. [paper link]
  • Boxin Du, Si Zhang, Yuchen Yan, Hanghang Tong, New Frontiers of Multi-Network Mining: Recent Developments and Future Trend. Proceedings of the 27th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 2021. [paper link]
  • Shane Roach, Connie Ni, Alexei Kopylov, Tsai-Ching Lu, Jiejun Xu, Si Zhang, Boxin Du, Dawei Zhou, Jun Wu, Lihui Liu, Yuchen Yan, Jingrui He, and Hanghang Tong, CANON: Complex Analytics of Network of Networks for Modeling Adversarial Activities. Proceedings of the IEEE International Conference on Big Data (IEEE BigData). 2020. [paper]
  • Lihui Liu, Boxin Du, Heng Ji, Hanghang Tong, Kompare: A Knowledge Graph Reasoning Prototype. Demos of the Neural Information Processing Systems (NeurIPS), 2020. [paper] [demo]
  • Du, Boxin, and Hanghang Tong. "MrMine: Multi-resolution Multi-network Embedding." Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM). 2019. [paper] [slides] [code]
  • Liu, lihui, Boxin Du, Jiejun Xu, and Hanghang Tong. “G-Finder: Approximate Attributed Subgraph Matching.” Proceedings of the IEEE International Conference on Big Data (IEEE BigData). 2019. [paper] [code]
  • Du, Boxin, and Hanghang Tong. "FASTEN: Fast Sylvester Equation Solver for Graph Mining." In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, pp. 1339-1347. ACM, 2018. [paper] [slides] [code]
  • Du, Boxin, Si Zhang, Nan Cao, and Hanghang Tong. "FIRST: Fast Interactive Attributed Subgraph Matching." In Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1447-1456. ACM, 2017. [paper] [slides] [code]

Tutorials

  • New Frontiers of Multi-Network Mining: Recent Developments and Future Trend (@KDD 2021) [link]

Main Projects

  • Subgraph matching toolbox [link]
  • Knowledge graph comparative reasoning system [video demo] [link: to appear]

Teaching

  • Teaching Assistant, CS412: Introduction to Data Mining, Jiawei Han, Hanghang Tong. University of Illinois at Urbana-Champaign, Fall 2019.
  • Teaching Assistant, CS575: Statistical Machine Learning, Hanghang Tong. Arizona State University, Spring 2017.
  • Teaching Assistant, CS575: Statistical Machine Learning, Jingrui He. Arizona State University, Fall 2016.

Professional Services

  • Program Committee member: CIKM (2021), SDM (2020), IJCAI (2020), PAKDD (2020, 2019), IEEE BigData (2019, 2018), etc.
  • Sub-reviewer of conferences: WWW (2020), NeurIPS (2020), KDD (2020, 2019), ICDM (2020, 2019), WSDM (2020), ICLR (2020), ICML (2019), ICDM (2019), CIKM (2018, 2017), BigMine (2018), MLG (2018), ICWSM-18, WWW2018Satellites, DASFAA (2018), BESC (2017), ACM MM (2017), ASONAM (2017), ICWSM-17, AAAI-17, etc.
  • Reviewer of Jornal: TKDE, DAMI, etc.

Industry Experiences

  • Applied Science Intern, Amazon, New York, June 2020 - Aug. 2020
  • Research Intern, WeWork, Palo Alto, June 2019 - Aug. 2019

Honors and Awards

  • SIGIR Student Travel Award, Nov. 2019
  • KDD Student Travel Award, Aug. 2018
  • KDD Student Travel Award, Aug. 2017