Scholar
Hanghang Tong
Google Scholar ID: RaINcuUAAAAJ
University of Illinois at Urbana-Champaign
Citations & Impact
Citations
33,805
H-index
57
i10-index
258
Publications
20
Co-authors
85
list available
Contact
Publications
Resume (English only)
Academic Achievements
- IEEE Fellow (2021, for contributions to graph mining); IEEE ICDM 2022 10-Year Highest Impact Paper Award; Springer Knowl. Inf. Syst. (KAIS) on 'Best-ranked paper of ICDM 2022'; Dean's Award for Excellence in Research (2022); Excellent Paper Award, IEEE Big Data Mining and Analytics (2021); Best Student Paper Runner-up (IEEE). Served as PC co-chairs for multiple top conferences.
Research Experience
- Leading the IDEA Lab@UIUC, focusing on projects such as safe graph neural networks, diffusion history reconstruction, optimal deep graph learning, fair network learning, network correspondence, teams in big networks, and network robustification.
Education
- No specific educational background information provided.
Background
- Professor & University Scholar at the Department of Computer Science, University of Illinois at Urbana-Champaign. Research interests include large scale data mining, machine learning, and AI, especially for graph and multimedia data with applications to social networks analysis, healthcare, cyber-security, cyber-physical systems, agriculture, and e-commerce.
Miscellany
- Teaches several courses including CS512: Data Mining Principles, CS514: Advanced Topics in Network Science, CS412: Introduction to Data Mining, and more.
