Hanghang Tong

Introduction

The main focus of IDEA Lab@UIUC lies in 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.

Publications

• Selected

• Google Scholar

• DBLP

• Presentations

Projects

• Recent:

  • safe graph neural networks

  • diffusion history reconstruction

  • optimal deep graph learning

  • fair network learning

  • network correspondence

  • teams in big networks

  • network robustification

Lab Members

• Current

  • Mr. Baoyu Jing (Ph.D student, spatial-temporal graphs)

  • Mr. Yuchen Yan (Ph.D student, graph association)

  • Mr. Zhe Xu (Ph.D student, optimal graphs and augmentation)

  • Ms. Xinyu He (Ph.D student, graph dynamics)

  • Ms. Eunice Chan (Ph.D student, fairness)

  • Mr. Zhining Liu (Ph.D student, graph attribution)

  • Mr. Hyunsik Yoo (Ph.D student, recommendation)

  • Mr. Zhichen Zeng (Ph.D student, multi-networks)

  • Mr. Xiao Lin (Ph.D student, networked time series)

  • Mr. Ruizhong Qiu (Ph.D student, graph algorithm)

  • Mr. Oliver (Gaotang) Li (Ph.D student, graph algorithm)

  • Mr. Ting Wei Li (Ph.D student, graph algorithm)

  • Dr. Jun-Gi Jang (Post-doc, tensor)

• Alumni

  • Dr. Lihui Liu (Ph.D 2024, knowledge graph reasoning)

  • Dr. Yunyong Ko (Post-doc, 2022-2024, hypergraph)

  • Dr. Jian Kang (Ph.D 2023, algorithmic fairness on graphs)

  • Dr. Qinghai Zhou (Ph.D 2023, graph anomaly)

  • Dr. Boxin Du (Ph.D 2021, multi-network association]

  • Dr. Si Zhang (Ph.D 2021, network alignment)

  • Dr. Liangyue Li (Ph.D 2018, team performance)

  • Dr. Chen Chen (Ph.D 2019, network connectivity optimization)

  • Dr. Xing Su (Ph.D 2017, mobile mining)

  • Dr. Shweta Jain (post-doc, 2020-2021 clique counting)

  • Dr. Rui Zhang (post-doc, 2019-2020, graph fusion)

  • Mr. Scott Freitas (BS 2017, master 2018, pathway mining)

  • Mr. Haichao Yu (Master 2018, multi-layered networks)

  • Ms. Ruiyue Peng (Master 2016, network connectivity)

  • Mr. Rongyu Lin (Master 2016, team performance)

  • Mr. Xiaoyu Zhang (Master 2017, team performance and network completion)

  • Mr. Zhe Xu (Master 2021, dense subgraphs)

  • Mr. Yuheng Zhang (Master 2022, batch active learning on graphs)

  • Mr. Shengyu Feng (Master 2022, graph contrastive learning)

  • Ms. Yian Wang (Master 2023, multi-view graph mining)

  • Mr. Zhichen Zeng (Master 2023, network alignment)

  • Mr. Derek Wang (Master 2023, networked time series)

  • Mr. Blaine Hill (Master 2024, knowledge graphs)

  • Ms. Ishika Agarwal (Master 2024, graph anomaly detection)

  • Mr. Ruizhong Qiu (Master 2024,Siebel Scholar, graph diffusion)

• CS512: Data Mining Principles, spring 2021, fall, 2022, spring 2024

• CS514: Advanced Topics in Network Science, fall 2023, fall 2024

• CS412: Introduction to Data Mining, fall, 2019, fall 2020, spring 2022, spring 2023

• gateio

• CSE575: Statistical Machine Learning, spring 2016, spring 2017, fall 2017, fall 2018

• CSE310: Data Structures and Algorithms, fall 2015

• CSE591: Semantic Web Mining, spring 2015

• I1900 Pattern Recognition and Machine Learning, spring 2014

• CS84010: Big Data Analytics, fall 2013

• Recent Events:

  • Editor-in-Chief, ACM SIGKDD Explorations

  • PC co-chairs, DSAA 2024 (research track)

  • PC co-chairs, CIKM 2021

  • PC co-chairs, CSoNet 2019

  • PC co-chairs, workshop on graph techniques for adversarial activity modeling , since 2020

  • Associate Editor, ACM Computing Surveys, since 2020

• Full list: see my cv

• University Scholar, UIUC, 2024

• IEEE ICDM 2022 10-Year Highest Impact Paper Award, 2022

• Springer Knowl. Inf. Syst. (KAIS) on “Best-ranked paper of ICDM 2022”, 2022

• Dean's Award for Excellence in Research, Associate Professor, 2022

• IEEE Fellow, 2021 (for contributions to graph mining)

• Excellent Paper Award, IEEE Big Data Mining and Analytics, 2021

• Best Student Paper Runner-up, IEEE ICDM, 2021

• ACM Distinguished Member, 2020

• Teachers Ranked as Excellent, Spring 2020, fall 2023

• IEEE ICDM Tao Li Award, 2019

• SDM/IBM Early Career Data Mining Research Award, 2018

• ICWSM Best Reviewer Award, 2018

• NSF CAREER award, 2017

• ASU CIDSE Best Researcher Award – Junior Faculty, 2017

• ACM CIKM’17 Best Demo Candidate (Second Place), 2017

• SIGMOD’17 Best Demo, Honorable Mention, 2017

• ACM TKDD on “Bests of KDD 2016”, 2016

• 10-Year Highest-Impact Paper Award, The 15th IEEE International Conference on Data Mining (ICDM), 2015.

• Knowl. Inf. Syst. (KAIS) on “Bests of ICDM 2015”, 2015.

• Best Paper Award, IEEE Tsinghua Science and Technology, 2015.

• Statistical Analysis and Data Mining on “Bests of SDM 2015”, 2015.

• Best Paper Award, The 21st ACM International Conference on Information and Knowledge Management (CIKM), 2012.

• IBM Research Accomplishment Award on “Social and Cognitive Network Science”, 2012.

• Statistical Analysis and Data Mining on “Bests of SDM 2011”, 2011.

• Frontiers of Computer Science on “Bests of ICDM 2010”, 2010.

• Best Paper Award, 2008 SIAM Conference on Data Mining (SDM), 2008

• Best Research Paper Award, The 6th IEEE International Conference on Data Mining (ICDM), 2006.