About me
I am Qinghai Zhou (周庆海), currently a Ph.D. candidate from the department of Computer Science at University of Illinois at Urbana-Champaign, advised by Dr. Hanghang Tong. My research interests are broadly in data mining and machine learning, with a focus on large-scale graph mining and its applications in network analysis. I received my MS in Computer Engineering from the University of Florida in 2016 and BS in Physics from Nanjing University in 2014.
Publication
- Zhou, Qinghai, Liangyue Li, Nan Cao, Norbou Buchler, and Hanghang Tong. “Extra: Explaining team recommendation in networks.” In Proceedings of the 12th ACM Conference on Recommender Systems (pp. 492-493). 2018.
- Zhou, Qinghai, Liangyue Li, Nan Cao, Lei Ying, and Hanghang Tong. “ADMIRING: Adversarial Multi-network Mining.” In 2019 IEEE International Conference on Data Mining (ICDM) (pp. 1522-1527). IEEE, 2019
- Zhou, Qinghai, Liangyue Li, and Hanghang Tong. “Towards Real Time Team Optimization.” In 2019 IEEE International Conference on Big Data (Big Data) (pp. 1008-1017). IEEE, 2019.
- Zhou, Qinghai, Liangyue Li, Xintao Wu, Nan Cao, Lei Ying, Hanghang Tong. “ATTENT: Active Attributed Network Alignment.” In Proceedings of the Web Conference 2021 (pp. 3896-3906).
- Zhou, Qinghai*, Kaize Ding*, Hanghang Tong, Huan Liu. “Few-shot Network Anomaly Detection via Cross-network Meta-Learning.” In Proceedings of the Web Conference 2021 (pp. 2448-2456). (*equal contribution)
- Zhou, Qinghai*, Jian Kang*, Hanghang Tong. “JuryGCN: Quantifying Jackknife Uncertainty on Graph Convolutional Networks.” In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 742-752). (*equal contribution)
- Yan, Yuchen, Qinghai Zhou, Jinning Li, Tarek Abdelzaher, Hanghang Tong. “Dissecting Cross-Layer Dependency Inference on Multi-Layered Inter-Dependent Networks.” In Proceedings of the 31st ACM International Conference on Information & Knowledge Management (pp. 2341-2351).
- Xu, Zhe, Yuzhong Chen, Qinghai Zhou, Yuhang Wu, Menghai Pan, Hao Yang, Hanghang Tong. “Node Classification Beyond Homophily: Towards a General Solution.” In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 2862-2873).
- Zhou, Qinghai, Kaize Ding, Huan Liu, Hanghang Tong. “Learning Node Abnormality with Weak Supervision.” In 2023 ACM CIKM. 2023
Industrial Experiences
- Meta AI Applied Research, Research Intern, May 2022 – Aug. 2022
- Facebook AI Applied Research, Research Intern, Jun. 2021 – Aug. 2021
Professional Services
- Program Committee: AAAI (SPC, 2022, 2023), KDD (2022, 2023), WWW (2023), IJCAI (2021-2023), CIKM (2022-2023), SDM (2022, 2023).
- Journal Review: TKDD, TKDE
Contacts
- Email: qinghai2 AT illinois DOT edu