Computational Data Science Lab

Neural Methods for Optimization

We are often dealing with decision-making tasks associated with models subject to environment uncertainties. In this project, we develop algorithmic and learning foundations for data-driven optimization.

Selected publications:
☸ PAKDD 2024. Guangmo Tong, Peng Zhao, and Mina Samizadeh. "Query-Decision Regression Between Shortest Path and Minimum Steiner Tree." ACM International Conference on Information and Knowledge Management, 2023
☸ CIKM 2023. Guangmo Tong and Mina Samizadeh. "VN-Solver: Vision-based Neural Solver for Combinatorial Optimization over Graphs." Pacific-Asia Conference on Knowledge Discovery and Data Mining. Singapore: Springer Nature Singapore, 2024
☸ NeurIPS 2021. Guangmo Tong. "USCO-Solver: Solving Undetermined Stochastic Combinatorial Optimization Problems." Advances in Neural Information Processing Systems 34 (2021): 1646-1659.
☸ NeurIPS 2020. Guangmo Tong. "StratLearner: learning a strategy for misinformation prevention in social networks." Advances in Neural Information Processing Systems 33 (2020): 15546-15555.

Social Influence Analysis

Dynamics of opinions, epidemics, and behaviors are fundamental phenomena. In this project, we develop learning and algorithmic techniques for modeling and managing social influence.

Selected publications:
☸ CSoNet 2024 (Best Paper Award). Siqi Wang, Jiahao Xie, Yifan Wang, and Guangmo Tong. "Query-Decision Regression for Misinformation Prevention in Social Networks" 13th International Conference on Computational Data and Social Networks, 2024.
☸ NeurIPS 2022. Guangmo Tong. "Social-Inverse: Inverse Decision-making of Social Contagion Management with Task Migrations" Advances in Neural Information Processing Systems, 2019.
☸ IJCAI 2022. Yifan Wang and Guangmo Tong. "Learnability of Competitive Threshold Models." the 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence, 2022
☸ INFOCOM 2019. Guangmo Tong and Ding-Zhu Du. "Beyond uniform reverse sampling: A hybrid sampling technique for misinformation prevention." IEEE conference on computer communications, 2019.
☸ NeurIPS 2018. Guangmo Tong, Ding-Zhu Du, and Weili Wu. "On misinformation containment in online social networks." Advances in neural information processing systems 31, 2018.
☸ INFOCOM 2017. Guangmo Tong, Weili Wu, Ling Guo, Deying Li, Cong Liu, Bin Liu, and Ding-Zhu Du. "An efficient randomized algorithm for rumor blocking in online social networks." IEEE Conference on Computer Communications, 2017.

Cyber-Physical Systems

In collaboration with other research labs, our research aims to provide algorithmic and machine learning solutions to applications in various cyber-physical systems, including connected autonomous vehicles, wireless networks, real-time systems, and point cloud based sensing technologies.

Selected publications:
☸ TIOT 2022. Zheng Dong, Yan Lu, Guangmo Tong, Yuanchao Shu, Shuai Wang, and Weisong Shi. "Watchdog: Real-time vehicle tracking on geo-distributed edge nodes." ACM Transactions on Internet of Things, 2022.
☸ IoT-J 2020. Mozi Chen, Kezhong Liu, Jie Ma, Xuming Zeng, Zheng Dong, Guangmo Tong, and Cong Liu. "MoLoc: Unsupervised fingerprint roaming for device-free indoor localization in a mobile ship environment." IEEE Internet of Things Journal, 2020.
☸ MetroCAD 2020. Zheng Dong, Weisong Shi, Guangmo Tong, and Kecheng Yang. "Collaborative autonomous driving: Vision and challenges." IEEE International Conference on Connected and Autonomous Driving, 2020.