Dongsheng Luo
Assistant Professor |
I am an assistant professor at Florida International University. I obtained my doctoral degree at the College of Information Science and Technology, Pennsylvania State University, supervised by Prof. Xiang Zhang and my B.Eng degree in computer science and technology from Beihang University in 2017, supervised by Prof. Shuai Ma.
Our lab is dedicated to crafting efficient and trustworthy AI solutions for science. We prioritize models that are practical for real-world deployment and emphasize transparency, robustness, and reliability. We actively bridge the gap between AI and scientific domains. Through interdisciplinary collaborations, we tailor our AI innovations to address complex challenges in environmental science, health informatics, and human computer interaction, thereby faciliating impactful scientific advancements..
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Towards Robust Fidelity for Evaluating Explainability of Graph Neural Networks [arxiv]
Xu Zheng*, Farhad Shirani*, Tianchun Wang, Wei Cheng, Zhuomin Chen, Haifeng Chen, Hua Wei, Dongsheng Luo
Learning Graph Filters for Spectral GNNs via Newton Interpolation [arxiv]
Junjie Xu, Enyan Dai, Dongsheng Luo, Xiang Zhang, Suhang Wang
RegExplainer: Generating Explanations for Graph Neural Networks in Regression Task [arxiv]
Jiaxing Zhang, Zhuomin Chen, Hao Mei, Dongsheng Luo, Hua Wei
Self-Explainable Graph Neural Networks for Link Prediction [arxiv]
Huaisheng Zhu, Dongsheng Luo, Xianfeng Tang, Junjie Xu, Hui Liu, Suhang Wang
Unsupervised document embedding via contrastive augmentation [arxiv]
Dongsheng Luo, Wei Cheng, Jingchao Ni, Wenchao Yu, Xuchao Zhang, Bo Zong, Yanchi Liu, Zhengzhang Chen, Dongjin Song, Haifeng Chen, Xiang Zhang
Shedding Light on Random Dropping and Oversmoothing
Han Xuanyuan, Tianxiang Zhao, Dongsheng Luo
NeurIPS 2023 Workshop: New Frontiers in Graph Learning, 2023
Faithful and Consistent Graph Neural Network Explanations with Rationale Alignment
Tianxiang Zhao, Dongsheng Luo , Xiang Zhang, Suhang Wang
ACM Transactions on Intelligent Systems and Technology (TIST), 2023
An End-to-End Tool Decoding Highly Corrupted Satellite Stream from Eavesdropping
Minghao Lin, Minghao Cheng, Xu Zheng, Dongsheng Luo, Yueqi Chen
BlackHat USA 2023 Arsenal
AutoTCL: Automated Time Series Contrastive Learning with Adaptive Augmentations
Xu Zheng, Tianchun Wang, Wei Cheng, Aitian Ma, Haifeng Chen, Mo Sha, and Dongsheng Luo
The Second Workshop of Artificial Intelligence for Time Series Analysis: Theory, Algorithms, and Applications (AI4TS), August 2023 (Best Paper Award)
Unsafe Behavior Detection with Adaptive Contrastive Learning in Industrial
Control Systems
Xu Zheng, Tianchun Wang, Samin Y. Chowdhury, Ruimin Sun, Dongsheng Luo
Workshop on Re-design Industrial Control Systems with Security (RICSS) @ IEEE EuroS&P 2023
MixupExplainer: Generalizing Explanations for Graph Neural Networks with Data Augmentation
Jiaxing ZhangE, Dongsheng LuoE, Hua Wei
In Proceedings of 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2023
Time Series Contrastive Learning with Information-Aware Augmentations
Dongsheng Luo, W. Cheng, Y. Wang, D. Xu, J. Ni, W. Yu, X. Zhang, Y. Liu, Y. Chen, H. Chen, Xiang Zhang
In AAAI Conference on Artificial Intelligence (AAAI), 2023
Random Walk on Multiple Networks.
Dongsheng Luo, Yuchen Bian, Yaowei Yan, Xiong Yu, Jun Huan, Xiao Liu, Xiang Zhang
in IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023.
MOGAT: An Improved Multi-Omics Integration Framework Using Graph Attention Networks
Raihanul Bari Tanvir, Mezbahul Islam, Masrur Sobhan, Dongsheng Luo, Ananda Mohan Mondal
The 15th RECOMB Satellite Workshop on Computational Cancer Biology (RECOMB-CCB 23)
CLExtract: Recovering Highly Corrupted DVB/GSE Satellite Stream with Contrastive Learning
Minghao Lin, Minghao Cheng, Dongsheng Luo, Yueqi Chen
Workshop on the Security of Space and Satellite Systems (SpaceSec) 2023
Towards Faithful and Consistent Explanations for Graph Neural Networks
Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang.
In ACM International Conference on Web Search and Data Mining (WSDM), 2023.
A Collective Approach to Scholar Name Disambiguation. [paper] [code]
Dongsheng Luo, Shuai Ma, Yaowei Yan, Chunming Hu, Xiang Zhang, and Jinpeng Huai
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022.
TopoImb: Toward Topology-level Imbalance in Learning from Graphs
Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang.
In Learning on Graphs Conference (LOG), 2022.
Personalized Federated Learning via Heterogeneous Modular Networks.
Tianchun Wang, Wei Cheng, Dongsheng Luo, Wenchao Yu, Jingchao Ni, Liang Tong, Haifeng Chen, Xiang Zhang.
In 2022 IEEE International Conference on Data Mining (ICDM'22).
Learning to Drop: Robust Graph Neural Network via Topological Denoising [arxiv][code] [slides][poster][video]
[中文解读]
Dongsheng Luo, Wei Cheng, Wenchao Yu, Bo Zong, Jingchao Ni, Haifeng Chen, Xiang Zhang
In Proceedings of 14th ACM International Conference on Web Search and Data Mining (WSDM), 2021
A Collective Approach to Scholar Name Disambiguation. [paper] [code]
Dongsheng Luo, Shuai Ma, Yaowei Yan, Chunming Hu, Xiang Zhang, and Jinpeng Huai
IEEE International Conference on Data Engineering (ICDE), 2021 (TKDE Extended Abstract)
Attentive Social Recommendation:Towards User And Item Diversities [arxiv][code]
Dongsheng Luo, Yuchen Bian, Xiang Zhang, Jun Huan
DLG-AAAI21 Workshop, 2021
InfoGCL: Information-Aware Graph Contrastive Learning
Dongkuan Xu, Wei Cheng, Dongsheng Luo, Haifeng Chen, Xiang Zhang
The 35th Conference on Neural Information Processing Systems (NeurIPS), 2021
Deep Multi-Instance Contrastive Learning with Dual Attention for Anomaly Precursor Detection
Dongkuan Xu, Wei Cheng, Jingchao Ni, Dongsheng Luo, Masanao Natsumeda, Dongjin Song, Bo Zong, Haifeng Chen, Xiang Zhang
The 21th SIAM International Conference on Data Mining (SDM), 2021
Parameterized Explainer for Graph Neural Network [arxiv][appendix][code&data] [slides][poster][video]
[ML Reproducibility 1]
[ML Reproducibility 2]
[中文解读]
Dongsheng Luo, Wei Cheng, Dongkuan Xu, Wenchao Yu, Bo Zong, Haifeng Chen, Xiang Zhang
in Proceedings of 34th Conference on Neural Information Processing Systems (NeurIPS), 2020
Local Community Detection in Multiple Networks [pdf]
[appendix] [code&data][data(DBLP)][slides][video]
[中文解读]
Dongsheng Luo, Yuchen Bian, Yaowei Yan, Xiao Liu, Jun Huan, Xiang Zhang
in Proceedings of 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD),2020
Deep Multi-Graph Clustering via Attentive Cross-Graph Association [pdf][poster]
[spotlight][code&data]
Dongsheng Luo, Jingchao Ni, Suhang Wang, Yuchen Bian, Xiong Yu and Xiang Zhang
Proceedings of the ACM International Conference on Web Search and Data Mining (WSDM), 2020
Memory-Based Random Walk for Multi-Query Local Community Detection. [repo] [code&data]
Yuchen BianE, Dongsheng LuoE, Yaowei Yan, Wei Cheng, Wei Wang, and Xiang Zhang
Knowledge and Information Systems (KAIS), 2019 (Extended version of the ICDM'2018 paper)
Constrained Local Graph Clustering by Colored Random Walk
Yaowei Yan, Yuchen Bian, Dongsheng Luo, Dongwon Lee, and Xiang Zhang
Proceedings of the International Conference on World Wide Web (WWW), 2019
Spatio-Temporal Attentive RNN for Node Classification in Temporal Attributed Graphs.
[中文解读]
Dongkuan Xu, Wei Cheng, Dongsheng Luo, Xiao Liu, Xiang Zhang
Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 2019
Adaptive Neural Network for Node Classification in Dynamic Networks
Dongkuan Xu, Wei Cheng, Dongsheng Luo, Yameng Gu, Xiao Liu, Jingchao Ni, Bo Zong, Haifeng Chen, Xiang Zhang.
Proceedings of the IEEE International Conference on Data Mining (ICDM), 2019
On Multi-Query Local Community Detection. [repo] [code&data]
Yuchen Bian, Yaowei Yan, Wei Cheng, Wei Wang, Dongsheng Luo, and Xiang Zhang
Proceedings of the IEEE International Conference on Data Mining (ICDM), 2018 (Best Paper Candidate)
Query Independent Scholarly Article Ranking
Shuai Ma, Chen Gong, Renjun Hu, Dongsheng Luo, Chunming Hu, and Jinpeng Huai
Proceedings of the IEEE International Conference on Data Engineering (ICDE), 2018
Local Graph Clustering by Multi-Network Random Walk with Restart [code]
Yaowei Yan, Dongsheng Luo, Jingchao Ni, Hongliang Fei, Wei Fan, Xiong Yu, John Yen, and Xiang Zhang
Proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2018
Ensemble Enabled Weighted PageRank[pdf]
Dongsheng Luo, Chen Gong, Renjun Hu, Liang Duan, and Shuai Ma
The WSDM Cup 2016 - Entity Ranking Challenge, San Francisco, CA, USA, 2016. (The 2nd place in the final ranking)
FIU
CAP 6778 Advanced Topics in Data Mining (Fall 2022, Spring 23, Fall 2023)
Teaching Assistant @ PSU
DS 220-001 Data Management for Data Science (Spring 2021)
IST 210: Organization of Data (Fall 2020, Fall 2019)
IST 558: Data Mining II (Spring 2020)
IST 242: Intermediate & Object-Oriented Application Development (Spring 2019)
Senior PC Member:
AAAI 23,24
PC Member & Reviewer:
NeurIPS 22, 23
ICLR 24
ICML 23
KDD 20-23
The Web Conf 24
WSDM 23,24
AAAI 21
IJCAI 23
SDM 22, 24
ICDM 22,23
LOG 22,23
ICASSP 24
Topic Editor:
Self-Supervised Learning for Time Series, Frontiers in Big Data
Journal Reviewer:
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
IEEE Transactions on Knowledge and Data Engineering (TKDE)
ACM Transactions on Knowledge Discovery from Data (TKDD)
IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
VLDB Journal
Knowledge and Information Systems (KAIS)
Data Mining and Knowledge Discovery (DMKD)
IEEE Transactions on Big Data (TBD)
IEEE Computational Intelligence Magazine
Neurocomputing
Sensors