Short Bio

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 in 2022 and my B.Eng degree in computer science and technology from Beihang University in 2017, supervised by Prof. Shuai Ma.

Research Interests

For more details, visit our lab website FIU Trustworthy AI Lab

Explainable AI, Robust AI, Physical-aware AI

Self-Supervised Learning, Fast Domain Adaptation, Model Compression/ Automatic Feature Selection

Federated Learning,Multi-domain Analysis, Applications in Health Informatics, Neuroscience

Time series, Graph Neural Network, Spatiotemporal Data Analysis

Selected Publications

Google Scholar

^E indicates equal contribution, ______ indicates students under my supervision

Workshop/Recent Preprints

• Interpreting Graph Neural Networks with In-Distributed Proxies
  Zhuomin Chen, J. Zhang, J. Ni, X. Li, Y. Bian, M. Islam, A. Mondal, H. Wei and Dongsheng Luo
  WWW 2024 Wokshop: TrustLOG, 2024
  
• PAC Learnability under Explanation-Preserving Graph Perturbations
  Xu Zheng, Farhad Shirani, T. Wang, S. Gao, W. Dong, W. Cheng, and Dongsheng Luo
  Preprint, 2024
  

Accepted

• Parametric Augmentation for Time Series Contrastive Learning
  Xu Zheng, T. Wang, W. Cheng, A. Ma, H. Chen, M. Sha, and Dongsheng Luo
  The International Conference on Learning Representations (ICLR), 2024
  The Second Workshop of Artificial Intelligence for Time Series Analysis: Theory, Algorithms, and Applications (AI4TS), 2023 (Best Paper Award)
  


• Towards Robust Fidelity for Evaluating Explainability of Graph Neural Networks
  Xu Zheng, Farhad Shirani, T. Wang, W. Cheng, Zhuomin Chen, H. Chen, H. Wei, Dongsheng Luo
  The International Conference on Learning Representations (ICLR), 2024
  WWW 2024 Wokshop: TrustLOG, 2024
  


• Factorized Explainer for Graph Neural Networks
  Rundong Huang, Farhad Shirani, Dongsheng Luo
  The AAAI Conference on Artificial Intelligence (AAAI), 2024.


• Towards Inductive and Efficient Explanations for Graph Neural Networks
  Dongsheng Luo, T. Zhao, W. Cheng, D. Xu, F. Han, W. Yu, X. Liu, H. Chen, Xiang Zhang
  IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
  


• MixupExplainer: Generalizing Explanations for Graph Neural Networks with Data Augmentation
  Jiaxing Zhang^E, Dongsheng Luo^E, Hua Wei
  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
  Proceedings of the AAAI International 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
  [code]


• A Collective Approach to Scholar Name Disambiguation
  Dongsheng Luo, Shuai Ma, Yaowei Yan, Chunming Hu, Xiang Zhang, and Jinpeng Huai
  In IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022
  IEEE International Conference on Data Engineering (ICDE), 2021.
  [code]


• Learning to Drop: Robust Graph Neural Network via Topological Denoising
  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
  [code]


• Parameterized Explainer for Graph Neural Network
  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
  [code] [ML Reproducibility]


• Local Community Detection in Multiple Networks
  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
  [code]


• Deep Multi-Graph Clustering via Attentive Cross-Graph Association
  Dongsheng Luo, Jingchao Ni, Suhang Wang, Yuchen Bian, Xiong Yu, Xiang Zhang
  Proceedings of the ACM International Conference on Web Search and Data Mining (WSDM), 2020
  [code]


• Memory-based random walk for multi-query local community detection
  Yuchen Bian^E, Dongsheng Luo^E, Yaowei Yan, Wei Cheng, Wei Wang, and Xiang Zhang
  Knowledge and Information Systems (KAIS), 2020
  (Best Paper Candidate of ICDM 2018)
  [code]


• Ensemble Enabled Weighted PageRank
  Dongsheng Luo, Chen Gong, Renjun Hu, Liang Duan, and Shuai Ma
  The WSDM Cup 2016 - Entity Ranking Challenge (WSDM CUP), 2016
  (The 2nd place in the final ranking)
  

Teaching

• FIU
  • CAP 6778 Advanced Topics in Data Mining (Fall 2022, Spring 23, Fall 2023, Spring 24)
• 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)

Patents

• W Cheng, H Chen, J Ni, W Yu, Y Chen, D Luo ``Contrastive Time Series Representation Learning via Meta-Learning'' U.S. 2023
• W. Cheng, H. Chen, X. Zhang, D. Luo, ``Keyphrase Generation for Text Search with Optimal Indexing Regularization via Reinforcement Learning'',U.S., 2022.
• W. Cheng, H. Chen, J. Ni, D. Luo, ``Unsupervised Document Representation Learning via Contrastive Augmentation'',U.S., 2021.
• S. Ma, D. Luo, C. Gong, R. Hu, ``An ensemble-based system and method for scholarly article ranking'', Patent Number: CN105740386B.4, China, 2016.

Professional Services

• Senior Program Committee Member:
  • AAAI' 23, 24


• Program Committee Member/Reviewer:
  • ICML'23, 24
  • NeurIPS'22, 23
  • ICLR'24
  • KDD'20,21,22,23
  • TheWebConf (WWW)'24
  • WSDM'23,24
  • AAAI'21
  • IJCAI'23,24
  • 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)
  • ACM Transactions on Knowledge Discovery from Data (TKDD)
  • IEEE Transactions on Big Data (TBD)
  • IEEE Transactions on Knowledge and Data Engineering (TKDE)
  • Neurocomputing
  • Data Mining and Knowledge Discovery (DAMI)
  • IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
  • VLDB Journal
  • Knowledge and Information Systems (KAIS)

Honors and Awards

• Best Paper Award, AI4TS@IJCAI, 2023
• College of IST Ph.D. Award for Research Excellence, Penn State University, 2021
• Best Paper Award Finalist, ICDM, 2018
• Outstanding Undergraduate Student Award of Beijing City, 2017
• CSC Outstanding Undergraduate Exchange Program Award, 2016
• WSDM Cup 2016 – Entity Ranking Challenge the 2nd place in the final ranking, 2016
• China National Undergraduate Scholarship: 2014, 2015