Openings

May 2024: I am looking for remote interns/Ph.D. students working on AI for environmental science and XAI for science.

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

• Trustworthy AI : Explainable AI, Robust AI, Physical-Aware AI
• Data/Label Efficient AI: Self-Supervised Learning, Fast Domain Adaptation, Model Compression/ Automatic Feature Selection
• Multi-Source, Multi-Modality Machine Learning: Federated Learning,Multi-domain Analysis
• Data Mining : Time series, Graph Neural Network, Spatiotemporal Data Analysis

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

Ph.D. Students

Selected Publications

Google Scholar

Recent Workshop/Preprints

• PAC Learnability under Explanation-Preserving Graph Perturbations
  Xu Zheng, Farhad Shirani, T. Wang, S. Gao, W. Dong, W. Cheng and Dongsheng Luo
• Spectral GNN via Two-dimensional (2-D) Graph Convolution
  Guoming Li, J. Yang, S. Liang and Dongsheng Luo
• Elevating Spectral GNNs through Enhanced Band-pass Filter Approximation
  Guoming Li, J. Yang, S. Liang and Dongsheng Luo

Conference/Journal Papers

• Generating In-Distribution Proxy Graphs for Explaining Graph Neural Networks
  Zhuomin Chen, J. Zhang, J. Ni, X. Li, Y. Bian, M. Islam, A. Mondal, H. Wei and Dongsheng Luo
  The International Conference on Machine Learning (ICML), 2024
  WWW 2024 Wokshop: TrustLOG, 2024
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• TimeX++: Learning Time-Series Explanations with Information Bottleneck
  Zichuan Liu, T. Wang, J. Shi, Xu Zheng, Zhuomin Chen, L. Song, W. Dong, J. Obeysekera, Farhad Shirani and Dongsheng Luo
  The International Conference on Machine Learning (ICML), 2024
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• 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)
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• 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 (Best Paper Award Runner-Up)
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• Factorized Explainer for Graph Neural Networks
  Rundong Huang, Farhad Shirani, Dongsheng Luo
  The AAAI Conference on Artificial Intelligence (AAAI), 2024.
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• 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.
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• 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
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• Random Walk on Multiple Networks
  Dongsheng Luo, Yuchen Bian, Yaowei Yan, Xiong Yu, Jun Huan, Xiao Liu, Xiang Zhang
  IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023.
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• A Collective Approach to Scholar Name Disambiguation
  Dongsheng Luo, Shuai Ma, Yaowei Yan, Chunming Hu, Xiang Zhang, and Jinpeng Huai
  IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022
  Extend Abstract at IEEE International Conference on Data Engineering (ICDE), 2021.
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• Learning to Drop: Robust Graph Neural Network via Topological Denoising
  Dongsheng Luo, Wei Cheng, Wenchao Yu, Bo Zong, Jingchao Ni, Haifeng Chen, Xiang Zhang
  Proceedings of 14th ACM International Conference on Web Search and Data Mining (WSDM), 2021.
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• Parameterized Explainer for Graph Neural Network
  Dongsheng Luo, Wei Cheng, Dongkuan Xu, Wenchao Yu, Bo Zong, Haifeng Chen, Xiang Zhang
  Proceedings of 34th Conference on Neural Information Processing Systems (NeurIPS), 2020
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• Local Community Detection in Multiple Networks
  Dongsheng Luo, Yuchen Bian, Yaowei Yan, Xiao Liu, Jun Huan, Xiang Zhang
  Proceedings of 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2020.
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• 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.
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Teaching

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

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:
  • 2024: ICML, ICLR, NeurIPS, WWW, WSDM, IJCAI, ICDM, SDM, LOG, ICASSP
  • 2023: ICML, NeurIPS, SIGKDD, WSDM, IJCAI, ICDM, LOG
  • 2022: NeurIPS, SIGKDD, ICDM, SDM
  • 2021: SIGKDD, AAAI
  • 2020: SIGKDD


• 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 Big Data (TBD)
  • 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 Runner-Up, TrustLOG@WWW, 2024
• 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