Short Bio

I will be joining Singapore Management University as a Presidential Assistant Professor on July 1st, 2026. I am actively recruiting RAs, Ph.D. students, Postdocs, and visiting scholars. If you are interested in working with me, please send me an email (dsluo [at] smu [dot] edu [dot] sg) with your CV. For the Spring 2027 intake, applications must be submitted before June 30th, 2026.

I was an assistant professor at Florida International University (2022-2026). 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.

Research Interests

• AI for Science : Machine Learning for Scientific Discovery, Environmental Science, Healthcare
• Multimodal LLM: Reasoning over Text, Structured, Time-Series, and Multimodal Data
• Trustworthy AI: Explainability, Robustness, Safety, Systematic Evaluation of Model Reliability
• Data Science: Mining, Analysis, and Learning over Large-Scale Complex Data

Ph.D. Students

I am very fortunate to work with these talented and dedicated students.

• Xu Zheng (Ph.D. student@FIU, Ph.D. Advisor (Spring 2023-Spring 2026), Co-supervised with Dr. Mo Sha, Spring 2026-):
  SIGKDD 26, AAAI 2026, TPAMI 2026, ICLR 2025, ICML 2024b, ICLR 2024a, ICLR 2024b, EuroS&PW 2023
• Zhuomin Chen (Ph.D. student@FIU, Ph.D. Advisor (Fall 2023-Spring 2026), Co-supervised with Dr. Mo Sha, Spring 2026-):
  SIGKDD 26, TPAMI 2026, AAAI 2026, ICLR 2025, NeurIPS 24, ICML 2024a, ICML 2024b, ICLR 2024b
• Esteban Schafir (Ph.D. student@FIU, Ph.D. Advisor (Summer 2025-Spring 2026), Co-supervised with Dr. Mo Sha, Spring 2026-):
  AAAI 2026, TPAMI 2026

Selected Publications

Google Scholar  |  Full Publications

Recent Workshop/Preprints

• From Signals to Semantics: A Survey on Time Series Explainability through a Human-Cognitive Lens
  Zhuomin Chen, Gabriel Lucchesi, Qingkai Dong, Xu Zheng, Dongjin Song, Qingsong Wen, Wei Cheng, Jingchao Ni, Dongsheng Luo
  Preprint, 2026
• L2motifs: An Explainable Framework for Machine-Generated Texts Detection
  Xu Zheng, Zhuomin Chen, Esteban Schafir, Sipeng Chen, Hojat Allah Salehi, Haifeng Chen, Farhad Shirani, Wei Cheng, Dongsheng Luo
  Arxiv, 2025
• From Binary to Continuous: Stochastic Re-Weighting for Robust Graph Explanation
  Zhuomin Chen, Jingchao Ni, Hojat Allah Salehi, Xu Zheng, Dongsheng Luo
• Trajectory Graph Copilot: Pre-Action Error Diagnosis in LLM Agents
  Xu Zheng, Zhuomin Chen, Chaohao Lin, Hua Wei, Haifeng Chen, Wei Cheng, Dongsheng Luo
• 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

Conference/Journal Papers

• Uncovering Insights of Compound Flooding with Data-Driven AI
  Xu Zheng, Chaohao Lin, Sipeng Chen, Zhuomin Chen, Jimeng Shi, Jayantha Obeysekera, Jingchao Ni, Wei Cheng, Jason Liu, Dongsheng Luo
  Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2026


• Addressing Structural Distribution Shift in Explanations for Graph Neural Networks
  Zhuomin Chen, Hojat Allah Salehi, Esteban Schafir, Xu Zheng, Jiaxing Zhang, Hua Wei, Jingchao Ni, Farhad Shirani, Dongsheng Luo
  IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2026.
  


• Explanation-Preserving Augmentation for Semi-Supervised Graph Representation Learning
  Zhuomin Chen, Jingchao Ni, Hojat Allah Salehi, Xu Zheng, Esteban Schafir, Farhad Shirani, Dongsheng Luo
  The AAAI Conference on Artificial Intelligence (AAAI), 2026
  


• F-Fidelity: A Robust Framework for Faithfulness Evaluation of Explainable AI
  Xu Zheng, Farhad Shirani, Zhuomin Chen, Chaohao Lin, Wei Cheng, Wenbo Guo, Dongsheng Luo
  The International Conference on Learning Representations (ICLR), 2025
  


• Elevating Spectral GNNs through Enhanced Band-pass Filter Approximation
  Guoming Li, J. Yang, S. Liang and Dongsheng Luo
  The Web Conference (WWW), 2025
  


• 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
  Also Present at WWW Workshop: 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
  Also Present at IJCAI Workshop: 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
  Also Present at WWW Workshop: 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

• FIU CAP 6778 Advanced Topics in Data Mining (Fall 2022, Spring 23, Fall 2023, Spring 24, Fall 2024, Spring 2025)
• FIU CAP 5768 Introduction to Data Science (Spring 2025)

Professional Services

• Senior Program Committee Member/Area Chair:
  • Area Chair: ICLR 26, SIGKDD AI4Science Track 26, NeurIPS 25
  • Senior PC: AAAI 23, 24, 25, 26
  • Senior PC: IJCAI 25
  • Senior PC: PAKDD 25


• Program Committee Member/Reviewer:
  • 2026: COLM, ARR
  • 2025: ICML, ICLR, WWW, AISTATS, WACV, AI4TS@AAAI, NAACL Demo
  • 2024: ICML, ICLR, NeurIPS, WWW, WSDM, IJCAI, ICDM, SDM, LOG, ICASSP, ARR Rolling, WACV, MILETS@KDD
  • 2023: ICML, NeurIPS, SIGKDD, WSDM, IJCAI, ICDM, LOG, AI4TS@IJCAI
  • 2022: NeurIPS, SIGKDD, ICDM, SDM
  • 2021: SIGKDD, AAAI
  • 2020: SIGKDD


• Journal Reviewer:
  • IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
  • IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
  • IEEE Transactions on Knowledge and Data Engineering (TKDE)
  • ACM Transactions on Knowledge Discovery from Data (TKDD)
  • IEEE Transactions on Information Forensics and Security
  • IEEE Transactions on Big Data (TBD)
  • Data Mining and Knowledge Discovery (DAMI)
  • The VLDB Journal
  • Knowledge and Information Systems (KAIS)
  • Neurocomputing

Honors and Awards

• Best Paper Award Nominee at IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS'25)
• 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