Dongsheng Luo

Assistant Professor
Knight Foundation School of Computing and Information Sciences
Florida International University
Email: x@fiu.edu where x = dluo
Office: CASE 212 B.

Linkedin, Github, Google Scholar

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

Research Interests

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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I am open to collaborate!

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1. Trustworthy AI

2. Data/Label Efficient AI

3. Multi-source, Multi-modality Machine Learning

4. Non-static and Non-grid Data Analysis

Updates

  • 10/2023: One paper "Learn2Drop" was accepted to GLFrontiers 23.
  • 08/2023: We won the best paper award at AI4TS@IJCAI 23.
  • 06/2023: One Arsenal is accepted to BlackHat USA.
  • 05/2023: One paper on Industrial Control Systems was accepted to RICSS 23.
  • 05/2023: One paper "MixupExplainer" was accepted to SIGKDD 23.
  • 03/2023: One paper "MOGAT" was accepted to RECOMB-CCB 23.
  • 02/2023: One paper "CLExtract" was accepted to SpaceSec 23.
  • 11/2022: One paper "TopoImb" was accepted to Learning on Graphs Conference 22.
  • 11/2022: One paper "InfoTS" was accepted to AAAI 23.
  • 11/2022: One paper on Random Walk was accepted to TKDE 22.
  • 10/2022: One paper on explainable GNNs was accepted to WSDM 23.
  • 08/2022: One paper, FedMN, was accepted to ICDM 22.
  • 08/2022: I joined FIU as an Assistant Professor

    • Publications

    Preprints

    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

    2023

    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.

    2022

    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).

    2021

    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

    2020

    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

    2019 and before

    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)

    Teaching

    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)

    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.

    • Students


    Xu Zheng, (Spring 2023 -).
    Zhuomin Chen, (Fall 2023 -).

    Professional Services

    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

    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 Candidate, 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


    *Last updated on 10/19/2023*