I’m a Ph.d candidate specializing in Artificial Intelligence at the College of Computer Science, Chongqing University. My research interests include aviation big data analytics, explainable artificial intelligence, data mining, causal discovery and so on. I was awarded the National Scholarship for Postgraduates in 2023, Excellent Master’s Thesis of Chongqing in 2022, and has published some articles in top international academic journals/conferences, such as IEEE Transactions on Knowledge and Data Engineering(TKDE), IEEE Transactions on Intelligent Transportation Systems(TITS), Knowledge-Based Systems(KBS), The Visual Computer(TVC), Ubiquitous Intelligence & Computing(UIC), etc. I has carried out the reviewing task of the KDD, KBS, TAES, AESM, and CJOA.

Education

• Ph.D in College of Computer Science, Chongqing University, 2022-now
• M.S. in College of Computer Science, Chongqing University, 2018-2021
• B.S. in College of Information Science and Technology, Nanjing Forestry University, 2014-2018

Publications

2025

Context-Aware Learning and Pattern Decomposition for Temporal Knowledge Graph Reasoning

* (2025). Context-Aware Learning and Pattern Decomposition for Temporal Knowledge Graph Reasoning.(Submitted)

Boosting Low-budget Active Learning with Label Calibration and Unsupervised Representations

Han, Y., Shang, J., Li, R., Li, X., Liao, L., Zheng, L., & Min, G.. (2025). Boosting Low-budget Active Learning with Label Calibration and Unsupervised Representations. IEEE Transactions on Pattern Analysis and Machine Intelligence. (Submitted)

MRI: Memory Retention Mechanism for Interpretable Time Series Forecasting

Li, X., Zheng, L., Shang, J., Liao, L., Zhang, J., & Zhong, J. (2025). MRI: Memory Retention Mechanism for Interpretable Time Series Forecasting. IEEE Transactions on Pattern Analysis and Machine Intelligence.(Submitted)

MDGNN: Multiple Flight Safety Incidents Prediction Model Based on Dynamic Graph Neural Networks

Song, L., Li, X., Liu, H., Wu, L., Sun, H., Zheng, L., & Shang, J. (2025). MDGNN: Multiple Flight Safety Incidents Prediction Model Based on Dynamic Graph Neural Networks. IEEE Transactions on Intelligent Transportation Systems.

ERD-Net: Modeling entity and relation dynamics for Temporal Knowledge Graph reasoning

Liao, L., Zheng, L., Chen, F., Shang, J., Li, X., & Li, W. (2025). ERD-Net: Modeling entity and relation dynamics for Temporal Knowledge Graph reasoning. Knowledge-Based Systems, 317, 113404.

MultiSafe: Multiple Flight Safety Events Prediction Based on Interpretable Deep Multi-Task Learning

Huang, Y., Shang, J., Li, X., et al. (2025). MultiSafe: Multiple Flight Safety Events Prediction Based on Interpretable Deep Multi-Task Learning.(Submitted)

DGAN: Flight sensor data anomaly detection based on dual-view graph attention network

Yan, W., Li, X., Zheng, L., Shang, J., Wu, L., Liu, H., ... & Qian, Y. (2025). DGAN: Flight data anomaly detection based on dual-view graph attention network. IEEE Sensors Journal.

IATCN: Interpretable Attention-Enhanced Temporal Convolutional Network for Multiple Flight Safety Incidents Prediction

Song, L., Sun, H., Li, X., et al. (2025). IATCN: Interpretable Attention-Enhanced Temporal Convolutional Network for Multiple Flight Safety Incidents Prediction.(Submitted)

MGAN: Multi-scale Graph Attention Network for Flight Safety Incidents Detection

Yan, W., Li, X., Zhao, X., et al. (2025). MGAN: Multi-scale Graph Attention Network for Flight Safety Incidents Detection.(Submitted)

A Dual Two-Stage Attention-based Model for interpretable hard landing prediction from flight data

Shang, J., Li, X., Zhang, R., Zheng, L., Li, X., Zhang, R., ... & Sun, H. (2025). A Dual Two-Stage Attention-based Model for interpretable hard landing prediction from flight data. Engineering Applications of Artificial Intelligence, 154, 110911.

MVAN: Towards Interpretable Joint Prediction of Multiple Flight Safety Events with Multi-View Attention Network

Li, C., Li, X., Zheng, L., Shang, J., et al. (2025). MVAN: Towards Interpretable Joint Prediction of Multiple Flight Safety Events with Multi-View Attention Network.(Submitted)

Causal Mamba for Multivariate Time Series Forecasting

* (2025). Causal Mamba for Multivariate Time Series Forecasting. (Submitted)

Crossperformer: Cross-period Transformer for Time Series Forecasting

* (2025). Crossperformer: Cross-period Transformer for Time Series Forecasting. (Submitted)

Fine-Grained Time and Hidden Feature Learning for Interpretable Hard Landing Prediction Based on QAR Data

Cai, J., Shang, J., Li, X., Li, C., & Zheng, L. (2025). Fine-Grained Time and Hidden Feature Learning for Interpretable Hard Landing Prediction Based on QAR Data. IEEE Transactions on Intelligent Transportation Systems.

CCAN: Channel-wise Clustering and Attention Networks for Interpretable Hard Landing Prediction

Zhang, H., Sun, H., Liu, Y., Zhao, X., Li, X., Shang, J., Zheng, L.. (2025). CCAN: Channel-wise Clustering and Attention Networks for Interpretable Hard Landing Prediction.(Submitted)

Query-Guided Temporal Confidence Network for Noisy Temporal Knowledge Graph Reasoning

Liao, L., Zheng, L., Shang, J., Li, X., Zhong, J., & Wei, K.. (2025). Query-Guided Temporal Confidence Network for Noisy Temporal Knowledge Graph Reasoning.(Submitted)

WTAN: Wavelet Transform-based Attention Network for Tail Strike Prediction and Interpretable Analysis

Xiong, D., Li, X., Song, E., et al. (2025). WTAN: Wavelet Transform-based Attention Network for Tail Strike Prediction and Interpretable Analysis.(Submitted)

2024

Decomposition with feature attention and graph convolution network for traffic forecasting

Liu, Y., Wu, X., Tang, Y., Li, X., Sun, D., & Zheng, L. (2024). Decomposition with feature attention and graph convolution network for traffic forecasting. Knowledge-Based Systems, 112193.

ATPF: An Adaptive Temporal Perturbation Framework for Adversarial Attacks on Temporal Knowledge Graph

Liao, L., Zheng, L., Shang, J., Li, X., & Chen, F. (2024). ATPF: An Adaptive Temporal Perturbation Framework for Adversarial Attacks on Temporal Knowledge Graph. IEEE Transactions on Knowledge and Data Engineering.

DUVET: Dual View Enhanced Transformer for Multivariate Flight Time series Anomaly Detection

Li, C., Li, X., Chen, H., Zheng, L., Sun, H., Shang, J. (2024). DUVET: Dual View Enhanced Transformer for MultivariateFlight Time series Anomaly Detection.

2023

SDTAN: Scalable Deep Time-Aware Attention Network for Interpretable Hard Landing Prediction

Chen, H., Shang, J., Zheng, L., Li, X., Liu, X., Sun, H., ... & Yu, L. (2023). SDTAN: Scalable Deep Time-Aware Attention Network for Interpretable Hard Landing Prediction. IEEE Transactions on Intelligent Transportation Systems, 24(9), 10211-10223.

IMTCN: An Interpretable Flight Safety Analysis and Prediction Model Based on Multi-Scale Temporal Convolutional Networks

Li, X., Shang, J., Zheng, L., Wang, Q., Liu, D., Liu, X., ... & Sun, H. (2024). IMTCN: An Interpretable Flight Safety Analysis and Prediction Model Based on Multi-Scale Temporal Convolutional Networks. IEEE Transactions on Intelligent Transportation Systems.

2021

A Deep learning Method for Landing Pitch Prediction based on Flight Data

Chen, H., Shang, J., Zhao, X., Li, X., Zheng, L., & Chen, F. (2020, October). A deep learning method for landing pitch prediction based on flight data. In 2020 IEEE 2nd International Conference on Civil Aviation Safety and Information Technology (ICCASIT (pp. 199-204). IEEE.

Active instance segmentation with fractional-order network and reinforcement learning

Li, X., Wu, G., Zhou, S., Lin, X., & Li, X. (2022). Active instance segmentation with fractional-order network and reinforcement learning. The Visual Computer, 1-14.

A Relation-Guided Attention Mechanism for Relational Triple Extraction

Yang, Y., Li, X., & Li, X. (2021, July). A relation-guided attention mechanism for relational triple extraction. In 2021 International Joint Conference on Neural Networks (IJCNN) (pp. 1-8). IEEE.

CurveCluster+: Curve Clustering for Hard Landing Pattern Recognition and Risk Evaluation Based on Flight Data

Li, X., Shang, J., Zheng, L., Wang, Q., Sun, H., & Qi, L. (2021). Curvecluster+: Curve clustering for hard landing pattern recognition and risk evaluation based on flight data. IEEE Transactions on Intelligent Transportation Systems, 23(8), 12811-12821.

PathSAGE: Spatial Graph Attention Neural Networks with Random Path Sampling

Ma, J., Li, J., Li, X., & Li, X. (2021). PathSAGE: Spatial Graph Attention Neural Networks with Random Path Sampling. In Neural Information Processing: 28th International Conference, ICONIP 2021, Sanur, Bali, Indonesia, December 8–12, 2021, Proceedings, Part II 28 (pp. 111-120). Springer International Publishing.

2020

CurveCluster: Automated Recognition of Hard Landing Patterns Based on QAR Curve Clustering

Li, X., Shang, J., Zheng, L., Liu, D., Qi, L., & Liu, L. (2019, August). CurveCluster: Automated recognition of hard landing patterns based on QAR curve clustering. In 2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI) (pp. 602-609). IEEE.

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