About
Pei-Xuan Li is currently pursuing her Ph.D. in Electrical Engineering (EE) at National Cheng Kung University (NCKU), Taiwan, where she is conducting research with Prof. Hsun-Ping Hsieh from Urban Science and Computing Lab (UCLAB).
She also received the M.S. degree in Electrical Engineering (EE) at National Cheng Kung University (NCKU). She received the B.S. degree in Engineering Science (ES) at National Cheng Kung University (NCKU), Taiwan, where she had been working with Prof. Wei-Guang Teng from Knowledge Discovery Lab.
Her research interests are in geographic information science, data mining, urban computing, and financial computing.
Education
- Ph.D in Electrical Engineering, National Cheng Kung University, Tainan, Taiwan, 2027 (expected)
- M.S. in Electrical Engineering, National Cheng Kung University, Tainan, Taiwan, 2023
- B.S. in Engineering Science, National Cheng Kung University, Tainan, Taiwan, 2021
Publications
A Two-Stage Anomaly-Aware Framework for Robust Traffic Forecasting with Memory-Guided GNNs
Pei-Xuan Li, Cheng-Ru Chou, Jhe-Wei Tsai, Hsun-Ping Hsieh. A Two-Stage Anomaly-Aware Framework for Robust Traffic Forecasting with Memory-Guided GNNs. In Proceedings of the 19th ACM International Conference on Web Search and Data Mining (WSDM '26).
Multi-modal Spatio-temporal Forecasting in Sensor-less Regions: A Dual-stage Graph Approach from Disease to Crime
Pei-Xuan Li, Hsun-Ping Hsieh. Multi-modal Spatio-temporal Forecasting in Sensor-less Regions: A Dual-stage Graph Approach from Disease to Crime. In Proceedings of the 33st ACM International Conference on Advances in Geographic Information Systems (SIGSPATIAL '25).
MAC: A Multi-Agent Reinforcement Learning Framework with Correctable Strategies for Portfolio Management
Kuang-Da Wang*, Pei-Xuan Li*, Hsun-Ping Hsieh, Wen-Chih Peng. MAC: A Multi-Agent Reinforcement Learning Framework with Correctable Strategies for Portfolio Management. IEEE International Conference on Knowledge Innovation and Invention (ICKII) 2025 (Best paper award, * Equal contribution)
Session-based Recommendation with Multi-granularity User Intent and Dual-channel Sparse Graph Attention Networks
Pei-Xuan Li, Chia-Lung Lin, Hsun-Ping Hsieh*. Session-based Recommendation with Multi-granularity User Intent and Dual-channel Sparse Graph Attention Networks. In Proceedings of the 2025 Pacific-Asia Conference on Knowledge Discovery and Data Mining, 2025 (PAKDD '25)
FOG: Feature-Oriented Graph Neural Networks for Tabular Data
Teng-Yuan Tsou, Pei-Xuan Li, Fandel Lin, Hsun-Ping Hsieh*. FOG: Feature-Oriented Graph Neural Networks for Tabular Data. In Proceedings of the 2025 Pacific-Asia Conference on Knowledge Discovery and Data Mining, 2025 (PAKDD '25)
Dual Attention with Self-Adaptive Negative Sampling for Session-Based Recommendation
Yu-Chen Chen*, Pei-Xuan Li*, Hsun-Ping Hsieh, and Chris Shei. 2025. Dual Attention with Self-Adaptive Negative Sampling for Session-Based Recommendation. ACM Trans. Manage. Inf. Syst. Just Accepted (June 2025). https://doi.org/10.1145/3744348 (* Equal contribution)
Prediction for Sensor-less Locations Using Multi-View Graph Fusion Approach with Approximation Module: A Case Study on Dengue Fever Risk Sensor
Pei-Xuan Li and Hsun-Ping Hsieh. 2025. Prediction for Sensor-less Locations Using Multi-View Graph Fusion Approach with Approximation Module: A Case Study on Dengue Fever Risk Sensor. ACM Trans. Intell. Syst. Technol. Just Accepted (February 2025). https://doi.org/10.1145/3718094
ACCEPT: A Context-Sensitive, Configurable, and Extensible Prediction Tool using Grid-based Data Processing and Neural Networks in Geospatial Decision Support
Teng-Yuan Tsou, Shih-Yu Lai, Hsuan-Ching Chen, Jung-Tsang Yeh, Pei-Xuan Li, Tzu-Chang Lee, and Hsun-Ping Hsieh. 2024. ACCEPT: A Context-Sensitive, Configurable, and Extensible Prediction Tool using Grid-based Data Processing and Neural Networks in Geospatial Decision Support. In Proceedings of the 32nd ACM International Conference on Advances in Geographic Information Systems (SIGSPATIAL '24). Association for Computing Machinery, New York, NY, USA, 669–672. https://doi.org/10.1145/3678717.3691275
LINKin-PARK: Land Valuation Information and Knowledge in Predictive Analysis and Reporting Kit via Dual Attention-DCCNN
Teng-Yuan Tsou, Shih-Yu Lai, Hsuan-Ching Chen, Jung-Tsang Yeh, Pei-Xuan Li, Tzu-Chang Lee, and Hsun-Ping Hsieh. 2024. LINKin-PARK: Land Valuation Information and Knowledge in Predictive Analysis and Reporting Kit via Dual Attention-DCCNN. In Proceedings of the 33rd ACM International Conference on Information and Knowledge Management (CIKM '24). Association for Computing Machinery, New York, NY, USA, 5289–5293. https://doi.org/10.1145/3627673.3679239
Dengue Risk Detection and Observation System
Hung Wei Lee, Hsun-Ping Hsieh, Pei-Xuan Li, Chih Ching Tsao, Ally Chang, Po-Jui Lai, Zheng Lu. Dengue Risk Detection and Observation System. IEEE International Conference on Knowledge Innovation and Invention (ICKII) 2024 (Best paper award)
Estimating Future Financial Development of Urban Areas for Deploying Bank Branches: A Local-Regional Interpretable Model
Pei-Xuan Li, Yu-En Chang, Ming-Chun Wei, and Hsun-Ping Hsieh. 2024. Estimating Future Financial Development of Urban Areas for Deploying Bank Branches: A Local-Regional Interpretable Model. ACM Trans. Manage. Inf. Syst. 15, 2, Article 8 (June 2024), 26 pages. https://doi.org/10.1145/3656479
Enhancing Robust Liver Cancer Diagnosis: A Contrastive Multi-Modality Learner with Lightweight Fusion and Effective Data Augmentation
Pei-Xuan Li, Hsun-Ping Hsieh, Yang Fan-Chiang, Ding-You Wu, and Ching-Chung Ko. 2024. Enhancing Robust Liver Cancer Diagnosis: A Contrastive Multi-Modality Learner with Lightweight Fusion and Effective Data Augmentation. ACM Trans. Comput. Healthcare 5, 2, Article 6 (April 2024), 13 pages. https://doi.org/10.1145/3639414
Exploring Feature Fusion from A Contrastive Multi-Modality Learner for Liver Cancer Diagnosis
Yang Fan Chiang, Pei-Xuan Li, Ding-You Wu, Hsun-Ping Hsieh, and Ching-Chung Ko. 2024. Exploring Feature Fusion from A Contrastive Multi-Modality Learner for Liver Cancer Diagnosis. In Proceedings of the 5th ACM International Conference on Multimedia in Asia (MMAsia '23). Association for Computing Machinery, New York, NY, USA, Article 14, 1–7. https://doi.org/10.1145/3595916.3626383
Forecasting Dengue Fever Risk in Regions without Sensors Using Multi-View Graph Fusion Recurrent Neural Network
Pei-Xuan Li and Hsun-Ping Hsieh. 2023. Forecasting Dengue Fever Risk in Regions without Sensors Using Multi-View Graph Fusion Recurrent Neural Network. In Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems (SIGSPATIAL '23). Association for Computing Machinery, New York, NY, USA, Article 86, 1–4. https://doi.org/10.1145/3589132.3625636
ParkFlow: Intelligent Dispersal for Mitigating Parking Shortages Using Multi-Granular Spatial-Temporal Analysis
Yang Fan Chiang, Chun-Wei Shen, Jhe-Wei Tsai, Pei-Xuan Li, Tzu-Chang Lee, and Hsun-Ping Hsieh. 2023. ParkFlow: Intelligent Dispersal for Mitigating Parking Shortages Using Multi-Granular Spatial-Temporal Analysis. In Proceedings of the 32nd ACM International Conference on Information and Knowledge Management (CIKM '23). Association for Computing Machinery, New York, NY, USA, 5036–5040. https://doi.org/10.1145/3583780.3614751
ExoFIA: Deep Exogenous Assistance in the Prediction of the Influence of Fake News with Social Media Explainability
Pei-Xuan Li, Yu-Yun Huang, Chris Shei, Hsun-Ping Hsieh*. (2023) “ExoFIA: Deep Exogenous Assistance in the Fake News Influence Predictor with Social Media Explanability.” Applied Sciences, 2023.
Awards
Service
Program Committee
- Full Paper Track, the 34th ACM International Conference on Information and Knowledge Management (2025)
External Reviewer
- Journal of Information Science and Engineering (2023)
Sub-Reviewer
- ACM SIGIR (2021, 2024, 2025)
- ACM KDD (2022-2024)
Student Volunteer
- Reception desk volunteer of the 31st ACM International Conference on Advances in Geographic Information Systems (SIGSPATIAL ‘23)
Teaching experience
Working experience
- 2021/09 – present: Research Assistant,
- Urban Science and Computing Lab, NCKU, Taiwan
- Advisor: Prof. Hsun-Ping Hsieh
- 2022/07 - 2022/08: Intern
- Smart Protect Network Team, Trend Micro, Taiwan
- 2019/06 –2022/06: Research Assistant
- Knowledge Discovery Lab, NCKU, Taiwan
- Advisor: Prof. Wei-Guang Teng
- 2020/07 - 2020/08: Intern
- C5E AI Team, AUO, Taiwan