Projects per year
Personal profile
Personal profile
Chaoqun Wang received her PhD from the School of Data Science at the City University of Hong Kong in 2024. She holds both a bachelor's and a master's degree in management from Wuhan University, which she completed in 2017 and 2020 respectively. Her research interests include artificial intelligence, deep learning, explainable models, and time series analysis.
Office Hour：
- Wednesday 10am-12pm
- Thursday 10am-12pm
Office： D5003
Research interests
Artificial intelligence; Deep learning; Explainable model; Time series data
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Education/Academic qualification
PhD, Data Science, City University of Hong Kong
Award Date: 2 Oct 2024
Master, Management, Wuhan University
Award Date: 30 May 2020
Bachelor, Management, Wuhan University
Award Date: 30 Jun 2017
Research areas
- Time Series
- Explainable Model
- Deep Learning
Person Types
- Staff
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Collaborations and top research areas from the last five years
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Projects
- 1 Active
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Dynamic Credit Limit Optimization and Risk Assessment for E-commerce Consumers Using Multimodal Learning and Explainable Models
Wang, C. (PI)
1/07/25 → 30/06/28
Project: Internal Research Project
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A two-stage disentangled and balanced representation learning method for counterfactual regression
Wang, S., Huang, Y., Leung, C. H., Wang, C. & Wu, Q., 25 Mar 2026, In: Information Sciences. 730, 122886.Research output: Contribution to journal › Article › peer-review
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Demystifying deep credit models in e-commerce lending: An explainable approach to consumer creditworthiness
Wang, C., Li, Y., Wang, S. & Wu, Q., 15 Mar 2025, In: Knowledge-Based Systems. 312, 1 p., 113141.Research output: Contribution to journal › Article › peer-review
1 Citation (Scopus) -
The Causal Impact of Credit Lines on Spending Distributions
Li, Y., Leung, C. H., Sun, X., Wang, C., Huang, Y., Yan, X., Wu, Q., Wang, D. & Huang, Z., 25 Mar 2024, Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI-24 Technical Tracks 1). Wooldridge, M., Dy, J. & Natarajan, S. (eds.). 1 ed. Washington: AAAI press, Vol. 38. p. 180-187 8 p. (Proceedings of the AAAI Conference on Artificial Intelligence; vol. 38, no. 1).Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review
Open Access3 Citations (Scopus) -
DeLELSTM: Decomposition-based Linear Explainable LSTM to Capture Instantaneous and Long-term Effects in Time Series
Wang, C., Li, Y., Sun, X., Wu, Q., Wang, D. & Huang, Z., 1 Aug 2023, Proceedings of the 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023. Elkind, E. (ed.). International Joint Conferences on Artificial Intelligence Organization, Vol. 2023-August. p. 4299-4307 9 p. (IJCAI International Joint Conference on Artificial Intelligence; vol. 2023-August).Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review
Open Access5 Citations (Scopus) -
Forecasting carbon prices based on real-time decomposition and causal temporal convolutional networks
Li, D., Li, Y., Wang, C., Chen, M. & Wu, Q., 1 Feb 2023, In: Applied Energy. 331, 120452.Research output: Contribution to journal › Article › peer-review
79 Citations (Scopus)
Activities
- 1 Completed SURF Project
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Deep Learning Models for Handling Irregular Time Series
Wang, C. (Supervisor)
Jul 2025 → Aug 2025Activity: Supervision › Completed SURF Project