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 13:00-15:00
- Thursday 13:00-15:00
Office： D5003
Research interests
Artificial intelligence; Deep learning; Explainable model; Time series data
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
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):
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SDG 7 Affordable and Clean Energy -
SDG 13 Climate Action
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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
1 Citation (Scopus) -
DAED: Dynamic Additive Effect Decomposition for Interpretable Time Series Forecasting
Wang, C., Sun, X., Wang, J., Ren, G. & Hua, Z., 2026, Database Systems for Advanced Applications - 31st International Conference, DASFAA 2026, Proceedings. Jung, H., Wang, T., Toyoda, M., Kwon, H.-Y. & Lee, J.-W. (eds.). Springer Science and Business Media Deutschland GmbH, p. 330-340 11 p. (Lecture Notes in Computer Science; vol. 16537 LNCS).Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review
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DAED: Dynamic Additive Effect Decomposition for Interpretable Time Series Forecasting
Wang, C., Sun, X., Wang, J., Ren, G. & Hua, Z., 2026, International Conference on Database Systems for Advanced Applications. p. 330-340 11 p.Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review
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Heterogeneous biological graph convolutional network for drug-target interaction prediction
Zhu, H., Wang, J., Hua, Z., Wang, C., Zhang, Z., Yu, T. & Ge, L., May 2026, In: PLoS ONE. 21, 5 May, e0348895.Research output: Contribution to journal › Article › peer-review
Open Access -
Perturbed Dynamic Time Warping: A Probabilistic Framework and Generalized Variants
Sun, X., Wang, C. & Zhang, W., 2026, (Accepted/In press) The Fourteenth International Conference on Learning Representations (ICLR 2026).Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review
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