Dr. Chunyang Wang is currently an Assistant Professor (Chenhui Scholar) at the School of Data Science and Engineering, East China Normal University (ECNU). He received his Ph.D. in Computer Science and Technology from Shanghai Jiao Tong University (SJTU) in 2024, under the supervision of Prof. Yanmin Zhu, and was a visiting Ph.D. student at Nanyang Technological University (NTU Singapore) in 2022–2023, under the the supervision of Prof. Aixin Sun. He received his B.Eng from the Faculty of Computing, Harbin Institute of Technology (HIT).
My research interests focuses on Congitive Computing on Recommendtion Systems, Educational Data Mining and Language Education Technology, within online platforms in social, e-commerce and educational domains.
Looking for highly self-motivated students【Master & Undergraduate】. Contact me cywang@dase.ecnu.edu.cn.
Looking for highly self-motivated students【Master & Undergraduate】. Contact me cywang@dase.ecnu.edu.cn.
Recommendation Algorithms & Systems
- Sequential Recommendation
- Cold-start Recommendation
- Multi-domain Recommendation
Educational Data Mining & Generation
- Personalized Learning Analysis
- Learning Path Generation
- Educational Recommendation
Language Education Technology
- Multi-modality Generation
- Scenario-driven Simulation
- Shuishan Chinese Platform
🔥 News
- 2026.01: 📝 One paper accepted to ACM TKDD 2026!
- 2025.11: 📝 One paper accepted to AAAI 2026!
- 2025.11: 📝 One paper accepted to ACM WSDM 2026!
- 2025.08: 📝 One paper accepted to ACM CIKM 2025!
- 2025.06: 📝 One paper accepted to Neurocomputing 2025!
- 2025.03: 📝 One paper accepted to IEEE TMC 2025!
- 2025.01: 📝 One paper accepted to ACM TOIS 2025!
- 2024.11: 📝 One paper accepted to IEEE TKDE 2024!
- 2024.07: 🎉 Started position as Assistant Professor (Chenhui Scholar) at DaSE ECNU!
- 2024.06: 🎓 Successfully defended Ph.D. thesis at SJTU!
📝 Publications
Total Publications: 27 |
Citations: 640+ |
h-index: 13
📅 2026
4 papers
MESA: Plugin Meta-Modulation for Transformer-based Cold-start Sequential Recommendation
Adaptive Continual Learning with User-Incremental Forward Compatibility for Meta-Augmented Cold-Start Recommenders
EdGCL: Disentangling Social and Cognitive Homophily in Graph-Based Educational Recommender Systems
📅 2025
4 papers
Dual-Adaptive Update Strategies-Enhanced Meta-Optimization for User Cold-Start Recommendation
Multi-Agent Deep Reinforcement Learning With Trajectory Prediction for Task Migration-Assisted Computation Offloading
Dynamic Integration of Preference and Knowledge Status for Knowledge Concept Recommendation
Exploring the Tradeoff Between Diversity and Discrimination for Continuous Category Discovery
📅 2024
3 papers
Graph Diffusion-based Representation Learning for Sequential Recommendation
Review Enhanced Hierarchical Contrastive Learning for Recommendation
Guiding Graph Learning with Denoised Modality for Multi-modal Recommendation
📅 2023
9 papers
A Preference Learning Decoupling Framework for User Cold-Start Recommendation
Multifaceted Relation-aware Meta-learning with Dual Customization for User Cold-start Recommendation
Contrastive Multi-view Interest Learning for Cross-Domain Sequential Recommendation
Multi-aspect Graph Contrastive Learning for Review-Enhanced Recommendation
Learning Shared Representations for Recommendation with Dynamic Heterogeneous Graph Convolutional Networks
Learning Aspect-aware High-order Representations from Ratings and Reviews for Recommendation
Task-difficulty-aware Meta-learning with Adaptive Update Strategies for User Cold-start Recommendation
Adaptive Graph Representation Learning for Next POI Recommendation
Disentangled Contrastive Learning for Cross-Domain Recommendation
📅 2022
5 papers
Learning Graph-based Disentangled Representations for Next POI Recommendation
Graph-enhanced Spatial-temporal Network for Next POI Recommendation
Incorporating Heterogeneous User Behaviors and Social Influences for Predictive Analysis
Inter-and Intra-domain Relation-aware Heterogeneous Graph Convolutional Networks for Cross-Domain Recommendation
Deep Meta-learning in Recommendation Systems: A Survey
📅 2021
2 papers
Enhancing User Interest Modeling with Knowledge-enriched Itemsets for Sequential Recommendation
Modeling Inter-station Relationships with Attentive Temporal Graph Convolutional Network for Air Quality Prediction
📖 Education
- 2019.09 - 2024.06, Ph.D. in Computer Science
- Shanghai Jiao Tong University (SJTU), Shanghai, China
- Supervisor: Prof. Yanmin Zhu
- 2022.09 - 2023.08, Visiting Ph.D. Student
- Nanyang Technological University (NTU), Singapore
- Supervisor: Prof. Aixin Sun
- 2015.09 - 2019.06, B.Eng. in Computer Science
- Harbin Institute of Technology (HIT), Harbin, China
💬 Academic Services
Program Committee Member / Reviewer
- ACM SIGIR (2022, 2023, 2024, 2025)
- ACM KDD (2023, 2024, 2025)
- ACM CIKM (2023, 2024, 2025)
- AAAI (2023, 2024, 2025)
Journal Reviewer
- IEEE Transactions on Knowledge and Data Engineering (TKDE)
- ACM Transactions on Information Systems (TOIS)
- ACM Transactions on Knowledge Discovery from Data (TKDD)
- IEEE Transactions on Mobile Computing (TMC)
- IEEE Transactions on Neural Networks and Learning Systems（TNNLS）
🎓 Teaching
Undergraduate Courses
- Computer Vision and Multimedia Information Processing (Fall 2024, Fall 2025)
- Computer Networks (Fall 2024, Fall 2025)
- Social Computing (Spring 2025)
Graduate Courses
- Computer Vision and Multimedia Information Processing (Fall 2024, Fall 2025)
- Computational Pedagogy (Spring 2025)
🎤 Invited Talks
- 2025.10, Shuishan Chinese: AI for Chinese Language Teaching and Learning, ICTC 2025, New York, USA
- 2025.08, AI for Chinese Language Teaching and Learning, The 12th Summer School of DaSE, ECNU, Shanghai