2024-2027 国家自然科学基金，面上项目，混合驱动下智能可视化方法与技术研究（项目负责人）

2025-2026 校企合作项目，阿里巴巴，基于大模型的交互生成研究（项目联合负责人）

2023-2026 上海市自然科学基金，面上项目，面向数据智能的信息传达设计（项目负责人）

2022-2024 校企合作项目，腾讯-OUTPUT，科技树项目（项目负责人）

2022-2023 教育部高等教育司产学合作协同育人项目，数据可视化系列示范课程建设项目（项目负责人）

2022-2023 校企合作项目，蚂蚁集团，商业智能应用中的自助分析系统设计（项目联合负责人）

2021-2023 国家自然科学基金，青年项目，基于在线学习行为数据辅助自我调节式学习的可视分析研究（项目负责人）

2021-2023 国家自然科学基金，面上项目，信息可视化自动生成技术的研究 （项目骨干）

2021-2023 国际(地区)合作与交流项目，针对复杂事件序列数据的可视分析研究（项目骨干）

2020-2021 校企合作项目，蚂蚁集团，基于人工智能的自动可视化生成研究（项目负责人）

2018-2020 医疗路径大数据的大数据展示（法国社会保障局合作项目）Dynamic representation of large volumes of care pathways (collaboration with France government CNAMS) （项目负责人）

2018-2020 针对电子学习的学习设计，数据分析和可视化的开放性框架二期An Open Learning Design, Data Analytics and Visualization Framework for E-Learning ITS/388/17FP

2016-2018 针对电子学习的学习设计，数据分析和可视化的开放性框架An Open Learning Design, Data Analytics and Visualization Framework for E-Learning ITS/306/15FP （第二负责人）

2014-2018 慕课数据可视化分析工具VisMOOC: A Visualization Tool for MOOC F0532-CSE03 HKUST （第二负责人）

2014-2017 用户忠诚度可视分析Visual Analysis of Customer Loyalty RGC/GRF16208514 

[1] Chen, Q., Chen, Y., Zou R., Shuai, W., Guo Y., Wang J., & Cao, N. (2025). Chart2Vec: A Universal Embedding of Context-Aware Visualizations. IEEE Transactions on Visualization and Computer Graphics, 31(4), 2167-2181.

[2] Chen, Q., Shuai, W., Zhang, J., Sun, Z., & Cao, N. (2024). Beyond Numbers: Creating Analogies to Enhance Data Comprehension and Communication with Generative AI. In Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems.

[3] Guo, Y., Shi, D., Guo, M., Wu, Y., Cao, N. * & Chen, Q. * (2024). Talk2Data: A Natural Language Interface for Exploratory Visual Analysis via Question Decomposition. ACM Transactions on Interactive Intelligent Systems.

[4] Chen, Q., Chen, N., Shuai, W., Wu, G., Xu, Z., Tong, H., & Cao, N. (2024). Calliope-Net: Automatic Generation of Graph Data Facts via Annotated Node-link Diagrams. IEEE Transactions on Visualization and Computer Graphics, 30(1), 562-572. 

[5] Chen, Q., Cao, S., Wang, J., & Cao, N. (2024). How Does Automation Shape the Process of Narrative Visualization: A Survey of Tools. IEEE Transactions on Visualization and Computer Graphics, 30(8), 4429 - 4448.

[6] Guo, Y., Cao N.*, Cai L., Wu Y., Weiskopf D., Shi D., Chen.Q.* Datamator: An Authoring Tool for Creating Datamations via Data Query Decomposition. Applied Sciences 2023.

[7] Guo, Y., Cao, N., Qi X., Li, H., Shi, D., Zhang J., Chen Q., Daniel Weiskopf. (2023). Enhancing Natural Language-Based Data Exploration with Analysis Pipeline Illustration. IEEE VIS.

[8] Li, Y., Qi, Y., Shi, Y., Chen, Q., Cao, N., & Chen, S. (2022). Diverse Interaction Recommendation for Public Users Exploring Multi-view Visualization using Deep Learning. IEEE Transactions on Visualization and Computer Graphics, 29(1), 95-105.

[9] Lan, X., Wu, Y., Shi, Y., Chen, Q., & Cao, N. (2022, April). Negative emotions, positive outcomes? exploring the communication of negativity in serious data stories. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (pp. 1-14).

[10] Chen, Q., Sun, F., Xu, X., Chen, Z., Wang, J., & Cao, N. (2022). Vizlinter: A linter and fixer framework for data visualization. IEEE transactions on visualization and computer graphics, 28(1), 206-216.

[11] Guo, S., Jin, Z., Chen, Q., Gotz, D., Zha, H., & Cao, N. (2021). Interpretable anomaly detection in event sequences via sequence matching and visual comparison. IEEE Transactions on Visualization and Computer Graphics, 28(12), 4531-4545.

[12] Chen, Q., Yue, X., Plantaz, X., Chen, Y., Shi, C., Pong, T. C., & Qu, H. (2020). ViSeq: Visual Analytics of Learning Sequence in Massive Open Online Courses. IEEE transactions on visualization and computer graphics. 26 (3), 1622-1636.

[13] Qu, H., Shi, C., Fu, S., & Chen, Q. (2020). Method and system for analyzing user activities related to a video. U.S. Patent No. 10,616,626. Washington, DC: U.S. Patent and Trademark Office.

[14] Guo, S., Jin, Z., Chen, Q., Gotz. D., Zha. H., Cao. N. (2019, December). Visual Anomaly Detection in Event Sequence Data. IEEE BigData 2019.

[15] Fekete, J. D., Chen, Q., Feng, Y., & Renault, J. (2019, October). Practical Use Cases for Progressive Visual Analytics. IEEE VIS DISA 2019.

[16] Chen, Q., Li, Z., Pong, T. C., & Qu, H. (2019, April). Designing Narrative Slideshows for Learning Analytics. In 2019 IEEE Pacific Visualization Symposium (PacificVis) (pp. 237-246). IEEE.

[17] Mu, X., Xu, K., Chen, Q., Du, F., Wang, Y., & Qu, H. (2019). MOOCad: Visual Analysis of Anomalous Learning Activities in Massive Open Online Courses. IEEE EuroVis 2019.

[18] Xia, M., Sun, M., Wei, H., Chen, Q., Wang, Y., Shi, L., ... & Ma, X. (2019, April). PeerLens: Peer-inspired Interactive Learning Path Planning in Online Question Pool. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (p. 634). ACM.

[19] Chen, Y., Chen, Q., Zhao, M., Boyer, S., Veeramachaneni, K., & Qu, H. (2016, October). DropoutSeer: Visualizing learning patterns in Massive Open Online Courses for dropout reasoning and prediction. In 2016 IEEE Conference on Visual Analytics Science and Technology (VAST) (pp. 111-120). IEEE.

[20] Chen, Q., Chen, Y., Liu, D., Shi, C., Wu, Y., & Qu, H. (2016). Peakvizor: Visual analytics of peaks in video clickstreams from massive open online courses. IEEE transactions on visualization and computer graphics, 22(10), 2315-2330.

[21] Qu, H., & Chen, Q. (2015). Visual analytics for MOOC data. IEEE computer graphics and applications, 35(6), 69-75.

[22] Shi, C., Fu, S., Chen, Q., & Qu, H. (2015, April). VisMOOC: Visualizing video clickstream data from massive open online courses. In 2015 IEEE Pacific visualization symposium (PacificVis) (pp. 159-166). IEEE.

招收交叉学科背景的本科实习生、硕士及博士研究生，欢迎对科研方向感兴趣的同学发简历至邮箱：qingchen@tongji.edu.cn

面向不限于设计类、心理学、信息科学、认知科学、计算机、人工智能、自动化、软件工程、数学与统计学、物理学、材料科学、教育学、神经科学、医学与生命科学等专业及交叉学科背景，对科研有热情且具有较强的自我驱动力的同学~