199609-200106  中国  中国科学技术大学  科技英语  理学士

199609-200106  中国  中国科学技术大学  计算机科学  工学士

200109-200406  中国  中国科学技术大学  计算机科学  硕士

200509-200706  美国  伊利诺伊大学香槟分校 (University of Illinois, at Urbana-Champaign)  传播学  硕士

200709-201208  美国  西北大学 (Northwestern University)  工业工程与管理  博士

计算社会学，大数据分析，社会网络分析，计算传播学，数据挖掘与人工智能，个性化学习与学习分析，计算机化评测 ,  科学教育与智能反馈

                                                     

201209-201306  美国  罗格斯大学 (Rutgers University)  博士后研究员 (Postdoctoral Research   Associate)

201307-201602  美国  美国教育考试中心 (Educational Testing Service)  副研究员 (Associate Research   Scientist)

201603-202011  美国  美国教育考试中心 (Educational Testing Service)  研究员 (Research Scientist)

202012- 至今  中国  中国科学技术大学  特任研究员

主持

国家自然科学基金委面上项目：基于过程性数据的在线合作解决问题能力建模分析与个性化干预机制研究（ 47 万， 2022-2025 ）

中科大第三批 “ 学术领军人才培养计划 ” A  档：基于大数据的传播行为与融媒体刻画研究（ 100 万， 2022-2024 ）

中科院人才计划青年项目：计算社会科学视角下的合作与人机交互（ 800 万， 2022-2025 ）

中科大引进人才科研启动项目：计算社会学与计算传播学的研究方法与应用（ 100 万， 2021-2023 ）


参与

科技部国家重点研发项目：面向终身学习的个性化 “ 数字教师 ” 智能体技术研究与应用（ 4940 万，项目骨干，子课题负责人， 2021-2024 ）

科技部国家重点研发项目：主流价值观内容认知与精准传播建模理论及系统平台（ 2000 万，项目骨干，子课题负责人， 2021-2024 ）

1.	Li, J., Wang, F., Liu, Q., Zhu, M., Huang, W., Huang, Z., Chen, E., Su, Y., & Wang, S. (2022). HierCDF: A Bayesian Network-based Hierarchical Cognitive Diagnosis Framework. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 904–913. https://doi.org/10.1145/3534678.3539486
2.	Chen, Z., Shen, J., Zhu, M., Hu, B., & Liu, A. (2022). Predicting Virtual Gifting Behaviors in Live Streaming Using Danmaku Information. Proceedings of the 8th International Conference on Big Data Computing and Communications (BigCom 2022).
3.	Zhu, M. (2021). Social Networks Analysis. In A. A. von Davier, B. Mislevy, & J. Hao (Eds.), Computational Psychometrics: New Methods for a New Generation of Educational Assessment (pp. 231–244). Springer. https://doi.org/https://doi.org/10.1007/978-3-030-74394-9_13
4.	Zhu, M., Liu, O. L., & Lee, H.-S. (2020). Using cluster analysis to explore students’ interactions with automated feedback in an online earth science task. The International Journal of Quantitative Research in Education, 5(2), 111-135.
5.	Zhu, M., Andrews-Todd, J., & Zhang, M. (2020). Application of Network Analysis in Understanding Collaborative Problem Solving Processes and Skills. In H. Jiao & R. W. Lissitz (Eds.), Innovative Psychometric Modeling and Methods (pp. 69–89). Charlotte, NC: Information Age Publisher.
6.	Zhu, M., Liu, O. L., & Lee, H.-S. (2020). The effect of automated feedback on revision behavior and learning gains in formative assessment of scientific argument writing. Computers & Education, 143, 103668. https://doi.org/10.1016/j.compedu.2019.103668
7.	Zhu, M., & Todd, J. A. (2019). Understanding the Connections of Collaborative Problem Solving Skills in a Simulation-based Task through Network Analysis. In The Proceedings of the International Conference on Computer Supported Collaborative Learning (CSCL 2019). Lyon, France.
8.	Zhu, M., Zhang, M., & Deane, P. (2019). Analysis of Keystroke Sequences in Writing Logs. ETS Research Report Series (RR-19-11).
9.	Zhang, M., Zhu, M., Deane, P., & Guo, H. (2019). Identifying and Comparing Writing Process Patterns Using Keystroke Logs. In Quantitative Psychology: The 83nd Annual Meeting of the Psychometric Society, New York. New York: Springer.
10.	Zhu, M., & Zhang, M. (2017). Network analysis of conversation data for engineering professional skills assessment. ETS Research Report Series (RR-17-59).
11.	Shu, Z., Bergner, Y., Zhu, M., & Hao, J. (2017). An item response theory analysis of problem-solving processes in scenario-based tasks. Psychological Test and Assessment Modeling, 59(1), 109–131.
12.	Zhu, M., Lee, H.-S., Wang, T., Liu, O. L., Belur, V., & Pallant, A. (2017). Investigating the impact of automated feedback on students’ scientific argumentation. International Journal of Science Education, 39(12), 1648–1668. 
13.	Zhu, M., & Bergner, Y. (2017). Network Models for Teams with Overlapping Membership. In A. A. von Davier, M. Zhu, & P. Kyllonen (Eds.), Innovative Assessment of Collaboration. Springer.
14.	Zhu, M., Liu, O. L., Mao, L., & Pallant, A. (2016). Use of Automated Scoring and Feedback in Online Interactive Earth Science Tasks. In Proceedings of the 2016 IEEE Integrated STEM Education Conference. Princeton, NJ.
15.	Zhu, M., & Zhang, M. (2016). Examining the patterns of communication and connections among engineering professional skills in group discussion: A network analysis approach. In Proceedings of the 2016 IEEE Integrated STEM Education Conference. Princeton, NJ.
16.	Zhu, M., Shu, Z., & von Davier, A. A. (2016). Using networks to visualize and analyze process data for educational assessment. Journal of Educational Measurement, 53(2), 190–211.
17.	Bergner, Y., Andrews, J. J., Zhu, M., & Gonzales, J. E. (2016). Agent-based modeling of collaborative problem solving. ETS Research Report Series (RR-16-27). Princeton, NJ. 
18.	Zhu, M., Kuskova, V., Wasserman, S., & Contractor, N. (2016). Correspondence Analysis of Multirelational Multilevel Network Affiliations: Analysis and Examples. In E. Lazega & T. Snijders (Eds.), Multilevel Network Analysis for the Social Sciences - Theory, Methods and Applications. Springer. 145–172.
19.	Zhu, M., Bergner, Y., Zhang, Y., Baker, R., Wang, Y., Paquette, L., & Barnes, T. (2016). Longitudinal Engagement, Performance, and Social Connectivity : a MOOC Case Study Using Exponential Random Graph Models. In Proceeding of the 6th International Learning Analytics and Knowledge Conference (LAK ’16). Edinburgh, UK:ACM.
20.	Zhu, M., & Feng, G. (2015). An exploratory study using social network analysis to model eye movements in mathematics problem solving. In Proceeding of the 5th International Learning Analytics and Knowledge Conference (LAK ’15). Poughkeepsie, NY: ACM. 
21.	Zhu, M., Huang, Y., & Contractor, N. S. (2013). Motivations for self-assembling into project teams. Social Networks, 35(2), 251-264.
22.	Huang, Y., Zhu, M., Wang, J., Pathak, N., Shen, C., Keegan, B., & Contractor, N. (2009, August 29-31). The formation of task-oriented groups: Exploring combat activities in online games. The 2009 IEEE International Conference on Social Computing (SociaICom-09), Vancouver, Canada.