I study artificial intelligence systems with a focus on cognition architectures and machine learning. Hands-on projects include building intelligent autonomous driving agents and applying machine learning in data analysis
My research focuses on the intersection of large language models (LLMs) with cognition architecture, machine learning in data science, and their profound implications for information systems and human-computer interaction. I am a dedicate member of IEEE and the Center for Socially Responsible Artificial Intelligence at Penn State, with extensive collaboration and guidance from researchers in the fields of artificial intelligence systems, engineering, information systems, human-computer interaction, and AI applications in education.
Wu.S., Ferreira, R., Ritter, F., Walter., L. (accepted)Comparing LLMs for Prompt-Enhanced ACT-R and Soar Model Development: A Case Study in Cognitive Simulation. Paper accepted by 38th Annual Association for the Advancement of Artificial Intelligence (AAAI) Conference on Artificial Intelligence Fall Symposium Series on Integrating Cognitive Architecture and Generative Models at Arlington, Virginia, USA
Wu.S., Bagherzadeh, A., Ritter, F., Tehranchi, F. (under publication, 2023) Long Road Ahead: Lessons Learned from the (soon to be) Longest Running Cognitive Model. Paper accepted by 21st International Conference on Cognitive Modeling (ICCM) at the University of Amsterdam, the Netherlands
Wu, W., Liu, C., Wu, S., Yuan, L., Ding, R., Zhou, F., Wu, Q. (under publication, 2023) Social Enhanced Explainable Recommendation With Knowledge Graph. IEEE Transactions on Knowledge and Data Engineering (TKDE)
Wu.S., Swanson, H., Sherin, B., Wilensky, U. (2022). Investigating student learning about disease spread and prevention in the context of agent-based computational modeling. Proceedings of the 16th International Conference of the Learning Sciences - ICLS 2022. (pp. 1245 - 1248). Hiroshima, Japan: International Society of the Learning Sciences
Kim. C., Puntambekar. S., Lee. E., Gnesdilow D., Dey, I., Cang, X., Wu, S., Passonneau, R. (2023) Understanding of a Law of Science and Its Relation to Science Writing with Automated Feedback. Proceedings of 17th International Conference of the Learning Sciences - ICLS 2023>
Wu.S.,Bagherzadeh, A., Ritter, F., Tehranchi, F. (2023, Sep) Cognition Models Bake-off: Lessons Learned from Creating Long-Running Cognitive Models. Poster and Lightening Talk in 16th International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction and Behavior Representation in Modeling and Simulation (SBP-BRiMs)
Wu.S., Bagherzadeh, A., Ritter, F., Tehranchi, F (2023, June). Long Road Ahead: Lessons Learned from the (soon to be) Longest Running Cognitive Model. Poster for the 2023 Graduate Women in Science National Conference, PA, USA
Wu.S.(2023, March). Student Learning in the Context of Agent-based Computational Modeling Microworlds. Lightening talk for the 2023 Symposium for Teaching and Learning with Technology to be held at Penn State University Park Campus
Northup. J., Wu. S. (2022, November). CSS Pitfalls for Screen Readers. Conference workshop presentation in 25th annual Accessing Higher Ground Accessible Media, Web and Technology Conference, Denver, Colorado
