Ph.D. Candidate

Pennsylvania State University

Hi there! I’m a Ph.D. candidate in Informatics at the Pennsylvania State University, advised by Dr. John Carroll.

Research Interests:

I'm interested in the human-centered design for data & AI empowered educational technologies. With a combination of data science and user research methods, I investigate the process of designing and designing innovative technologies for educational purposes, and how to properly integrate human perspectives in the process.

Education

PhD in Informatics

Pennsylvania State University
MSc in Industrial Engineering, 2019

Purdue University
BSc in Engineering Management, 2017

Beijing Jiaotong University

Research experience

Graduate Researcher

Teaching & Learning with Technology

Aug 2022 – Present Penn State

Our mission is to innovate with technologies that transform teaching and learning in positive and enduring ways. I empower technology development and strategic decision-making through data science.

UX Researcher

Naver Labs Europe

Jan 2022 – Aug 2022 Remote collaboration

Lead usability studies to evaluate their codeless app development system. Conducted thorough benchmarking analyses of the product’s usability, summarizing user feedback and expert reviews to identify opportunities for improvement.

PhD Student

Collaboration and Innovation Lab

Sep 2020 – Present Penn State

I lead multiple research projects to address societal problems in technology advancement. Synthesize literature, propose hypotheses, develop research plans, execute quantitative & qualitative studies, and report core findings to relevant communities.

Research Associate

MEERCat

Sep 2019 – Aug 2020 Purdue

Our mission is to enable the holistic transformation of STEM education by bridging research & practice. I conducted quantitative and qualitative research for several projects.

Master student

Health Ergonomics Analytics Lab

Aug 2017 – Aug 2019 Purdue

My research investigated the data-driven cognitive modeling in healthcare. I proposed and validated machine learning assessment for robotic surgery training, based on eye-tracking and EEG signals.

Publications

Wu, C., Pérez-Álvarez, J. M., & Mos, A., & Carroll, J. M., (2023). Codeless App Development: Evaluating A Cloud-Native Domain-Specific Functions Approach. Proceedings of the 56th Hawaii International Conference on System Sciences.. (link)

Wu, C., Wang, Proctor, R. W., T., Li, Ning., Blocki, J., & Xiong, A. (2021). Communicating Differential Privacy Models by Illustrations: A Survey and In-Depth Interview Study. Proceedings of the 65d Human Factors and Ergonomics Society Annual Meeting. (link)

Wu, C., Berger, E., DeBoer, J., & Rhoads, J. F. (2021). Use of worked-example videos to support problem solving: An analysis of student behavior. Computer Applications in Engineering Education. (link)

Berger, E. J, Wu, C., Briody, E. K., Wirtz, E.,Rodríguez-Mejía, F.(2020). Faculty subcultures in engineering and their implications for organizational change. Journal of Engineering Education. (link)

Wu, C., Cha, J., Sulek, J., Sundaram, C. P., Wachs, J., Proctor, R. W., & Yu, D. (2020). Sensor-based indicators of performance changes between sessions during robotic surgery training. Applied Ergonomics. (link)

Wu, C., Cha, J. S., Sulek, J., Zhou, Z., Sundaram, C. P., Wachs, J. P., Yu, D. (2019). Eye-tracking Metrics Predicts Mental Workload in Robotic Surgical Skills Training. Human Factors. (link)

Wu, C., Cha, J. S., Sulek, J., Zhou, Z., Sundaram, C. P., Wachs, J. P., Yu, D. (2019). Analysis of Eye Behavior: Mental Workload Assessment in Robotic Surgery . Proceedings of the 63rd Human Factors and Ergonomics Society Annual Meeting. (link)

Huang, G., Liang, N., Wu, C., Pitts, B. (2019). The Impact of Mind Wandering on Signal Detection, Semi-autonomous Driving Performance, and Physiological Responses. Proceedings of the 63rd Human Factors and Ergonomics Society Annual Meeting. (link)

Briody, E. K., Rodríguez-Mejía, F., Rothstein, R., Wu, C., Berger, E. J.(2019). Busy Times, Productive Students: Cutoff Points Marking Time in University Engineering Culture. Proceedings of the 8th Research in Engineering Education Symposium. (link)