Rongen "Sophia" Zhang

Professional Summary

Sophia Zhang is an Assistant Professor of Business Analytics in the Department of Information Systems and Business Analytics at Baylor University. A first-generation college graduate, she is grateful for the opportunity to pursue her calling as an educator and researcher. She earned her PhD in Computer Information Systems from Georgia State University.

Her research examines how emerging technologies shape individual decision-making, with a focus on decentralized governance, AI explainability, generative AI delegation, and technology-mediated user engagement. Her work has been published in leading outlets such as Information Systems Journal, Journal of Medical Internet Research, ACM Transactions on Management Information Systems, and Frontiers in Neuroscience, and has been presented at major international conferences including the International Conference on Information Systems (ICIS), the Hawaii International Conference on System Sciences (HICSS), the Institute for Operations Research and the Management Sciences Annual Meeting (INFORMS), and the Conference on Information Systems and Technology (CIST). She has been recognized with the Best Associate Editor and Best Reviewer awards at the International Conference on Information Systems (ICIS).

Education

• 2022 – PhD, Computer Information Systems, Georgia State University, Atlanta, Georgia
• 2018 – BA, Information Systems and Information Management, Harbin Institute of Technology, Harbin, China

Courses

• MIS 4344 - Business Intelligence
• MIS 5342 - Business Intelligence

Research Interests

• Decentralized Governance
• Explainable AI and Decision-Making
• Generative AI Delegation
• Technology-mediated User Engagement
• Configurational perspectives (QCA)

Selected Publications

• Zhang, R., Park, E., Kim, Y., & Kim, J. (2025). Uncovering the associations of research paradigms and methods with theoretical contribution types. Communications of the Association for Information Systems, 57, 1189–1216.
• Zhang, R. S., & Ramesh, B. (2023). A configurational perspective on design elements and user governance engagement in blockchain platforms. Information Systems Journal.
• Ellis, C., Sendi, M., Zhang, R., Carbajal, D., Wang, D., Miller, R., & Calhoun, V. (2023). Novel methods for elucidating modality importance in multimodal electrophysiology classifier. Frontiers in Neuroinformatics.
• Werder, K., Ramesh, B., & Zhang, R. (2022). Establishing data provenance for responsible artificial intelligence systems. ACM Transactions on Management Information Systems (TMIS), 13(2), 1–23.
• Zhang, R., George, A., Kim, J., Johnson, V., & Ramesh, B. (2019). Benefits of blockchain initiatives for value-based care: Proposed framework. Journal of Medical Internet Research, 21(9), e13595.