Ali Tosyali
Associate Professor, MIS
Ali Tosyali
Associate Professor, MIS
Bio
Ali Tosyali is an Associate Professor of Management Information Systems at the Saunders College of Business, Rochester Institute of Technology, where he has taught since 2021. Before joining RIT, he was an Assistant Professor of MIS at the University of Delaware. He holds a Ph.D. and an M.S. in Industrial and Systems Engineering from Rutgers University and a B.S. in Systems Engineering from the Turkish Military Academy in Ankara, Turkey. His research uses network science, artificial intelligence, and machine learning to address problems on digital platforms and in healthcare and cybersecurity, including detecting fake reviews, explainable AI for mental health screening, and cybersecurity risk and disclosure. His work has appeared in the Proceedings of the National Academy of Sciences, the Journal of Management Information Systems, IEEE Transactions on Engineering Management, and the Annals of Operations Research, among others. His study of fake-review buyers on Amazon was covered by The Wall Street Journal, Forbes, and WIRED, and was a finalist for the MSI Robert D. Buzzell Best Paper Award. At RIT he teaches data analytics, business intelligence, and generative AI for business.
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Tutun, S., Topuz, K., Tosyali, A., Bhattacherjee, A., & Li, G. (2024). Explainable artificial intelligence for mental disorder screening: A computational design science approach. Journal of Management Information Systems, 41(4), 958-981.
Xie, Y., Wang, T., Jeong, Y. S., Tosyali, A., & Jeong, M. K. (2024). True sparse PCA for reducing the number of essential sensors in virtual metrology. International Journal of Production Research, 62(6), 2142-2157.
He, S., Hollenbeck, B., Overgoor, G., Proserpio, D., & Tosyali, A. (2022). Detecting fake-review buyers using network structure: Direct evidence from Amazon. Proceedings of the National Academy of Sciences, 119(47), e2211932119.
Tosyali, A., Kim, J., Choi, J., Kang, Y., & Jeong, M. K. (2020). New node anomaly detection algorithm based on nonnegative matrix factorization for directed citation networks. Annals of Operations Research, 288(1), 457-474.
Choi, J., Tosyali, A., Kim, B., Lee, H. S., & Jeong, M. K. (2019). A novel method for identifying competitors using a financial transaction network. IEEE Transactions on Engineering Management, 69(4), 845-860.
Tosyali, A., Kim, J., Choi, J., & Jeong, M. K. (2019). Regularized asymmetric nonnegative matrix factorization for clustering in directed networks. Pattern Recognition Letters, 125, 750-757.
Rodriguez, A., Tosyali, A., Kim, B., Choi, J., Lee, J. M., Coh, B. Y., & Jeong, M. K. (2016). Patent clustering and outlier ranking methodologies for attributed patent citation networks for technology opportunity discovery. IEEE Transactions on Engineering Management, 63(4), 426-437.
Currently Teaching
In the News
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November 13, 2025
RIT researcher develops mental health equivalent of MRI
Across the country, millions struggle to find timely or affordable mental health support. This imbalance was an inspiration for Ali Tosyali, who researched a potential assistive technology that could help practitioners identify potential disorders in a faster and efficient manner.