Ali Tosyali Headshot

Ali Tosyali

Assistant Professor

Department of MIS, Marketing, and Analytics
Saunders College of Business

585-475-7051
Office Location

Ali Tosyali

Assistant Professor

Department of MIS, Marketing, and Analytics
Saunders College of Business

Bio

Ali Tosyali is an assistant professor of management information systems at the Rochester Institute of Technology. His research interests lie broadly at the intersection of network science, machine learning, and information systems, driven by applications in financial services analytics, social network analysis, healthcare analytics, digital platforms, and business analytics.

Select Scholarship

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)

Tutun, S., Tosyali, A., Sangrody, H., Khasawneh, M., Johnson, M., Albizri, A., & Harfouche, A. (2022). Artificial intelligence in energy industry: forecasting electricity consumption through cohort intelligence adaptive neural fuzzy inference system. Journal of Business Analytics, 1-18. 

Yu, Y., Tosyali, A., Baek, J., & Jeong, M. K. (2022). A Novel Similarity-Based Link Prediction Approach for Transaction Networks. IEEE Transactions on Engineering Management.

Tosyali, A., & Tavakkol, B. (2021). A node-based index for clustering validation of graph data. Annals of Operations Research, 1-25.

Tosyali, A., Choi, J., Kim, B., Lee, H., & Jeong, M. K. (2021). A dynamic graph-based approach to ranking firms for identifying key players using inter-firm transactions. Annals of Operations Research, 303(1), 5-27.

Tosyali, A., Song, R., Guo, W. G., Abolhassani, A., & Kalamdani, R. (2021). Data-Driven Gantry Health Monitoring and Process Status Identification Based on Texture Extraction. Journal of Computing and Information Science in Engineering, 21(1).

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. (2022). 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

MGIS-355
3 Credits
The course is intended to provide an integrative foundation in the field of business intelligence at both the operational and strategic levels. Students will experience a variety of contemporary tools to analyze complex business data and arrive at a rational solution. Topic such as data warehousing, visualization and data mining will be covered, along with other topics relevant to the field of business intelligence. The computer will be used extensively throughout the course.
MGIS-489
3 Credits
Advanced study of MIS topics reflecting contemporary issues and/or current technological advancements impacting the development, implementation and management of information systems in organizations. Seminar topics have ranged from new technological developments to management security issues in MIS systems. Topics for a specific semester will be announced prior to the course offering.
MGIS-650
3 Credits
This course serves as an introduction to data analysis including both descriptive and inferential statistical techniques. Contemporary data analytics and business intelligence tools will be explored through realistic problem assignments.

In the News

Featured Work