Ali Tosyali

Ali Tosyali is an assistant professor in the Department of MIS, Marketing, and Analytics in the Saunders College of Business at RIT. Before joining RIT, he was an assistant professor in the Department of Accounting and MIS in the Alfred Lerner College of Business and Economics at the University of Delaware. Dr. Tosyali received his MS and PhD in industrial and systems engineering from Rutgers University.

Dr. Tosyali's research focuses on developing new methodologies for various data-driven problems. His research interests lie broadly at the intersection of information systems, network science, machine learning, and complex systems, driven by applications in financial services analytics, social network analysis, opinion mining and analysis, and business analytics.

RESEARCH INTERESTS

Method Area: Network Science, Machine Learning, Complex Systems, Optimization

Application Area: Business Analytics, Financial Services Analytics, Social Network Analysis, Opinion Mining and Analysis

Education

• Doctor of Philosophy (Ph.D.) Rutgers University (2013 — 2019)
• Master’s Degree Rutgers University-New Brunswick (2013 — 2016)
• Bachelor's degree Turkish National Defense University (2009 — 2013)

Companies

• Assistant Professor Rochester Institute of Technology (2021)
• Assistant Professor University of Delaware (2019 — 2021)
• Lecturer Rutgers Business School (2017 — 2019)
• Research/Teaching Assistant Rutgers University (2013 — 2019)

Journals and Articles:

• Yu, Y., Tosyali, A., Baek, J., & Jeong, M. (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.
• Tosyali, A., Choi, J., Kim, B., Lee, H., & Jeong, M. (2021). A dynamic graph-based approach to ranking firms for identifying key players using inter-firm transactions. Annals of Operations Research.
• Tosyali, A., Song, R., Guo, W., 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.
• Tosyali, A., Kim, J., Choi, J., Kang, Y., & Jeong, M. (2020). New node anomaly detection algorithm based on nonnegative matrix factorization for directed citation networks. Annals of Operations Research.
• Choi, J., Tosyali, A., Kim, B., Lee, H., & Jeong, M. (2019). A Novel Method for Identifying Competitors Using a Financial Transaction Network. IEEE Transactions on Engineering Management.
• Tosyali, A., Kim, J., Choi, J., & Jeong, M. (2019). Regularized asymmetric nonnegative matrix factorization for clustering in directed networks. Pattern Recognition Letters.
• Rodriguez, A., Tosyali, A., Kim, B., Choi, J., & Lee, J. (2016). Patent clustering and outlier ranking methodologies for attributed patent citation networks for technology opportunity discovery. IEEE Transactions on Engineering Management.
• Sevim, C., Ekiyor, A., & Tosyali, A. (2016). As a supply chain financing source, trade credit and bank credit relationship during financial crises from clustering point of view. International Business Research.

Proceedings:

• Tavakkol, B., & Tosyali, A. (2020). Density-based clustering validation of uncertain data objects.. Northeast Decision Sciences Institute Annual Meeting.
• Usta, M., & Tosyali, A. (2018). Characterization of Model-Based Uncertainties in Incompressible Turbulent Flows by Machine Learning. ASME International Mechanical Engineering Congress and Exposition.