Ali Tosyali

Assistant Professor of Management Information Systems
Rochester Institute of Technology

I am an assistant professor of management information systems at the Rochester Institute of Technology. My research interests lie broadly at the intersection of network science, machine learning, and complex systems, driven by applications in financial services analytics, social network analysis, opinion mining and analysis, digital platforms, and business analytics.

In my spare time, I enjoy riding my motorcycle, coding, playing baglama (a folkloric instrument), sports, and woodworking.

See my CV.

Publications

Detecting Fake Review Buyers Using Network Structure: Direct Evidence from Amazon [paper, code]
  • with Sherry He, Brett Hollenbeck, Gijs Overgoor, and Davide Proserpio
  • Proceedings of the National Academy of Sciences (2022)
  • Media Coverage: WSJ, Wired, UCLA Anderson Review
Artificial intelligence in energy industry: forecasting electricity consumption through cohort intelligence & adaptive neural fuzzy inference system.
  • with Salih Tutun, Hossein Sangrody, Mohammad Khasawneh, Marina Johnson, Abdullah Albizri, Antoine Harfouche
  • Journal of Business Analytics (2022)
A novel similarity-based link prediction approach for transaction networks.
  • with Yi Yu, Jaeseung Baek, and Myong K. Jeong
  • IEEE Transactions on Engineering Management (2022)
A node-based index for clustering validation of graph data.
  • with Behnam Tavakkol
  • Annals of Operations Research (2021)
A dynamic graph-based approach to ranking firms for identifying key players using inter-firm transactions.
  • with Jeongsub Choi, Byunghoon Kim, Hoshin Lee, and Myong K. Jeong
  • Annals of Operations Research (2021)
Data-driven gantry health monitoring and process status identification based on texture extraction.
  • with Rui Song, Weihong Grace Guo, Amir Abolhassani, and Rajeev Kalamdani
  • Journal of Computing and Information Science in Engineering (2021)
New node anomaly detection algorithm based on nonnegative matrix factorization for directed citation networks.
  • with Jinho Kim, Jeongsub Choi, Yunyi Kang, and Myong K Jeong
  • Annals of Operations Research (2020)
A novel method for identifying competitors using a financial transaction network.
  • with Jeongsub Choi, Byunghoon Kim, Ho-shin Lee, and Myong K Jeong
  • IEEE Transactions on Engineering Management (2019)
Regularized asymmetric nonnegative matrix factorization for clustering in directed networks.
  • with Jinho Kim, Jeongsub Choi, and Myong K Jeong
  • Pattern Recognition Letters (2019)
Patent clustering and outlier ranking methodologies for attributed patent citation networks for technology opportunity discovery.
  • Andrew Rodriguez, Byunghoon Kim, Jeongsub Choi, Jae-Min Lee, Byoung-Youl Coh, and Myong K Jeong
  • IEEE Transactions on Engineering Management (2016)
As a supply chain financing source, trade credit and bank credit relationship during financial crises from clustering point of view.
  • with Cuneyt Sevim and Aykut Ekiyor
  • International Business Research (2016)

Working Papers

Robust Asymmetric Nonnegative Matrix Factorization for Clustering in Directed Networks
  • with Yi Yu, Jaeseung Baek, and Myong K. Jeong
Human-Centered Explainable AI Framework for Identifying Mental Disorders
  • with Salih Tutun, Kazim Topuz, Anol Bhattacherjee, and Gordon Li
Local Influential User Identification in Online Social Networks
  • with Salih Tutun and Behnam Tavakkol
True Sparse PCA for Reducing the Number of Essential Sensors in Virtual Metrology
  • with Yifan Xie, Tianhui Wang, Young-Seon Jeong, and Myong K. Jeong