Finding K-Most Influential Users in Social Networks for Information Diffusion Based on Network Structure and Different User Behavioral Patterns. - Maryam Shahsavari; Alireza Hashemi Golpayegani (ICEBE, 2017)

Recruiting the K-most influential prospective workers for crowdsourcing platforms. - Maryam Shahsavari; Alireza Hashemi Golpayegani; Morteza Saberi; Farookh Khadeer Hussain (Serv. Oriented Comput. Appl., 2018)

A lightweight and unsupervised approach for identifying risk events in news articles. - Maryam Shahsavari; Omar Khadeer Hussain; Morteza Saberi; Pankaj Sharma 001 (ICDM (Workshops), 2023)

Empowering Supply Chains Resilience: LLMs-Powered BN for Proactive Supply Chain Risk Identification. - Maryam Shahsavari; Omar Khadeer Hussain; Morteza Saberi; Pankaj Sharma 001 (D2R2, 2024)

Event Identification for Supply Chain Risk Management Through News Analysis by Using Large Language Models. - Maryam Shahsavari; Omar Khadeer Hussain; Morteza Saberi; Pankaj Sharma 001 (Rev. Socionetwork Strateg., 2024)

Modelling supply chain risk events by considering their contributing events: a systematic literature review. - Maryam Shahsavari; Omar Khadeer Hussain; Pankaj Sharma 001; Morteza Saberi (Enterp. Inf. Syst., 2025)