Morteza Saberi

Lecturer

University of Sydney

Australia

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About

Dr. Morteza Saberi is a Lecturer at the University of Technology Sydney, Australia. His research interests primarily encompass supply chain risk management, application of machine learning in decision support frameworks, and the development of advanced chatbot technologies. He has published several articles on topics such as data-driven decision support systems and the use of large language models for various applications.

Articles (19)

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2025

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2023

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2022

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2022

Collaborators (8)

Daniel Prior

University of New South Wales

AUSTRALIA

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Ripon Chakrabortty

Lecturer

University of Canberra

AUSTRALIA

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Omar Hussain

Associate Professor

University of New South Wales Canberra at ADFA

AUSTRALIA

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Farookh Hussain

University of Sydney

AUSTRALIA

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Maxwell Chipulu

University of Southampton

UNITED KINGDOM

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Ofer Zwikael

Professor of Project Management

Australian National University

AUSTRALIA

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Mehdi Rajabi Asadabadi

Lecturer in Project Management

University of Sydney

AUSTRALIA

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Mohsen Abbaspour Onari

Eindhoven University of Technology

NETHERLANDS

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Morteza Saberi

Research Interests

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About

Articles (19)

Generative Indonesian chatbot for university major selection using transformers embedding

Advances in impact force identification: A comprehensive review of techniques and mathematical innovations

Modelling supply chain risk events by considering their contributing events: a systematic literature review

Adaptive identification of supply chain disruptions through reinforcement learning

An explainable data-driven decision support framework for strategic customer development

A data-driven decision support framework for DEA target setting: an explainable AI approach

3D scene generation for zero-shot learning using ChatGPT guided language prompts

Event Identification for Supply Chain Risk Management Through News Analysis by Using Large Language Models

Enhancing the analysis of online product reviews to support product improvement: integrating text mining with quality function deployment

Data-driven personalized assortment optimization by considering customers’ value and their risk of churning: Case of online grocery shopping

An optimized Belief-Rule-Based (BRB) approach to ensure the trustworthiness of interpreted time-series decisions

SIAEF/PoE: Accountability of Earnestness for encoding subjective information in Blockchain

A multi-objective linear programming model for scheduling part families and designing a group layout in cellular manufacturing systems

A novel uncertainty-aware deep learning technique with an application on skin cancer diagnosis

Interpreting the antecedents of a predicted output by capturing the interdependencies among the system features and their evolution over time

The bi-objective orienteering problem with hotel selection: an integrated text mining optimisation approach

Reinforcement Learning-Based News Recommendation System

An end-to-end ranking system based on customers reviews: Integrating semantic mining and MCDM techniques

A Hybrid Semi-Supervised Approach for Estimating the Efficient and Optimal Level of Hospitals Outputs

Collaborators (8)

Daniel Prior

Ripon Chakrabortty

Omar Hussain

Farookh Hussain

Maxwell Chipulu

Ofer Zwikael

Mehdi Rajabi Asadabadi

Mohsen Abbaspour Onari

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