معرفی
Dr. Morteza Namvar is a Senior Lecturer at The University of Queensland Business School and an Affiliate of both the Centre for the Business and Economics of Health and Centre for Enterprise AI. His work bridges business contexts with advanced computational techniques, focusing on practical applications of artificial intelligence in organizational and healthcare settings.
- Faculty of Business, Economics and Law - School of Business
- Centre for the Business and Economics of Health
- Centre for Enterprise AI - Faculty of Engineering, Architecture and Information Technology
Dr. Namvar specializes in Machine Learning (ML), Natural Language Processing (NLP), and Large Language Models (LLMs), with research concentrated in three primary areas: leveraging NLP and LLMs for enhanced theory building in Information Systems research, text feature engineering using advanced language models, and personalization/user experience enhancement through contextual understanding. His work systematically analyzes unstructured text data to develop robust theoretical constructs and improve machine learning model capabilities.
His recent publications reveal strong trends in healthcare applications of LLMs, hate speech detection, and cryptocurrency market analysis through social media. The research consistently applies NLP techniques to solve real-world problems across healthcare, finance, and e-commerce domains, with particular emphasis on sociotechnical aspects of technology implementation.
Dr. Namvar has successfully secured competitive funding including the prestigious UQ Knowledge Exchange & Translation Fund grant for developing social media monitoring tools for small businesses, and multiple grants from Medical Protection Society Limited for machine learning applications in healthcare systems.
- 2021-2022: Developing a context-specific social media monitoring tool to empower Australian small business (UQKx&T Fund)
- 2021: Enhancing Education Development: Analysing Members' Feedback Using Machine Learning Techniques (Medical Protection Society)
- 2021: Investigating the effective use of data and analytics in Medical Protection Systems (Medical Protection Society)
He currently supervises five PhD students working on NLP and LLM applications in healthcare, data privacy regulation, and patient outcomes. His research impacts include leading machine learning projects with industry partners like Medical Protection Society and PA Hospital, where his NLP techniques have helped improve organizational strategies through text data analysis.
