Overview
Background
Dr. Morteza Namvar is a senior lecturer at UQ Business School, specializing in Business Information Systems. With a background in computer science and IT engineering, he brings valuable expertise to his research on Machine Learning (ML) and Natural Language Processing (NLP) in business settings. Morteza is passionate about exploring the applications of ML, NLP and LLM in organizational contexts. In his research program, he mentors several PhD and HDR students in leveraging these technologies to drive innovation and efficiency across various business domains. He has successfully secured funding for multiple ML and NLP projects and has disseminated his findings through publications in esteemed journals and conferences in IS and computer science. Dedicated to cultivating the next generation of ML enthusiasts, Morteza’s teaching focuses on ML development using Python, equipping students with the skills and confidence needed to thrive in the dynamic field of ML.
Availability
- Dr Morteza Namvar is:
- Available for supervision
- Media expert
Fields of research
Research interests
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Leveraging NLP and LLMs for Enhanced Theory Building in IS Research
In the first theme of research I explore how NLP and LLM technologies can enhance theory building and testing in IS research. As the role of textual data in IS research grows, the ability to effectively analyze this data is critical for theoretical advancement. In this research theme, I aim to leverage NLP and LLMs to systematically analyze unstructured text data, which can provide deeper insights into complex phenomena and support the development of robust theoretical constructs. By applying these advanced techniques, I strive to enhance the rigor and relevance of theory building and testing in the field of IS research, ultimately contributing to a more nuanced understanding of the dynamic interactions between technology and society.
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Text Feature Engineering using NLP and LLM
In this research theme, I focus on enhancing the capabilities of machine learning models through advanced text feature engineering using NLP and LLMs. As the complexity of textual data increases, the need for sophisticated feature extraction methods becomes critical to capture the nuanced patterns and meanings embedded in text. By leveraging the deep contextual understanding and language modeling capabilities of NLP and LLMs, I aim to develop innovative techniques for transforming unstructured text into structured, meaningful features that can be effectively utilized by machine learning algorithms. This research theme seeks to bridge the gap between raw textual data and actionable insights, facilitating improved performance in various applications such as sentiment analysis, semantic search, and misinformation detection.
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Personalization and User Experience Enhancement
In this research theme, I focus on using NLP and LLMs to personalize and enhance user experiences across various platforms and applications. By leveraging the contextual understanding capabilities of NLP and LLMs, I aim to develop algorithms that can deliver personalized content and recommendations, providing a more engaging and tailored user experience. This research includes exploring how these models can improve natural language understanding, conversational AI, and adaptive interfaces, which are critical in the era of personalized digital interactions.
Research impacts
Morteza has led teams at UQ in several machine learning (ML) projects with industry partners, including Medical Protection Society (MPS) and PA hospital. In these projects, he applied the NLP techniques he has developed in his research to the text data to help the industry in improving their strategies. He had succeeded in winning the prestigious UQKx&T grant.
Works
Search Professor Morteza Namvar’s works on UQ eSpace
2024
Journal Article
Data-driven sensegiving and sensemaking: a phenomenological investigation
Namvar, Morteza, Im, Ghiyoung P., Li, Jingqi (Celeste) and Chung, Claris (2024). Data-driven sensegiving and sensemaking: a phenomenological investigation. Information Technology & People. doi: 10.1108/itp-05-2023-0452
2024
Conference Publication
Navigating Implicit Hate Speech - A Scoping Review
Xie, Hetiao (Slim), Namvar, Morteza, Risius, Marten and Akhlaghpour, Saeed (2024). Navigating Implicit Hate Speech - A Scoping Review. European Conference on Information Systems, Paphos, Cyprus, 13-19 June 2024. Atlanta, GA United States: Association for Information Systems.
2024
Conference Publication
Unpacking sociotechnical discourses on telehealth use and data protection: a path towards digital health value creation
Pool, Javad, Fatehi, Farhad, Sharifi, Salma, Namvar, Morteza and Akhlaghpour, Saeed (2024). Unpacking sociotechnical discourses on telehealth use and data protection: a path towards digital health value creation. Amsterdam, Netherlands: IOS Press. doi: 10.3233/SHTI240013
2024
Journal Article
Machine Learning Based Decision-Making: A Sensemaking Perspective
Li, Jingqi Celeste, Namvar, Morteza, Im, Ghiyoung P. and Akhlaghpour, Saeed (2024). Machine Learning Based Decision-Making: A Sensemaking Perspective. Australasian Journal of Information Systems, 28 ARTN 4781, 1-22. doi: 10.3127/ajis.v28.4781
2023
Conference Publication
A Review of Hate Speech Detection: Challenges and Innovations
Xie, Hetiao (Slim), Namvar, Morteza and Risius, Marten (2023). A Review of Hate Speech Detection: Challenges and Innovations. Digit 2023, Hyderabad, India, December 10, 2023. Atlanta, GA United States: Association for Information Systems.
2023
Conference Publication
Understanding Bitcoin fluctuations via Tweet and user characteristics
Namvar, Morteza, Li, Jingqi and Akhlaghpour, Saeed (2023). Understanding Bitcoin fluctuations via Tweet and user characteristics. Pacific Asia Conference on Information Systems (PACIS), Nanchang, China, 8-12 July 2023.
2023
Conference Publication
Revisiting Review Depth in Search for Helpful Online Reviews
Dorwat, Shardul, Namvar, Morteza and Akhlaghpour, Saeed (2023). Revisiting Review Depth in Search for Helpful Online Reviews. 56th Hawaii International Conference on System Sciences (HICSS), Maui, HI United States, 3-6 January 2023. Piscataway, NJ United States: IEEE Computer Society.
2022
Journal Article
Exploring public opinion about telehealth during COVID-19 by social media analytics
Pool, Javad, Namvar, Morteza, Akhlaghpour, Saeed and Fatehi, Farhad (2022). Exploring public opinion about telehealth during COVID-19 by social media analytics. Journal of Telemedicine and Telecare, 28 (10), 718-725. doi: 10.1177/1357633x221122112
2022
Conference Publication
Iterative seed word generation for interactive topic modelling: a mixed text processing and qualitative content analysis approach
Namvar, Morteza, Akhlaghpour, Saeed, Boyce, James and Sharifi, Salma (2022). Iterative seed word generation for interactive topic modelling: a mixed text processing and qualitative content analysis approach. International Conference on Information Systems (ICIS), Copenhagen, Denmark, 9-14 December 2022. Atlanta, GA United States: Association for Information Systems.
2022
Journal Article
Beyond effective use: integrating wise reasoning in machine learning development
Namvar, Morteza, Intezari, Ali, Akhlaghpour, Saeed and Brienza, Justin P. (2022). Beyond effective use: integrating wise reasoning in machine learning development. International Journal of Information Management, 69 102566, 102566. doi: 10.1016/j.ijinfomgt.2022.102566
2022
Journal Article
The impact of context clues on online review helpfulness
Namvar, Morteza and Chua, Alton Y.K. (2022). The impact of context clues on online review helpfulness. Internet Research, 33 (3), 1015-1030. doi: 10.1108/intr-02-2021-0093
2022
Journal Article
Emergent affordances and potential challenges of mobile learning apps: Insights from online reviews
Gholizadeh, Mehran, Akhlaghpour, Saeed, Namvar, Morteza and Teixeira Isaias, Pedro (2022). Emergent affordances and potential challenges of mobile learning apps: Insights from online reviews. Information Technology & People, ahead-of-print (ahead-of-print), 2500-2517. doi: 10.1108/itp-05-2021-0412
2022
Conference Publication
Towards explaining user satisfaction with contact tracing mobile applications in a time of pandemic: a text analytics approach
Namvar, Morteza, Akhlaghpour, Saeed, Pool, Javad and Priscilia, Anisa (2022). Towards explaining user satisfaction with contact tracing mobile applications in a time of pandemic: a text analytics approach. Hawaii International Conference on System Sciences (HICSS), Hawaii, United States, 3-7 January 2022. Roskilde, Denmark: Roskilde University. doi: 10.24251/HICSS.2022.293
2022
Journal Article
Knowledge identity (KI): a determining factor in the effective use of analytics
Intezari, Ali, Namvar, Morteza and Taghinejad, Ramin (2022). Knowledge identity (KI): a determining factor in the effective use of analytics. Knowledge Management Research and Practice, 20 (1), 14-33. doi: 10.1080/14778238.2021.1967213
2022
Conference Publication
On Justification: Legislating a Digital First Artifact
Sharifi Khajedehi, Salma, Namvar, Morteza, Pool, Javad and Akhlaghpour, Saeed (2022). On Justification: Legislating a Digital First Artifact. International Conference on Information Systems (ICIS) , Copenhagen, Denmark, 19-14 December 2022. Atlanta, GA United States: AIS eLibrary.
2022
Journal Article
Hybrid metaheuristics for QoS-Aware Service Composition: a systematic mapping study
Naghavipour, Hadi, Soon, Tey Kok, Idris, Mohd Yamani Idna Bin, Namvar, Morteza, Salleh, Rosli Bin and Gani, Abdullah (2022). Hybrid metaheuristics for QoS-Aware Service Composition: a systematic mapping study. IEEE Access, 10, 12678-12701. doi: 10.1109/access.2021.3133505
2022
Conference Publication
Exploring the relationship between influencers’ sentiment and cryptocurrency fluctuation through microblogs
Namvar, Morteza, Li, Jingqi, Boyce, James, Akhlaghpour, Saeed and Indulska, Marta (2022). Exploring the relationship between influencers’ sentiment and cryptocurrency fluctuation through microblogs. ACIS 2022 - Australasian Conference on Information Systems, Melbourne, VIC, Australia, 4-7 December 2022. Atlanta, GA, United States: Association for Information Systems.
2021
Conference Publication
Utilitarian, hedonic and monetary motivations of using mobile learning apps: Opinion mining using big data text analytics
Gholizadeh, Mehran, Akhlaghpour, Saeed, Teixeira Isaias, Pedro and Namvar, Morteza (2021). Utilitarian, hedonic and monetary motivations of using mobile learning apps: Opinion mining using big data text analytics. Australasian Conference on Information Systems 2021, Sydney, NSW Australia, 6-10 December 2021. Association for Information Systems.
2021
Journal Article
Sensegiving in organizations via the use of business analytics
Namvar, Morteza, Intezari, Ali and Im, Ghiyoung (2021). Sensegiving in organizations via the use of business analytics. Information Technology & People, ahead-of-print (ahead-of-print), 1615-1638. doi: 10.1108/itp-10-2020-0735
2021
Conference Publication
Knowledge Identity (KI): A New Approach to Integrating Knowledge Management into Enterprise Systems
Intezari, Ali, Namvar, Morteza and Taghinejhad, Ramin (2021). Knowledge Identity (KI): A New Approach to Integrating Knowledge Management into Enterprise Systems. Hawaii International Conference on System Sciences (HICSS), Hawaii, United States, 5-8 January 2021. Honolulu, HI United States: HICCS.
Funding
Past funding
Supervision
Availability
- Dr Morteza Namvar is:
- Available for supervision
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Available projects
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Exploring the Applications of LLM in Pediatric Hospitals
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Uncovering the impacts of social media on cryptocurrency value
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Optimising machine learning techniques to enhance social media monitoring algorithms
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The effective use of machine learning (ML)
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Exploring the Applications of LLM in Pediatric Hospitals
This research focuses on the innovative use of LLMs within pediatric hospitals. We will explore how NLP and LLMs can be applied to enhance patient care, streamline administrative tasks, and support medical staff in making informed decisions. Students will have the opportunity to investigate the potential of AI-driven solutions to improve healthcare outcomes for children, offering a hands-on experience in a critical and evolving area of medical technology.
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Leveraging NLP and LLMs for Enhanced Misinformation Detection
This research delves into the use of NLP and LLMs for detecting misinformation. We will explore how these advanced AI techniques can be applied to analyze and identify false or misleading information across various digital platforms. Students will engage in developing and fine-tuning models to enhance the accuracy of misinformation detection, contributing to a crucial area of study in today's information-driven world
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Optimizing Call Center Speech Detection and Resource Allocation Using LLM-Driven Chatbots in Healthcare
In this research project, we explore the integration of LLMs to enhance call center operations in the healthcare sector. By leveraging advanced LLM-driven chatbots, we aim to improve speech detection accuracy and optimize resource allocation, ultimately leading to more efficient and responsive patient support systems. This study offers students an opportunity to engage with cutting-edge AI technologies and their practical applications in healthcare
Supervision history
Current supervision
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Doctor Philosophy
Exploring the Impact of Generative AI on the Workplace through Natural Language Processing
Principal Advisor
Other advisors: Associate Professor Saeed Akhlaghpour
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Master Philosophy
Text Analysis of Immigration Tweets in Australia Using Machine Learning and Natural Language Processing
Principal Advisor
Other advisors: Associate Professor Saeed Akhlaghpour, Dr Marten Risius
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Doctor Philosophy
Combining Qualitative and Machine Learning Techniques Towards Effective Regulation of Data Privacy and Cybersecurity
Principal Advisor
Other advisors: Dr Ali Intezari Harsini
Completed supervision
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2023
Doctor Philosophy
Towards Understanding Affordances of Mobile Learning Applications Through Applying Data-Driven Computationally Intensive Theory Development Approach to Online Reviews
Associate Advisor
Other advisors: Associate Professor Saeed Akhlaghpour
Media
Enquiries
Contact Dr Morteza Namvar directly for media enquiries about:
- machine learning
- text analytics
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