Keywords
Fields of Research (FoR)
Artificial intelligence, Machine learning, Pattern recognition, Natural language processing, Data engineering and data science, Deep learning, Reinforcement learning, Business analytics, Business information systems, Biomedical engineeringSEO tags
Biography
Dr Masoud Fetanat is a researcher, academic and applied AI practitioner working across artificial intelligence, machine learning, data science, generative AI, business analytics and information systems. He has extensive academic and industry experience developing and deploying AI and data-driven solutions across healthcare, financial services, engineering and AI product development.
His research interests include deep learning, predictive...view more
Dr Masoud Fetanat is a researcher, academic and applied AI practitioner working across artificial intelligence, machine learning, data science, generative AI, business analytics and information systems. He has extensive academic and industry experience developing and deploying AI and data-driven solutions across healthcare, financial services, engineering and AI product development.
His research interests include deep learning, predictive modelling, data science and business analytics, generative AI and large language models, trustworthy and responsible AI, agentic AI, MLOps and cloud AI systems, information systems and AI-enabled digital transformation, and biomedical and applied AI. He is particularly interested in translating advances in AI and data science into practical technologies, intelligent systems and decision-support tools that address real-world problems across business, finance, healthcare and engineering.
My Qualifications
Ph.D. UNSW Sydney
My Research Activities
I contribute to the international research community through peer-review service for journals across artificial intelligence, machine learning, data science, optimisation, intelligent systems, signal processing and applied engineering.
I have served as a reviewer for journals including:
- IEEE Transactions on Neural Networks and Learning Systems
- IEEE Transactions on Medical Imaging
- IEEE Transactions on Systems, Man, and Cybernetics
- IEEE Transactions on Biomedical Engineering
- IEEE Transactions on Industrial Informatics
- IEEE Internet of Things Journal
- IEEE Journal of Biomedical and Health Informatics
- IEEE Transactions on Cybernetics
- IEEE Transactions on Affective Computing
- IEEE Access
- Knowledge-Based Systems
- Expert Systems with Applications
- Applied Soft Computing
- Information Fusion
- Information Sciences
- Engineering Applications of Artificial Intelligence
- Biomedical Signal Processing and Control
My Research Supervision
Supervision keywords
Areas of supervision
Potential PhD, MPhil and Master by Research project areas include:
- Generative AI and large language models: foundation models, LLM post-training, evaluation, alignment and reliable deployment
- Retrieval-augmented generation and agentic AI: RAG, GraphRAG, knowledge-grounded reasoning, multi-agent systems and tool-using agents
- Machine learning, deep learning and predictive analytics for data-driven decision making across business, healthcare, engineering and scientific applications
- Business analytics and intelligent information systems: AI-enabled decision support, enterprise AI and data-driven organisational applications
- AI-enabled digital transformation: adoption and deployment of Generative AI, intelligent automation and emerging AI technologies in organisations
- Trustworthy and responsible AI: explainability, uncertainty, calibration, robustness, model reliability, privacy and technology risk
- Multimodal AI and representation learning across text, images, time-series, sensor data and structured information
- MLOps, cloud AI and machine-learning systems: model monitoring, drift detection, scalable deployment and responsible production AI
- Biomedical and healthcare AI: clinical prediction, biomedical signal processing, physiological modelling and intelligent decision-support systems
- Applied AI and data science for real-world problems across business, finance, healthcare and engineering
Publications
ORCID as entered in ROS
https://orcid.org/0000-0001-8882-9937