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Arooba Maqsood

Overview of thesis

Ever heard of the sneaky fat that hides deep inside your abdomen and wraps around your organs? It's called visceral fat, and it's a major health risk. Excess visceral fat is strongly linked to serious conditions such as heart disease, diabetes, and certain cancers. The challenge is that it's not easy to detect. While MRI provides accurate measurements, it's expensive, and CT scans expose patients to relatively high doses of radiation.

That's where my research comes in. My work focuses on developing deep learning models to estimate visceral fat from Dual-energy X-ray Absorptiometry (DXA) scans - a more affordable and low-radiation alternative. By combining advanced image analysis with artificial intelligence, my approach enables fast, accurate, and non-invasive estimation of visceral fat, helping clinicians identify at-risk patients earlier and support better-informed healthcare decisions.

Qualifications

  • Doctor of Philosophy (PhD) in Information Technology, Edith Cowan University, Joondalup, Western Australia, Australia (2024-Present)
  • Master of Computer Science (Specialization: Intelligent Systems), National University of Sciences and Technology (NUST), Islamabad, Pakistan (2020-2022)

Research

Research Interests

  • Computer Vision
  • Medical Image Analysis
  • Deep Learning
  • Machine Learning
  • Natural Language Processing
  • Document Analysis and Recognition
  • Handwriting Recognition and Generation
  • Multimodality
  • Vision-Language Models
  • Obesity
  • Visceral Fat

Past Research employment history

  • 2024: Research Assistant (Casual), The University of Western Australia, Perth, Australia
  • 2020 - 2023: Research Assistant (Machine Learning), Deep Learning Lab, National Centre of Artificial Intelligence (NCAI), National University of Sciences and Technology (NUST), Islamabad, Pakistan

Other work

  • 2024 - Present: Casual Academic, Edith Cowan University, Western Australia
  • 2023: Machine Learning Engineer, DeepReader GmbH (Pakistan Chapter)

Past Teaching

  • 2024 - Present: Casual Academic, Edith Cowan University
    • Conducting Programming Fundamentals workshops (Python and C/C++).
    • Marking assessments and providing academic feedback for Programming Fundamentals and Data Structures.

Scholarships and Awards

  • 2024 - DVCR Strategic Research Scholarship
  • 2025 - People's Choice Award, WACRA Heart-to-Vessel Research Showcase

Supervisors

  • Dr Syed Zulqarnain Gilani - School of Science, Centre for Artificial Intelligence and Machine Learning (CAIML), and Nutrition and Health Innovation Research Institute (NHIRI)
  • Professor David Suter - School of Science, Centre for Artificial Intelligence and Machine Learning (CAIML), and Nutrition and Health Innovation Research Institute (NHIRI)
  • Professor Joshua Lewis - School of Medical and Health Sciences, Centre for Artificial Intelligence and Machine Learning (CAIML), and Nutrition and Health Innovation Research Institute (NHIRI)
  • Associate Professor Marc Sim - School of Medical and Health Sciences, Centre for Artificial Intelligence and Machine Learning (CAIML), and Nutrition and Health Innovation Research Institute (NHIRI)

Contact

Arooba Maqsood
PhD Student 
Centre for Artificial Intelligence and Machine Learning (CAIML)
Nutrition and Health Innovation Research Institute (NHIRI)
School of Science
Email: a.maqsood@ecu.edu.au

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