Dr. Ishara Paranawithana

Scientist at CSIRO Health & Biosecurity

Biomedical Informatics Group, Australian e-Health Research Centre

Honorary Research Fellow at the Department of Molecular Imaging & Therapy, Austin Health

Medical Imaging | Computer Vision | Engineering | Applied AI & Data Analytics

About Me

An experienced engineer and researcher with a strong data science background (applied AI/ML), passionate about solving complex problems in medical and healthcare field. With over eight years of experience across medical imaging, neurotechnology, surgical robotics, and real-world clinical data analytics, my mission is to translate scientific innovation into impactful solutions that improve patient outcomes and quality of life.

Current Role: CSIRO - Alzheimer’s Disease & Dementia Research

I am currently an Early Career Research Fellow at the Australian e-Health Research Centre, CSIRO, Australia's national research agency, where I work on developing novel PET and MRI imaging biomarker quantification pipelines for Alzheimer’s disease. My focus is to create tools that help clinicians to detect the disease earlier and more accurately, monitor treatment response closely and make more informed clinical decisions. In this role, I work closely with collaborators from Austin Health (Melbourne) The Florey Institute of Neuroscience and Mental Health (Melbourne), University of Pittsburgh (USA), Eli Lilly & Company (USA), and Edith Cowan University (Perth), bringing together clinical and industry expertise to advance dementia research.

Doctoral Research: Understanding Early Brain Development

My PhD research (advisors: Prof. Yan Wong, Prof. Colette McKay and Dr. Darren Mao) explored how the brain’s language networks develop in early childhood. I developed objective imaging measures that can help identify early signs of language-related difficulties, particularly in infants with hearing impairment. This work shaped my interest in developing objective measures and tools that support early diagnosis and targeted intervention.

Early Work in Computer Vision and Surgical Robotics

Before my doctoral studies, I worked at Singapore University of Technology and Design (SUTD) as part of the Sensing, Actuation and Mechanism Design Group, contributing to healthcare-focused projects in vision-based micromanipulation and ultrasound-guided surgical robotics. Through collaborations with MIT (USA), A*STAR (Singapore), and Changi General Hospital (Singapore), I developed advanced prototypes and clinically deployable solutions aimed at improving clinical precision, safety, and workflow automation.

Background & Training

I hold a bachelor’s degree in Electronic and Telecommunication Engineering from University of Moratuwa, Sri Lanka. Throughout my career, I have been driven by passion to work at the intersection of engineering and data science to advance next-generation medical technologies and create meaningful solutions for complex read-world problems.

Core Skills & Competencies

Programming: Python (pandas, numpy, scipy, matplotlib, seaborn, plotly), MATLAB, C++, Bash/Shell scripting; Linux-based development environments; High-performance and parallel computing (HPC, CUDA/GPU clusters, SLURM job scheduling)

Tools & Platforms: Containerization (Singularity, Docker); Environment and dependency management (Anaconda); Code and data version control (GitHub, DVC); Interactive computing (VS Code, Jupyter)

Medical Imaging/Signal Processing: Multi–modal imaging (MRI: T1w/T2w/FLAIR/T2*/QSM/SWI, PET: Aβ/tau/neuroinflammation markers, CT, Ultrasound, fNIRS); Multi–dimensional data formats (DICOM, NIfTI); Image processing and analysis (NiBabel, Nilearn, SimpleITK, Scikit-image, OpenCV, SPM); Visualization and annotation tools (3D Slicer, ITK-SNAP, Mango, ImageJ)

Applied AI & Data Analytics: Supervised and unsupervised machine learning; Deep learning (CNNs, 3D U-Net); Feature engineering; Frameworks and libraries (PyTorch, MONAI, TensorFlow, Scikit-learn)