Dr Mevan Ekanayake is a Postdoctoral Researcher in the Anna Trigos Lab. His research focuses on leveraging deep learning to understand cancer evolution and treatment resistance by integrating large-scale molecular data (e.g., genomics) with patient imaging data (e.g., PET and CT scans).

Dr Ekanayake completed his PhD in Biomedical Engineering at Monash Biomedical Imaging (MBI), Monash University, in 2025. His doctoral research explored how artificial intelligence (AI) can enhance medical imaging by addressing key challenges such as lengthy scan times and limited spatial resolution. He developed novel AI models capable of reconstructing high-quality images from limited data, significantly improving both resolution and diagnostic accuracy. His work demonstrated the transformative potential of AI in advancing medical imaging and healthcare delivery. His research has been published in multiple high-impact, Q1-ranked journals (e.g., CiBM, BSPC, JDI) and presented at leading conferences (e.g., ISMRM, ISBI, WACV).

During his PhD, Dr Ekanayake received multiple awards recognizing both his scientific contributions and excellence in science communication. These include the Monash Engineering Postgraduate Publication Award, the Student Excellence Award at MBI, the ISMRM Summa Cum Laude Merit Award, the Hannah Brown Innovation Prize at the VHI Summit, and the Monash VYT Award. He also secured over AUD 30,000 in competitive funding, including DUC and AWS HPC research grants, as well as travel grants from IEEE and ISMRM.

In addition to his research, Dr Ekanayake has extensive teaching experience in deep learning, having served as an Assistant Lecturer and Teaching Associate at Monash University for over four years.

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Member of the Anna Trigos lab.