He has around ten years of experience in embedded computing systems, computer architecture, general-purpose computing with the use of a Graphics Processing Unit (GPU), high-performance computing and low-level system programming, which he leverages for the architecture-aware design of efficient computational systems for bioinformatics. Examples of his recent work include: a novel domain-specific file format for efficient nanopore data processing (Gammaarachchi, Nature Biotechnology 2022); GPU-accelerated adaptive banded event alignment algorithm which is a core component in nanopore data analysis (Gammaarachchi, BMC Bioinformatics 2019); memory optimisation of nanopore sequence alignment using partitioned indexes (Gammaarachchi, Scientific Reports 2020); and, optimisation of de Bruijn graphs using cache-friendly data structures in next-generation variant calling (Gammaarachchi, IEEE/ACM transactions on computational biology and bioinformatics / IEEE, 2018).

Since 2023, Hasindu has been a lecturer at the School of Computer Science and Engineering, UNSW Sydney. He is also a visiting scientist in the Genomic Technologies Group at Garvan Institute of Medical Research. From 2020 to 2022, he worked as a Genomics Computing Research Scientist at Garvan Institute of Medical Research. Hasindu completed his PhD in Computer Science and Engineering at UNSW Sydney in 2020. His PhD research has won multiple awards including third place in the Association for Computing Machinery Student Research Competition (ACM SRC) 2020, globally amongst the shortlisted competitors from over 20 major ACM conferences. He has served as a lecturer at the Department of Computer Engineering and a resource person at NVIDIA research centre at the University of Peradeniya. He completed his bachelor’s degree with first-class honours in Computer Engineering from the University of Peradeniya, Sri Lanka in 2015, where he received the award for best performance in Engineering.