
Dr Hasindu Gamaarachchi
Hasindu Gamarachchi is a senior 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. 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.
Hasindu Gamaarachchi focuses on the design, development and optimisation of bioinformatics software and hardware for real-time sequencing data analysis; and, prototyping novel domain-specific computer systems for efficient genomics data analysis. He has more than 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 work include: an iterative genome assembly method that uses nanopore adaptive sampling to produce near-complete genome assemblies (Gamaarachchi, Nature Communications 2025); a novel domain-specific file format for efficient nanopore data processing (Gammaarachchi, Nature Biotechnology 2022); and, GPU-accelerated adaptive banded event alignment algorithm which is a core component in nanopore data analysis (Gammaarachchi, BMC Bioinformatics 2020).
Awards
- 2025Australian Museum Macquarie University Eureka Prize for Outstanding Early Career Researcher
- 2024“Torsten Seemann” Outstanding Bioinformatics Software Developer Award – Australian Bioinformatic And Computational Biology Society (ABACBS)
- 2021Dean's Award for Outstanding PhD Theses awarded by UNSW Sydney
- 2021Outstanding PhD Thesis award by Australian Bioinformatics And Computational Biology Society (ABACBS)
- 2020Grand finalist (third place winner) in the Association for Computing Machinery Student Research Competition (ACM SRC)
- 2019Best poster award in Australasian Genomic Technologies Association (AGTA) Conference
- 2019First place in the Association for Computing Machinery Special Interest Group on Embedded Systems Student Research Competition (ACM SIGBED SRC) at Embedded Systems Week Conference
- 2016Best presenter award in Present Around The World 2016 organised by Institution of Engineering and Technology-Young Professionals Section (IET-YPS) Sri Lanka
- 2016Best technical paper award in Annual Technical Conference of Institution of Engineering and Technology-Young Professionals Section (IET-YPS) Sri Lanka
- 2016C.A. Hewavitharana Prize awarded by University of Peradeniya for best performance in Engineering
- 2016Industrial and Financial Systems (IFS) Gold Medal awarded by University of Peradeniya for best perfrmance in Computer Engineering
Education
- 2015Bachelor of Science (Bachelor of Science (B.S)), Computer EngineeringUniversity of Peradeniya, Sri Lanka
- 2020Doctor of Philosophy (Doctor of Philosophy (Ph.D)), Computer EngineeringUniversity of New South Wales, Australia
Selected publications
See all publications- 2025Nature Communications10.1038/s41467-025-65410-x
Targeted sequencing and iterative assembly of near-complete genomes.
- 2025Genome Research10.1101/gr.280090.124
A new compression strategy to reduce the size of nanopore sequencing data.
- 2025Bioinformatics (Oxford, England)10.1093/bioinformatics/btaf151
Realfreq: real-time base modification analysis for nanopore sequencing.
- 2025Bioinformatics (Oxford, England)10.1093/bioinformatics/btaf111
Leveraging basecaller's move table to generate a lightweight k-mer model for nanopore sequencing analysis.
- 2025Nature Methods10.1038/s41592-025-02623-4
A systematic benchmark of Nanopore long-read RNA sequencing for transcript-level analysis in human cell lines.
