Hasindu Gamaarachchi focuses on the design, development and optimisation of bioinformatics software and hardware for real-time nanopore sequencing data analysis; and, prototyping novel domain-specific computer systems for efficient genomics data analysis. 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.
Project title: Computational methods for fast, lightweight and live nanopore sequencing analysis
Project Description: Third generation Nanopore sequencing is an emerging technology that has countless applications in fields such as precision medicine, forensics and agriculture. While handheld portable nanopore sequencing devices exist, powerful computers are required to perform subsequent data analysis. This project aims to create improved, highly efficient analysis methods and designs for the future creation of custom computer hardware for portable nanopore analysis. Work involves the design of new algorithms and data structures that maps well to modern computer systems and accelerating those using technologies such as SIMD, GPU, and FPGA. Candidates are expected to have a strong background in computer engineering with a focus on low-level system programming (must be proficient in C), computer architecture and embedded systems. Previous bioinformatics knowledge is not a must but candidates should be prepared to learn the necessary background material quickly. Candidates will be based in the School of Computer Science & Engineering, UNSW Sydney, Australia. Candidates will also collaborate with the Garvan Institute of Medical Research to evaluate their completed systems for real-world applications.
Enthusiastic and self-motivated candidates who are ready to take up this challenge are requested to contact me via email: hasindu+hdr@unsw.edu.au. In emails you send, make sure to include the ASCII text of the following byte array as the subject (not the byte array, but the ASCII text version). This is to make sure I do not miss emails from genuine and serious candidates amongst hundreds of generic spam emails.
80,0x68,68,32,0b1101111,0x70,112,111,114,116,117,110,105,116,0b1111001,32,105,110,0x20,0x66,97,0x73,116,
32,110,97,110,111,112,0b1101111,114,101,32,97,110,0x61,108,121,115,105,115,32,40,118,48,46,49,46,48,41
https://orcid.org/0000-0002-9034-9905