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His current teaching interests relate to embedded systems encompassing digital systems design, VHDL for FPGAs and system testing. Dr. Harkin leads research on the design of intelligent embedded systems and focuses on developing electronic computing systems that can self-repair under the presence of errors. In particular, his work explores how computer models of neural networks (brain like-repair) can be mapped to hardware to build highly efficient and reliable embedded computers.
His work has seen innovations in Networks-on-Chip strategies and the hardware implementation of self-repairing Spiking Neural Networks, and is Co-founder of the medical analytics start-up company Respiratory Analytics. He has secured grant funding of +£3.5 million from several sources including EPSRC, MRC, Innovate UK, HSC R&D, InvestNI and DEL and has published over +140 articles in peer-reviewed journals and conferences. He was included in the University’s Computer Science (UoA 23) submission to the RAE 2008, REF2014 and also UoA 11 in REF2021.
His work has seen innovations in Networks-on-Chip strategies and the hardware implementation of self-repairing Spiking Neural Networks, and is Co-founder of the medical analytics start-up company Respiratory Analytics. He has secured grant funding of +£3.5 million from several sources including EPSRC, MRC, Innovate UK, HSC R&D, InvestNI and DEL and has published over +140 articles in peer-reviewed journals and conferences. He was included in the University’s Computer Science (UoA 23) submission to the RAE 2008, REF2014 and also UoA 11 in REF2021.
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Andrew Walter, Shimeng Wu,Andy M. Tyrrell,Liam McDaid,Malachy McElholm, Nidhin Thandassery Sumithran,Jim Harkin,Martin A. Trefzer
arxiv(2024)
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International Joint Conference on Computational Intelligencepp.514-523, (2023)
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2022 IEEE Zooming Innovation in Consumer Technologies Conference (ZINC)pp.7-10, (2022)
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