David Boland

About

David Boland is a Lecturer at the University of Sydney, Australia. His research areas include FPGA-based machine learning, energy-efficient federated learning, and real-time data analysis. He has published recent articles on topics such as block minifloat training accelerators, highly parallel CNN accelerators, and spectral correlation density estimation. His work emphasizes the application of FPGA technology in advancing computational efficiency and performance in various domains.