I am broadly interested in the areas of deep learning, hardware architecture, and computer networks. I have worked on developing efficient deep neural network (DNN) algorithms and have designed hardware architectures for these DNNs. I am also interested in optimizing DNN inference (prediction) for edge devices in both standalone and distributed network contexts.
Recently, I have also starting exploring applying Large Language Models for program decompilation.
B. McDanel and Zhanhao Liu
3rd Generation, Evaluation & Metrics (GEM) Workshop at EMNLP’23
paper
code
B. McDanel, H. Dinh, J. Magallanes
International Conference on Pattern Recognition (ICPR), 2022.
preprint
S. Zhang, B. McDanel, H. T. Kung
28th IEEE International Symposium on High-Performance Computer Architecture (HPCA-28), 2022.
preprint
Copyright © 2024. Brad McDanel.
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