David Samuel is a PhD student in Language Technology at the University of Oslo with nine years of software and research experience bridging deep learning, NLP, and signal processing. He trained at Charles University in Prague (BSc, MSc AI) and has industry research experience including a music source separation project presented at ICASSP and a stint at Preferred Networks. David contributes practical ML tooling—his GitHub includes a PyTorch implementation of Sharpness-Aware Minimization (SAM) with stability and adaptive enhancements—demonstrating attention to both theory and robust engineering. His background spans research roles and production back-end development, giving him fluency from model design to deployment. Based in Oslo, he focuses on principled optimization and audio-language problems, often tackling numerical and stability challenges that are easy to overlook.
9 years of coding experience
2 years of employment as a software developer
University of Oslo
Master's degree, Artificial Intelligence, Master's degree, Artificial Intelligence at Charles University in Prague
Contributions:56 commits, 6 PRs, 37 pushes in 1 year 8 months
Contributions summary:David primarily contributed to the implementation and refinement of a Sharpness-Aware Minimization (SAM) optimizer within the PyTorch framework. Their work involved defining the SAM class, implementing the `first_step` and `second_step` functions, and integrating it with existing PyTorch optimizers. They also provided an example using the CIFAR-10 dataset, incorporated element-wise Adaptive SAM, and addressed numerical stability issues.
Contributions:1 release, 39 commits, 31 pushes in 3 months
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David Samuel - Doctoral Student at University of Oslo