Daiyaan Arfeen
Deep Learning Architect at NVIDIA
United States
Summary
🤩
Rockstar🎓
Top SchoolDaiyaan Arfeen is a PhD computer science student at Carnegie Mellon with nine years of hands-on experience focused on deep learning and distributed systems. He has applied research and engineering skills across industry and academia, including internships at NVIDIA and AWS, a machine learning role at Hive, and research in optimization for efficient deep learning and distributed hyperparameter tuning at Berkeley RISE Lab. Daiyaan has taught and mentored students in ML and systems courses at UC Berkeley, translating complex theory into practical assignments and office-hour guidance. His background spans Bayesian modeling of human decision-making to production-oriented applied science, showing a rare blend of theoretical depth and implementation experience. Colleagues would note his ability to bridge research insights with scalable system designs that reduce power and memory footprints.
9 years of coding experience
2 years of employment as a software developer
Bachelor's degree Computer Science, Bachelor's degree Computer Science at University of California, BerkeleyDoctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Carnegie Mellon University
Github Skills (30)
pytorch10
parallel10
parallelization10
python10
data-science10
data-center10
machine-learning10
large-language-models10
reinforcement-learning10
llm-inference10
llm10
hyperparameter-optimization10
deep-learning10
tensorflow10
compression10
Programming languages (3)
Github contributions (5)
daiyaanarfeen/DeepSpeed
Jun 2023 - Jul 2023
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
Contributions:167 pushes, 1 branch in 1 month
daiyaanarfeen/Megatron-DeepSpeed
Jun 2023 - Jul 2023
Ongoing research training transformer language models at scale, including: BERT & GPT-2
Contributions:34 pushes in 1 month
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