Deepak Narayanan

Deepak Narayanan is a Senior Applied Deep Learning Research Scientist at NVIDIA, currently working in the ADLR (Applied Deep Learning Research) group.1 He joined NVIDIA in this role in July 2023, based in the Greater Seattle Area.1

Education and Career Path

Deepak has an impressive educational background:

• Ph.D. in Computer Science from Stanford University (2015-2021)
• Master's Degree in Computer Science from MIT (2014-2015)
• Bachelor's Degree in Mathematics and Computer Science from MIT (2011-2013)1

Prior to joining NVIDIA, Deepak's professional experience includes:

• Senior Researcher at Microsoft Research (September 2021 - July 2023)
• Software Development Intern at Microsoft (Summer 2014)
• Software Engineering Intern at Pinterest (Summer 2013)
• Research Intern at Microsoft Research India (Summer 2012)1

Research Focus

Deepak's research interests are broad and include:

• Systems for Machine Learning
• Distributed Systems
• Performance Optimization1

At NVIDIA, he primarily focuses on making the training and inference of large language models more efficient.2 His work involves developing and improving tools like NVIDIA Megatron-Core, which is designed to facilitate efficient training of generative AI models.2

Achievements and Impact

Deepak has made significant contributions to the field of deep learning and systems research:

• He has a high citation count, with over 9,600 citations and an h-index of 22.3
• His work on accelerating deep learning workloads and efficient multi-model execution has been particularly influential.3
• He has collaborated with renowned researchers from institutions like UC Berkeley, Microsoft Research, and MIT.3

Deepak's expertise in resource-efficient deep learning execution and training large language models at scale has made him a sought-after speaker in academic and industry circles.45