Parth Mannan
Senior Deep Learning Architect at NVIDIA
Bellevue, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolParth Mannan is a Senior Deep Learning Architect at NVIDIA with about three years of professional experience and an MS ECE thesis background from Georgia Tech focused on HW–SW co-design for efficient AI accelerators. He specializes in computer and GPU architecture, on-chip networks, and accelerating deep learning workloads, bringing research-grade rigor to production hardware design. His graduate work with Dr. Tushar Krishna on GeneSys explored continuous learning and hardware-accelerated evolutionary algorithms—an uncommon alternative to conventional reinforcement learning. Based in Bellevue, WA, Parth blends hands-on SoC design verification experience from Qualcomm with research prototyping and system-level thinking from internships and academic projects. He is comfortable translating academic ideas into silicon-feasible designs and thrives at the intersection of architecture, algorithms, and practical accelerator implementation.
3 years of coding experience
4 years of employment as a software developer
Master of Science - MS, Electrical and Computer Engineering, Master of Science - MS, Electrical and Computer Engineering at Georgia Institute of TechnologyBachelor of Engineering (B.E.), Electrical, Electronics and Communications Engineering, 9.18/10.0, Bachelor of Engineering (B.E.), Electrical, Electronics and Communications Engineering, 9.18/10.0 at Vellore Institute of Technology, Chennai
English, Hindi, Punjabi
Github Skills (59)
speaker-diarization10
speech-to-text10
machine-translation10
python10
machine-learning10
speech-synthesis10
multimodal10
large-language-models10
nmt10
text-normalization10
numpy10
deep-learning10
gpu10
generative-ai10
natural-language-processing10
Programming languages (2)
Github contributions (5)
parthmannan/fx_graph_converter
Jan 2023 - Jan 2023
Contributions:7 pushes, 1 branch, 2 comments in 4 days
parthmannan/stablediffusion
Oct 2023 - Oct 2023
High-Resolution Image Synthesis with Latent Diffusion Models
Contributions:1 push in 1 day
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