Dingqing Yang

Dingqing Yang is a deep learning performance engineer at NVIDIA. He joined the NVIDIA team in 2025 after completing his PhD in Electrical and Computer Engineering at the University of British Columbia. His work focuses on pushing the boundaries of large language model training, specializing in performance optimization for fine-grained mixture of experts (MoE) architectures.
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Posts by Dingqing Yang

Developer Tools & Techniques Apr 22, 2026

Advancing Emerging Optimizers for Accelerated LLM Training with NVIDIA Megatron

Higher-order optimization algorithms such as Shampoo have been effectively applied in neural network training for at least a decade. These methods have achieved... 9 MIN READ