Arash Vahdat

Arash Vahdat is a principal research scientist and research manager at NVIDIA Research leading the fundamental generative AI research (GenAIR) team. Arash is best known for his early work in generative AI models including variational autoencoders, diffusion models, and their latent extensions. Arash obtained his PhD from Simon Fraser University in Canada and was a research scientist at D-Wave Systems before joining NVIDIA in 2019.
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Posts by Arash Vahdat

Generative AI Jan 13, 2025

Evaluating GenMol as a Generalist Foundation Model for Molecular Generation

Traditional computational drug discovery relies almost exclusively on highly task-specific computational models for hit identification and lead optimization.... 8 MIN READ
Generative AI Apr 26, 2024

Enhance Text-to-Image Fine-Tuning with DRaFT+, Now Part of NVIDIA NeMo

Text-to-image diffusion models have been established as a powerful method for high-fidelity image generation based on given text. Nevertheless, diffusion models... 10 MIN READ
Computer Vision / Video Analytics Apr 26, 2022

Improving Diffusion Models as an Alternative To GANs, Part 2

This is part of a series on how researchers at NVIDIA have developed methods to improve and accelerate sampling from diffusion models, a novel and powerful... 16 MIN READ
Computer Vision / Video Analytics Apr 26, 2022

Improving Diffusion Models as an Alternative To GANs, Part 1

This is part of a series on how NVIDIA researchers have developed methods to improve and accelerate sampling from diffusion models, a novel and powerful class... 8 MIN READ
Data Science Nov 05, 2020

Discovering GPU-friendly Deep Neural Networks with Unified Neural Architecture Search

After the first successes of deep learning, designing neural network architectures with desirable performance criteria for a given task (for example, high... 9 MIN READ