Onur Yilmaz

Onur Yilmaz is a lead deep learning software engineer at NVIDIA and he has been with NVIDIA for more than 7 years. He is one of the main engineers who contributed to the RAPIDS cuML GPU-accelerated machine learning open source library, and he also contributed to NVIDIA Merlin, an open-source framework for building large-scale deep learning recommender systems. He is currently focusing on the inference side of the NVIDIA NeMo Framework. Onur holds a Ph.D. in computer engineering from the New Jersey Institute of Technology. His dissertation focused on traditional machine learning and high-performance computing for finance.
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Posts by Onur Yilmaz

Illustration showing models and NeMo.
Agentic AI / Generative AI Sep 10, 2024

Post-Training Quantization of LLMs with NVIDIA NeMo and NVIDIA TensorRT Model Optimizer

As large language models (LLMs) are becoming even bigger, it is increasingly important to provide easy-to-use and efficient deployment paths because the cost of... 10 MIN READ
Trustworthy AI / Cybersecurity Oct 04, 2022

Optimizing Fraud Detection in Financial Services with Graph Neural Networks and NVIDIA GPUs

Fraud is a major problem for many financial services firms, costing billions of dollars each year, according to a recent Federal Trade Commission report.... 22 MIN READ