Yan Cheng

Yan Cheng is the lead of the engineering team that works closely with the DLMED researchers to architect and implement the Clara Train SDK. He has many years of experience building industry-quality software systems. Before joining NVIDIA, he served as a chief architect for AOL, and did IT consulting for the federal government.

Posts by Yan Cheng

Data Science Apr 16, 2025

Efficient Federated Learning in the Era of LLMs with Message Quantization and Streaming

Federated learning (FL) has emerged as a promising approach for training machine learning models across distributed data sources while preserving data privacy.... 8 MIN READ

Edge Computing Apr 11, 2025

Effortless Federated Learning on Mobile with NVIDIA FLARE and Meta ExecuTorch

NVIDIA and the PyTorch team at Meta announced a groundbreaking collaboration that brings federated learning (FL) capabilities to mobile devices through the... 12 MIN READ

Data Science Dec 18, 2024

Security for Data Privacy in Federated Learning with CUDA-Accelerated Homomorphic Encryption in XGBoost

XGBoost is a machine learning algorithm widely used for tabular data modeling. To expand the XGBoost model from single-site learning to multisite collaborative... 10 MIN READ

Data Science Jun 28, 2024

Federated XGBoost Made Practical and Productive with NVIDIA FLARE

XGBoost is a highly effective and scalable machine learning algorithm widely employed for regression, classification, and ranking tasks. Building on the... 6 MIN READ

Computer Vision / Video Analytics Nov 29, 2021

Creating Robust and Generalizable AI Models with NVIDIA FLARE

Federated learning (FL) has become a reality for many real-world applications. It enables multinational collaborations on a global scale to build more robust... 6 MIN READ

Data Science Apr 15, 2020

Powering AutoML-enabled AI Model Training with Clara Train

Deep neural networks (DNNs) have been successfully applied to volume segmentation and other medical imaging tasks. They are capable of achieving... 8 MIN READ