Ting Ye is a software engineer with 13 years of experience, currently building systems at Intel from Minhang District, Shanghai. He combines deep learning interests with low-level network and firmware expertise, contributing to high-impact open-source projects such as the EDK II UEFI codebase. His contributions focus on strengthening network stacks and iSCSI reliability—adding IPv6 UNDI support, improving cryptographic error handling, and resolving session reinstatement issues—showing a pragmatic focus on robustness in constrained environments. Comfortable across back-end and firmware layers, he brings a systems-oriented perspective to machine learning engineering problems. Colleagues describe him as detail-driven and effective at turning intricate protocol-level issues into production-ready fixes.
Contributions:18 commits, 4 pushes in 6 years 4 months
Contributions summary:Ting primarily contributed to the EDK II project, focusing on bug fixes and enhancements related to network and iSCSI functionality. Their work involved addressing issues in the IPv6 network stack, improving error handling within cryptographic libraries, and resolving iSCSI session reinstatement problems. The user also enhanced iSCSI configuration checks and implemented IPv6 support from UNDI, demonstrating a focus on improving the robustness and functionality of the network stack within the UEFI environment.
A Python package for extending the official PyTorch that can easily obtain performance on Intel platform
Contributions:14 releases, 83 commits, 3 PRs in 2 years 3 months
pytorchpythondeep-learningintelmachine-learning
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.