Dear Guo Yejun and Steven Liu,
I hope this email finds you well.

I am very much interested in the "Modernizing LibTorch Backend: Async
Infrastructure, Batching, and GPU Pipelines" project for Google Summer
of Code 2026.

I have carefully read the project description, including the goals
around migrating to the unified DNNAsyncExecModule, implementing
high-throughput batching with at::cat()/at::split(), zero-copy GPU
pipeline using at::from_blob() for AV_PIX_FMT_CUDA frames, the Lazy
Reallocator, and the FATE test suite.

I have 2 years of experience in C++, C systems programming and am
currently familiarizing myself with LibTorch (PyTorch C++ API),
FFmpeg's libavfilter framework.

I would greatly appreciate any guidance on next steps, or any updates
to the project scope.

More than any other tools out there, ffmpeg has shown me that software
has real and meaningful effects on the lives of countless people ,and
the best way I can give back is by contributing to this project.

Thank you for your time and for mentoring this interesting project. I
look forward to your reply.

Best regards,
t.k.naveen,
Chennai / Indian Standard Time
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