Contributions to projects I use daily — mostly PyTorch and its ecosystem.
Deep learning framework to train, deploy, and scale PyTorch models fast.
Contributed PyTorch compiler optimizations and CUDA device-level bug fixes.
Streamline data pipelines for AI. Process datasets across 1000s of machines, and optimize data for blazing fast model training.
Improved performance on distributed data stream loading and multi-GPU staging.
Tensors and dynamic neural networks in Python with strong GPU acceleration.
Helped optimize compiler frontend, CUDA graph execution paths, and memory optimizations.