Haifeng Jiang maintained the quantization workflow for edge deployments by updating the pt2e quantizer utilities in the google-ai-edge/ai-edge-torch repository to ensure compatibility with PyTorch 2.6. He addressed the challenge of deprecated private imports by removing them from torch.ao.quantization.pt2e.utils and locally redefining necessary components, preserving existing functionality after the framework upgrade. This work, implemented in Python and leveraging expertise in library updates and quantization, prevented regressions in the quantization path and reduced upgrade risk. Haifeng’s focused engineering contributed to the ongoing reliability and maintainability of the codebase, demonstrating depth in handling complex library transitions.