Zhiwei Song is an AI engineer and MS candidate in Computer Science at the University of Wisconsin–Madison with 12 years of hands-on experience building and optimizing machine learning systems. He has demonstrable strengths in efficient model deployment—having implemented structured sparsity, custom CUDA/PyTorch operators, and post-training quantization workflows that yielded large inference speedups on edge and GPU platforms. Comfortable across the ML stack, he combines research experience in graph representation learning and recommender systems with practical production work in computer vision and LLM-based solutions. Zhiwei’s toolkit centers on Python and PyTorch, and he has a track record of tuning models for constrained hardware like Orin SoC while preserving accuracy. Based in Madison, he’s motivated to apply data-driven AI to real-world problems and often bridges the gap between prototype research and production-grade pipelines.
12 years of coding experience
2 years of employment as a software developer
Master of Science - MS, Computer Science, Master of Science - MS, Computer Science at University of Wisconsin-Madison
IB Diploma, IB Diploma at International School of Brussels
Contributions:12 pushes, 1 branch in 1 year 2 months
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