Jian Yang is a research scientist at Meta with a decade of experience bridging edge computing, vehicular networks, and machine learning, grounded in a Ph.D. from the University of Notre Dame. He combines strong systems and software skills (Python, Java, C/C++, Android/iOS) with hands-on kernel-level ML optimization—contributing performance-tuned convolution kernels to AMD's widely used MIOpen library. Jian has led interdisciplinary, industry-funded projects (including work for Ford) and built production forecasting and monitoring tools for Edge Backbone networks during his Meta internship. A quick learner and collaborative leader, he pairs academic rigor in wireless and hardware-security research with pragmatic engineering to deliver deployable systems. Based in Menlo Park, he pursues research that aims to make the world demonstrably better, as reflected both in his GitHub motto and his choice of impactful open-source contributions.
10 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Doctor of Philosophy (Ph.D.) at University of Notre Dame
Bachelor’s Degree, Bachelor’s Degree at Zhejiang University
Contributions summary:Jian primarily contributes to the `rocm/miopen` repository by implementing and optimizing convolution kernels. Their commits focus on adding and modifying 1x1 convolution kernels, including supporting pad and stride configurations. The contributions involve tuning performance through code changes and addressing potential compiler issues. The user's work directly affects the efficiency of the machine learning library.
Contributions:325 commits, 307 pushes, 1 branch in 4 years
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