Ming-yang Ho is a research scientist and computer vision specialist with eight years of experience building and deploying ML systems across industry and academia. He is first author on ECCV papers (Kernelized Instance Normalization, Dense Normalization) and has combined research with production engineering—shipping distributed inference services, ONNX/TensorRT deployments, and CI-backed CV libraries. His background spans roles from senior ML engineer at aetherAI to SWE PhD intern work on multi-agent systems at Google Cloud and investigating Gaussian Splatting for 3D reconstruction as a visiting researcher. Trained across pharmacy, bioinformatics, and computer science (including a PhD path at Duke and NTU), he brings uncommon domain breadth that informs practical ML solutions in healthcare and vision. Known for bridging novel algorithms with robust ML lifecycles, he often couples publications with productionized code and systems.
8 years of coding experience
5 years of employment as a software developer
Doctor of Pharmacy - PharmD, Pharmacy, GPA: 4.1/4.3 (CS-related GPA: 4.3) || Outstanding Graduate Award, Doctor of Pharmacy - PharmD, Pharmacy, GPA: 4.1/4.3 (CS-related GPA: 4.3) || Outstanding Graduate Award at National Cheng Kung University
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Duke University
Doctor of Philosophy - PhD, Computer Science, GPA 4.2/4.3, Doctor of Philosophy - PhD, Computer Science, GPA 4.2/4.3 at National Taiwan University
Contributions:1329 commits, 798 pushes, 1 issue in 9 months
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