Jia-ren Chang is a senior engineer with 11 years of experience specializing in computer vision, deep learning, and cognitive neuroscience, currently driving R&D at MediaTek in Taiwan. He holds a PhD in Computer Science and a strong research track record in 3D vision, including publications in well-known conferences and journals. His work on state-of-the-art stereo matching has clear industrial applicability and is reflected in hands-on contributions to the widely used PSMNet repository, where he improved model architecture, disparity regression, and dataset-specific finetuning. Previously as a data scientist at aetherAI, he bridged research and product by adapting advanced vision models for real-world inference scenarios. Jia-ren combines academic depth with practical engineering, frequently moving models from paper to reliable checkpoints and optimized pipelines. His background in neuroscience and psychology gives him a unique perspective on perception-driven ML problems.
11 years of coding experience
2 years of employment as a software developer
Master's degree, Neuroscience, Master's degree, Neuroscience at 國立陽明大學
Bachelor's degree, Psychology, Bachelor's degree, Psychology at 中山醫學大學
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at 國立交通大學
Contributions:89 commits, 5 PRs, 86 pushes in 3 years 6 months
Contributions summary:Jia-ren primarily focused on modifying and finetuning the PSMNet model, as indicated by the changes to `finetune.py` and `main.py`. These modifications involve adjusting learning rates, optimizing the 3-px error calculation, and saving model checkpoints. Furthermore, the user made several updates to the core model architecture, including `stackhourglass.py`, and corrected disparity regression in `submodule.py`. The user also adapted the code for different datasets and inference scenarios.
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