Jason Stock is a research scientist with eight years of experience at the intersection of machine learning and climate science, currently advancing AI-driven weather and climate research at NVIDIA. He holds a PhD in Computer Science from Colorado State University and has blended academic rigor with national-lab and industry experience through roles at Argonne, CSU, Maxar, and Boeing. His work spans learning the mechanics of neural networks, generative modeling, deep RL for control, and interpretable ML, with a notable focus on applying those methods to weather and climate modeling. Jason pairs foundational research with practical engineering—transitioning prototypes into research computing environments—and maintains an active public presence (jasonstock.me, GitHub, X) that reflects both reproducible research and tooling for scientific ML.
8 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy - Ph.D., Computer Science, Doctor of Philosophy - Ph.D., Computer Science at Colorado State University
Using Thread Pools & Micro Batching to Manage and Load Balance Active Network Connections
Contributions:22 PRs, 41 pushes, 5 branches in 1 year 4 months
balancebatchingload-balancethreadpools
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