Signals & learning
Connecting signal analysis, model training, and system validation through DSP and deep learning.
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I like starting with signals and data, then putting engineering methods into work people can use. DSP and deep learning are continuing interests, explored through ECG classification, embedded systems, and this site’s Web 3D interactions.
I treat AI agents as engineering collaborators rather than autocomplete: structured context, task decomposition, parallel research, tests, and review constrain the output. This site is both a long-term archive and a real product where that method keeps evolving.
Connecting signal analysis, model training, and system validation through DSP and deep learning.
I use context engineering, multi-agent task decomposition, documented decisions, and test-driven delivery.
I care about usability, accessibility, and expression; English calligraphy and photography keep me attentive to rhythm, space, and observation.
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