Accident severity rating/identifying
Classified and described traffic accident imagery (flagging accident vs. non-accident cases) to build training data for a model learning to identify incidents more accurately.
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I've done microtask data labeling on UHRS, Clickworker, and a few others, mostly annotation, classification, and content evaluation across a bunch of different datasets. I'm comfortable working from detailed guidelines, staying consistent over long batches, and keeping my accuracy high enough to stay in the better task queues. I'm also a chemistry researcher and student, so I bring solid domain knowledge to technical or scientific labeling, and I tend to actually think through the ambiguous cases rather than rushing past them. I'm good at reading a rubric, making sensible calls when instructions are vague, and doing the careful, repetitive evaluation work that good training data depends on.
Classified and described traffic accident imagery (flagging accident vs. non-accident cases) to build training data for a model learning to identify incidents more accurately.
BSc, Chemistry
Highschool diploma, STEM
Chemist