STEM AI Domain Expert — Final Year Research Project
Produced expert-verified, fact-checked technical documents used for STEM AI training data. Applied systematic fact-checking, source validation, and evidence-based quality control to research outputs for model training. Generated and annotated responses in hydrology, hydraulics, and environmental science for training and evaluation tasks. • Synthesized literature and primary data for factuality benchmarking • Validated every quantitative claim and methodological step in the content • Delivered gold-standard, structured STEM text for AI learning • Performed annotation and expert-level QA of STEM academic content