Dustin Schwenk is a research engineer and data scientist with 11 years building high-impact AI systems and datasets, currently known for core contributions to AI2’s OLMo project—the world’s leading fully open language model. He spans the full model lifecycle from pretraining dataset construction and large-scale training experiments to evaluation suite development, with earlier work across vision-language, robotics, and on-device inference. Dustin began his career applying simulation science to aerospace problems and brings that rigor in experimental design and uncertainty quantification to ML research. He has a strong foundation in engineering physics (UIUC) and a track record of turning complex scientific problems into reproducible datasets and benchmarks. Colleagues rely on him for meticulous data curation and pragmatic evaluation strategies that directly improve model robustness and real-world utility.
11 years of coding experience
14 years of employment as a software developer
University of Illinois Urbana-Champaign
Physics, Physics at Rose-Hulman Institute of Technology
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