Adeline Hillier

Scientific ML Software Developer at The Johns Hopkins University Applied Physics Laboratory

Greater Seattle Area United States
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Summary

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Adeline Hillier is a Scientific ML Software Developer with seven years of experience building high-performance scientific software at the intersection of machine learning, data assimilation, and climate science. Trained at MIT in EECS, she has developed production-ready emulators, uncertainty-quantification pipelines, and neural differential models for climate and turbulence problems and recently joined JHU Applied Physics Laboratory. Her background spans image- and video-based signal recovery in Julia, U-Net–based denoising and segmentation, and interactive visualization tools that accelerate research iteration. Comfortable communicating results to interdisciplinary audiences, she has presented work to Caltech, MIT and large scientific meetings and produced first-of-their-kind results validating new uncertainty quantification approaches. Intentional and detail-oriented, she pairs a curiosity for physical systems with pragmatic software engineering to turn research ideas into reproducible, high-performance code.
code6 years of coding experience
job3 years of employment as a software developer
bookM.Eng. Electrical Engineering and Computer Science, M.Eng. Electrical Engineering and Computer Science at Massachusetts Institute of Technology
bookNewport Senior High School
languagesSpanish, Portuguese
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Stackoverflow

Stats
1reputation
0reached
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0questions
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Github Skills (31)

fluid10
climate-science10
dynamics10
parameter-estimation10
climate-change10
fluid-dynamics10
ocean10
julia10
machine-learning9
gpu9
ocean-modelling9
uncertainty8
prediction-model8
probabilistic7
surface7

Programming languages (3)

JuliaJupyter NotebookPython

Github contributions (5)

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Contributions:42 pushes, 1 branch in 9 months
adelinehillier/OceanConvect

Jul 2020 - Aug 2020

Contributions:23 pushes, 3 branches in 1 month
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Adeline Hillier - Scientific ML Software Developer at The Johns Hopkins University Applied Physics Laboratory