Nima Sedaghat

Senior AI Scientist at Volkswagen Group of America Innovation and Engineering Center California (IECC)

Seattle, Washington, United States
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Summary

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Senior
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Top School
Nima Sedaghat is a deep learning and computer vision researcher with 11 years of experience leading AI efforts at the intersection of astronomy and industry. Based at the University of Washington, he directs teams building the computer vision pipeline that will detect supernovae in images from the LSST/Rubin telescope and leads the Active Asteroids NASA partner program combining deep learning with citizen science. His work spans from convolutional encoder-decoders to generative models and vision-language systems, recently tuning DeepSeek’s Janus-Pro to interpret astronomical imagery. Former roles at ESO and OSRAM saw him pioneer generative models across 1D–3D astronomical data and apply ML to industrial sensing, reflecting a rare blend of scientific curiosity and production-grade engineering. He holds a PhD in Computer Vision from the University of Freiburg and is known for getting generative models to learn astrophysical features without explicit supervision.
code11 years of coding experience
job12 years of employment as a software developer
bookDoctor of Philosophy (PhD), Computer Vision, Doctor of Philosophy (PhD), Computer Vision at The University of Freiburg
bookAmirkabir University of Technology
languagesEnglish, German, Persian
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Github Skills (46)

caffe10
machine-learning10
deep-learning10
object-recognition9
keras8
optical-flow8
twitter-api8
twitter8
astronomy7
classfile7
abstraction7
3d7
voxel7
python7
jupyter-notebook7

Programming languages (9)

HCLTypeScriptC++TeXHTMLJupyter NotebookMATLABPython

Github contributions (5)

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lsst-dm/dmtn-216

Jan 2022 - Dec 2022

Deep Learning Approach(es) for LSST Alert Production
Contributions:4 reviews, 2 PRs, 51 pushes in 10 months
pytorchalertlsstdeep-learningapproach
lsst/meas_transiNet

May 2022 - Feb 2024

Contributions:106 reviews, 24 PRs, 182 pushes in 1 year 10 months
pipelines
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