Sina Mohseni

Senior Software Engineer at NVIDIA

Campbell, California, United States
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Summary

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Senior
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Sina Mohseni is a Senior Software Engineer and PhD candidate specializing in interpretable ML, deep learning safety, and human-AI interaction with a decade of experience bridging research and production. Currently at NVIDIA, he designs safety-focused deep learning techniques for autonomous systems, including self-supervised out-of-distribution error detection published at AAAI. His academic work at Texas A&M under DARPA XAI spans explainable interfaces, robustness evaluation with saliency maps, and human-grounded explanations that inform practical engineering design. He has a track record of shipping tooling and crowdsourced data pipelines from internships at Bosch to engineering prototypes for LiDAR annotation and analytic provenance visualizations. Comfortable across research and systems engineering, he blends rigorous empirical evaluation with deployable solutions that improve trust and dependability in open-world ML. Based in Campbell, California, he pairs deep domain knowledge with hands-on implementation experience across industry and academia.
code10 years of coding experience
job11 years of employment as a software developer
bookPhD in Computer Science, Explainable AI, Visual Anaytics, Human-AI Interaction, PhD in Computer Science, Explainable AI, Visual Anaytics, Human-AI Interaction at Texas A&M University
bookBachelor of Science (B.Sc.), Electrical and Electronics Engineering, Bachelor of Science (B.Sc.), Electrical and Electronics Engineering at University of Isfahan
bookMaster's degree, Electrical and Electronics Engineering, Master's degree, Electrical and Electronics Engineering at Babol Noshirvani University of Technology (NUT)
languagesEnglish, Persian
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Github Skills (20)

classifier10
interpretable-machine-learning9
cascade9
vision-transformer7
mscoco7
object-detection7
machine-learning6
pytorch6
transformer5
faster-rcnn5
swin-transformer5
mask-rcnn5
openmmlab4
instance-segmentation4
retinanet4

Programming languages (3)

JavaScriptHTMLPython

Github contributions (5)

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Reference tables to introduce and organize evaluation methods and measures for explainable machine learning systems
Contributions:15 commits, 14 pushes, 1 branch in 5 months
machine-learninginterpretable-machine-learningxai-evaluation
Contributions:17 commits, 14 pushes, 1 branch in 3 years 4 months
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