Vinson Zheng
Undergraduate Research Assistant (Engineered Microstructures And Radiation Effects Laboratory)
New York City Metropolitan Area United States
Summary
👤
Senior🎓
Top SchoolVinson Zheng is an Engineering Science student at Stony Brook University advancing into an accelerated master’s program with a focus on materials science, ceramics, and high-temperature materials for fusion reactors. He combines hands-on materials processing and microstructural characterization in EMREL with applied R&D experience from DARPA/DoD projects at Physical Sciences Inc. and field compliance work in environmental safety, giving him a rare blend of lab-scale materials expertise and real-world regulatory practice. Vinson also contributes to machine learning projects on GitHub—working on semantic segmentation training and reproducibility—which complements his experimental work with data-driven analysis skills. A two-time NASA L’SPACE participant, he has practical systems-level experience in mission concept and thermal engineering, and has helped secure competitive funding for team proposals.
8 years of coding experience
1 year of employment as a software developer
High School Diploma, High School Diploma at Valley Stream Central High SchoolBachelor of Engineering - BE, Engineering Science, Bachelor of Engineering - BE, Engineering Science at Stony Brook University
Github Skills (5)
semantic-segmentation10
computer-vision10
tensorflow10
python10
machine-learning9
Programming languages (4)
Github contributions (5)
GeorgeSeif/Semantic-Segmentation-Suite
Mar 2018 - Mar 2018
Semantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily!
Role in this project:
ML Engineer
ML EngineerContributions:18 commits, 2 PRs, 8 comments in 9 days
Contributions summary:Vinson primarily contributed to the training and evaluation process of semantic segmentation models within the TensorFlow framework. Their commits focused on correcting typos, improving validation image handling, and merging updates from the upstream repository. The changes include code adjustments for managing validation images, setting random seeds for reproducibility, and calculating training time.
trainsemantic-segmentationdeep-learningsemantic-segmentation-modelstensorflow
Spritea/Context-Aggregation-Network
Apr 2019 - Dec 2019
Context aggregation network for semantic labeling in aerial images.
Contributions:15 commits, 1 PR, 11 pushes in 8 months
aggregationdeep-learninglabelingsemantic-labelingaerial
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