Ryan Sander
Image Scientist at United States Department of Defense
Washington DC-Baltimore Area United States
Summary
👤
Senior🎓
Top SchoolRyan Sander is an Image Scientist with eight years of experience applying machine learning to real-world imaging problems, currently working at the U.S. Department of Defense out of the Washington DC–Baltimore area. An MIT CSAIL alum with BS and MEng degrees in EECS/AI and a background in mathematical economics, he blends rigorous theoretical training with practical systems experience. He also mentors aspiring researchers and consults on ML projects, translating complex ideas into teachable, deployable solutions. Known for a mission-driven focus, he seeks to make the world better through ML while navigating high-stakes, privacy- and security-conscious environments. Less obvious: his academic track record includes specialized deep learning theory study at Princeton and a near-perfect academic record, signaling both breadth and depth across research and engineering.
8 years of coding experience
Summer School, Deep Learning Theory, Summer School, Deep Learning Theory at Princeton UniversityBachelor of Science (BS), Electrical Engineering and Computer Science, Mathematical Economics, 5.0/5.0, Bachelor of Science (BS), Electrical Engineering and Computer Science, Mathematical Economics, 5.0/5.0 at Massachusetts Institute of TechnologyAdvanced Studies Diploma, Advanced Studies, 3.96/4.00, Advanced Studies Diploma, Advanced Studies, 3.96/4.00 at Lake Braddock Secondary
English, Spanish
Stackoverflow
449reputation
43kreached
21answers
0questions
Github Skills (48)
clustering10
reinforcement-learning9
convolutional-neural-networks9
parallel9
pytorch9
lda9
python9
large-language-models9
machine-learning9
deep-learning9
optimization9
computer-vision9
ray8
hyperparameter-optimization8
tensorflow8
Programming languages (5)
Github contributions (5)
rmsander/sparse-fusion-scene-seg
Nov 2019 - Aug 2021
Contributions:10 commits, 19 pushes, 1 branch in 1 year 9 months
rmsander/learning-machine_learning
Mar 2020 - Sep 2022
A repository for learning the fundamentals of machine learning through concepts, implementation, and real-world examples.
Contributions:6 reviews, 19 commits, 15 PRs in 2 years 6 months
machine-learningpythonnumpydeep-learningdata-science
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