Bhavan Vasu is a computer vision and machine learning researcher with eight years of experience applying explainable AI, interactive ML, and domain adaptation to imagery from satellites to Mars. Currently a Graduate Research Assistant at Oregon State University and a PhD candidate, he specializes in interpretable temporal models, image generation/translation, and neural network probing and pruning. His work spans academia, industry, and government labs — including Kitware and JPL — where he augmented model interpretability for mission imagery and published on Mars-relevant instrumentation. Comfortable bridging algorithm research and practical systems, he brings embedded-sensor and time-series experience alongside deep expertise in change detection, object localization, and remote sensing. Notably, he pairs rigorous statistical modeling with hands-on engineering to make ML systems more transparent and operational in real-world imaging pipelines.
8 years of coding experience
4 years of employment as a software developer
Master of Science - MS, Computer Engineering, Master of Science - MS, Computer Engineering at Rochester Institute of Technology
Associate of Science - AS, Science, Associate of Science - AS, Science at JAIN College
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Oregon State University
Bachelor of Engineering - BE, Electrical, Electronics and Communications Engineering, Bachelor of Engineering - BE, Electrical, Electronics and Communications Engineering at Global Academy Of Technology
This repository contains the python code for a Siamese neural network to detect changes in aerial images using Tensorflow.
Contributions:26 commits, 42 pushes, 1 branch in 1 year 5 months
neural-networkpythontensorflow
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