Sainandan Ramakrishnan
Software Engineer at Applied Intuition
San Francisco Bay Area United States
Summary
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Senior🎓
Top SchoolSainandan Ramakrishnan is a software engineer in the San Francisco Bay Area with eight years of experience applying deep learning to multi-modal computer vision problems. He has driven production-grade perception work at NVIDIA—building multi-sensor, distributed training and on-car DNN pipelines for autonomous vehicles—and now contributes to Applied Intuition’s tooling for AV development. His background blends strong academic research (NeurIPS publication, Georgia Tech MS with a 4.0 GPA) with hands-on systems engineering, from large-scale data processing to model release in embedded environments. He has proven expertise in reducing dataset bias and integrating language-vision compositionality from his CV/ML research, a perspective he brings to practical perception products. Known for bridging research and deployment, he excels at turning novel multi-modal ideas into robust, scalable models for real-world vehicles.
8 years of coding experience
8 years of employment as a software developer
Master of Science - MS, Computer Engineering, 4.0/4.0 ( suma cum laude ), Master of Science - MS, Computer Engineering, 4.0/4.0 ( suma cum laude ) at Georgia Institute of TechnologyBachelor of Technology - BTech, Electronics Engineering, 9.14/10, Bachelor of Technology - BTech, Electronics Engineering, 9.14/10 at Veermata Jijabai Technological Institute (VJTI)
English, Hindi, Marathi, TamilGithub contributions (3)
sainandan-ramakrishnan/Deep-Generative-Filter-for-motion-deblurring
Sep 2017 - Oct 2017
Contributions:5 commits, 4 pushes, 1 branch in 2 days
sainandan-ramakrishnan/Compositional-VQA-classifiers
Oct 2017 - Jan 2018
Contributions:26 pushes, 1 branch, 1 comment in 3 months
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