Yugandhar Tripathi
SDE - II at Amazon
Lucknow, Uttar Pradesh, India
Summary
🤩
Rockstar🎓
Top SchoolYugandhar Tripathi is an inquisitive SDE-II at Amazon with eight years of hands-on experience building production software and research-driven prototypes across AR/VR, privacy-preserving ML, NFTs/smart contracts, and algorithmic trading. He combines core engineering at scale with open-source cryptography work—contributing to PySyft’s secure multi-party computation and precision-sensitive tensor operations—bringing practical privacy expertise to applied ML. A co-founder of an AR startup and long-time OpenMined contributor, he moves fluidly between R&D and delivery, shipping features and refactors that improve reliability and security. Based in Lucknow, he blends strong academic fundamentals (B.Tech CSE, 8.6 CGPA) with a penchant for detailed, reproducible implementations. Colleagues describe him as detail-oriented and curiosity-driven, often translating research concepts into usable code and documentation (including Hindi tutorials). He’s equally comfortable iterating on low-level tensor math as on product-facing AR/ML experiences.
8 years of coding experience
4 years of employment as a software developer
Bachelor of Technology, Computer Science, 8.6 CGPA, Bachelor of Technology, Computer Science, 8.6 CGPA at Jaypee Institute Of Information Technology
English, Hindi, German, French, Russian, Spanish, Japanese
Stackoverflow
571reputation
341kreached
8answers
0questions
validation
top-5%
Github Skills (20)
secure-computation10
pytorch10
operation10
python10
tensorrt10
deeplearning-ai10
deep-learning10
tensorflow10
federated-learning10
cryptography10
tensor10
validation9
php6
css6
docker6
Programming languages (10)
Github contributions (5)
OpenMined/PySyft
Aug 2019 - Apr 2020
Perform data science on data that remains in someone else's server
Role in this project:
ML Engineer
ML EngineerContributions:8 commits, 6 PRs, 1 push in 8 months
Contributions summary:Yugandhar primarily contributed to the core functionalities of the PySyft library, specifically focusing on privacy-preserving machine learning techniques. Their work includes modifying and refactoring code related to secure multi-party computation (SMPC), particularly within the context of additive sharing and the SecureNN protocol. The commits show enhancements to the underlying tensor operations and precision handling, which are crucial for encrypted computation. Additionally, the user has contributed to Hindi translation tutorials and addressed formatting concerns.
pytorchcryptographyacquiringpythonscience
Yugandhartripathi/jiit-network
Oct 2018 - Nov 2018
Contributions:22 commits, 4 PRs, 13 pushes in 1 month
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