Krishna Uppala
Research And Development Engineering Manager at Apple
Cupertino, California, United States
Summary
👤
Senior🎓
Top SchoolKrishna Uppala is a Research and Development Engineering Manager at Apple with eight years of experience applying deep learning and computer vision to real-world products and research. He progressed through hands-on roles from ML engineer to senior engineer and now leads R&D efforts, combining product-scale deployment experience with a strong research background in CV and sequential decision making. His early academic and lab work produced CVPR and ECCV spotlight contributions in depth estimation and adversarial methods, and he has implemented state-of-the-art text recognition models during AI residencies. Krishna also contributes to notable open-source tooling for adversarial robustness, maintaining compatibility across TensorFlow versions in the widely used CleverHans library. Based in Cupertino, he blends rigorous research instincts from Carnegie Mellon and IIT Guwahati training with pragmatic engineering practices for shipping robust ML systems.
8 years of coding experience
6 years of employment as a software developer
Bachelor of Technology (B.Tech.) Electrical and Electronics Engineering, Bachelor of Technology (B.Tech.) Electrical and Electronics Engineering at Indian Institute of Technology, GuwahatiComputer Science, Computer Science at Carnegie Mellon University
English, Hindi, Telugu
Github Skills (8)
machine-learning10
dep10
tensorflow10
deprecated10
python10
benchmarking8
benchmark8
security7
Programming languages (3)
Github contributions (5)
cleverhans-lab/cleverhans
Jul 2018 - Jul 2018
An adversarial example library for constructing attacks, building defenses, and benchmarking both
Role in this project:
ML Engineer
ML EngineerContributions:35 commits, 6 PRs, 43 comments in 25 days
Contributions summary:Krishna primarily contributed to the project by removing and addressing deprecation warnings related to TensorFlow functions, particularly `keepdims`. They refactored code in multiple files to maintain compatibility with different TensorFlow versions. Additionally, the user added warnings about future CleverHans version support for specific Tensorflow versions, highlighting a focus on maintaining and improving the library's robustness and compatibility within the machine learning domain.
benchmarkingrobustnessadversarial-machine-learningsecurityadversarial
feedforward/blog
Apr 2018 - May 2021
My Blog - summaries of some deep learning papers i have read.
Contributions:12 pushes, 1 branch in 3 years 1 month
pytorchmy-blogdeep-learningmachine-learningdeep-learning-papers
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