Swachhand Lokhande
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolSwachhand Lokhande is a software engineer with 11 years of experience, currently based in San Francisco and completing an MSE in Computer and Information Science at the University of Pennsylvania. He focuses on machine learning, distributed systems, and practical software development, blending research rigor with production-oriented engineering. His open-source work includes substantive backend and ML contributions to TensorFlow—improving op documentation, fixing XLA compilation bugs, and refactoring compilation cache and device compiler components. A strong academic foundation from VJTI (B.Tech, 8.99/10) complements hands-on systems experience, enabling him to tackle both algorithmic and low-level infrastructure challenges. Notably, he combines attention to documentation and developer ergonomics with deep technical changes, a mix that helps bridge usability and performance in large ML codebases.
11 years of coding experience
HSC, Computer Science, 196/200, HSC, Computer Science, 196/200 at Bhavans CollegeBachelor of Technology (B.Tech.), Computer Engineering, CGPA - 8.99/10, Bachelor of Technology (B.Tech.), Computer Engineering, CGPA - 8.99/10 at Veermata Jijabai Technological Institute (VJTI)Master of Science in Engineering, Computer and Information Science, CGPA - 4.0/40, Master of Science in Engineering, Computer and Information Science, CGPA - 4.0/40 at University of Pennsylvania
Marathi, Hindi, English
Github Skills (11)
mle10
xla10
machine-learning10
deep-learning10
tensorflow10
python10
linear-algebra10
ml10
documentation8
cprogramming-language7
c-language7
Programming languages (2)
Github contributions (5)
tensorflow/tensorflow
Sep 2022 - Jan 2023
An Open Source Machine Learning Framework for Everyone
Role in this project:
Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:7 reviews, 30 commits, 17 comments in 4 months
Contributions summary:Swachhand contributed to improving the documentation and implementation of several TensorFlow operations, focusing on enhancing documentation for functions such as `tf.nn.gelu` and `tf.nn.ctc_loss`. Their contributions extended to addressing critical issues related to the XLA compilation process, including bug fixes for uninitialized variables within depthwise pooling operations. Furthermore, the user was involved in introducing and refactoring classes related to the XLA compilation cache and device compiler, which involved significant changes to the project's underlying architecture.
pythondata-sciencedeep-learningmlmachine-learning
swachhandl/tensorflow
Sep 2022 - Sep 2022
An Open Source Machine Learning Framework for Everyone
Contributions:1 push in 1 day
pythondata-sciencedeep-learningmachine-learningframework-learning
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