Aarsh Chaube
Graduate Teaching Assistant
City of Edinburgh, Scotland, United Kingdom
Summary
🤩
Rockstar🎓
Top SchoolAarsh Chaube is a PhD candidate in Computing Systems Architecture at the University of Edinburgh with six years of industry and research experience focused on ML compilers, hardware-aware deployment, and efficient execution of large language and vision models on constrained devices. He blends compiler engineering and computer vision expertise from UCL to tackle program synthesis, transpilation, and porting legacy code to new hardware, with hands-on work integrating backends like TVM, TensorRT, JAX, and ONNX. In industry roles he led testing, QA, and CI/CD for graph compiler binaries, accelerated Ivy’s testing pipeline up to 3x, and built ML systems for blockchain security at Moralis. An active open-source contributor, his Ivy commits improved multi-backend dtype handling and op converters, reflecting a pragmatic focus on reproducible, backend-agnostic tooling. Colleagues know him for marrying rigorous property-based testing with performance optimization and for translating research ideas into deployable engineering solutions.
6 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy - PhD Institute of Computing Systems Architecture, Doctor of Philosophy - PhD Institute of Computing Systems Architecture at The University of EdinburghHigh School, High School at Delhi Public School - IndiaBachelor of Technology - BTech Computer science-Big data, Bachelor of Technology - BTech Computer science-Big data at SRM IST ChennaiUniversity College London
Github Skills (9)
ivy10
python10
numpy10
tensorflow9
jax9
pytorch9
deep-learning8
machine-learning8
deeplearning-ai8
Programming languages (8)
Github contributions (5)
ivy-llc/ivy
Apr 2022 - Jan 2023
Convert Machine Learning Code Between Frameworks
Role in this project:
Back-end Developer
Back-end DeveloperContributions:202 reviews, 599 commits, 385 PRs in 9 months
Contributions summary:Aarsh's commits primarily focus on modifying the data type handling within the core Ivy library. Their contributions include refactoring and reformatting the `astype` and `trace` functions. These changes involved implementing type conversion methods for different backends (Jax, NumPy, TensorFlow, and PyTorch) and enhancing documentation and examples.
pythontensorflowframework-learningtemplatedata-science
Aarsh2001/Aarsh2001
Jan 2023 - Feb 2023
Contributions:29 commits, 37 pushes, 1 branch in 1 month
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