Thanalakshan Sivarasa
Software Engineer at University of California, Los Angeles
Colombo, Western Province, Sri Lanka
Summary
🤩
Rockstar🎓
Top SchoolThanalakshan Sivarasa is a software engineer with 11 years of experience bridging electrical engineering foundations and practical ML-focused backend work. Based in Colombo, he brings a systems-thinking approach honed from an engineering degree at the University of Moratuwa and internships across WindForce, Trade Promoters, and Yarl IT Hub. An active contributor to the TensorLy project, he has strengthened tensor decomposition routines and test coverage, demonstrating attention to numerical robustness in scientific Python tooling. He blends hands-on QA and backend development with domain curiosity rooted in biological engineering concepts, reflecting interdisciplinary problem solving. Outside work he’s a cyclist and self-described nerd who applies the same iterative, data-driven mindset to team challenges and code quality.
11 years of coding experience
1 year of employment as a software developer
Bachelor of Science - BSc, Electrical Engineering, Bachelor of Science - BSc, Electrical Engineering at University of MoratuwaMaths, Maths at Jaffna Hindu College
English, Arabic
Github Skills (9)
tensorrt10
tensor10
python10
decomposition10
testing10
backend9
machine-learning9
mxnet8
pytest7
Programming languages (12)
Github contributions (5)
tensorly/tensorly
Jun 2020 - Jan 2023
TensorLy: Tensor Learning in Python.
Role in this project:
Back-end Developer & QA Engineer
Back-end Developer & QA EngineerContributions:99 reviews, 180 commits, 108 PRs in 2 years 7 months
Contributions summary:Thanalakshan primarily focused on updating and testing functions within the tensorly/decomposition library. They modified several test files, particularly related to the tucker and parafac decomposition methods. The user made adjustments to code related to the mxnet backend, including adding a test, and fixing a clip function. These changes show a focus on the robustness and correctness of the tensor decomposition methods.
tensor-factorizationtensor-decompositionpythontensor-learningtensor
meyer-lab/DE.jl
Jul 2020 - Dec 2020
The Julia solver for DE learning.
Contributions:70 PRs, 124 pushes, 73 branches in 5 months
solverjulia
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.