Atharva Khandait
Gothenburg, Sweden
Summary
🤩
Rockstar🎓
Top SchoolAtharva Khandait is a machine learning engineer with 9 years of hands-on experience building and deploying production ML systems, currently based in Gothenburg while pursuing an MS in Complex Adaptive Systems at Chalmers. He developed an LSTM-based unsupervised feature extractor and end-to-end pipeline at HDFC Bank that drives incremental monthly revenue of ~€311k, and has led MLOps and automation efforts on billion-point datasets. His background spans research-grade disentangled representation learning at IIT Bombay, video-based crowd analysis using ResNet, and low-level C++ ML contributions through Google Summer of Code and to the mlpack library. Comfortable in both Python and C++, he combines theoretical curiosity—having implemented and adapted research architectures—with practical deployment experience that reliably moves models from experiments to production.
8 years of coding experience
3 years of employment as a software developer
Indian Institute of Technology BombayMaster of Science - MS, Complex Adaptive Systems, Master of Science - MS, Complex Adaptive Systems at Chalmers University of Technology
English, Hindi, Marathi
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (6)
algorithms10
machine-learning10
k-nearest-neighbours10
c-language10
cprogramming-language10
testing10
Programming languages (2)
Github contributions (5)
mlpack/mlpack
Feb 2018 - Oct 2019
mlpack: a fast, header-only C++ machine learning library
Role in this project:
Back-end Developer
Back-end DeveloperContributions:99 commits, 21 PRs, 1 push in 1 year 8 months
Contributions summary:Atharva primarily contributed to the mlpack project by adding their name to the list of contributors. Additionally, they addressed issues and wrote tests related to the K-Nearest Neighbors (KNN) and K-Furthest Neighbors (KFN) search algorithms. The user implemented checks to ensure the validity of parameters such as the value of k, and leaf size, as well as making sure the dimensions of the matrices are correct.
regressionheaderdeep-learningscientific-computingc-plus-plus
akhandait/mlpack
Feb 2018 - May 2022
mlpack: a scalable C++ machine learning library --
Contributions:159 pushes, 34 branches in 4 years 3 months
scalabledeep-learningmachine-learningmachine-learning-librarylibrary-learning
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