Vrinda Prabhu

Lead Data Scientist

Bengaluru, Karnataka, India
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Summary

👤
Senior
🎓
Top School
Vrinda Prabhu is a Lead Data Scientist based in Bengaluru with 10 years of experience building practical deep learning solutions, primarily in computer vision, and a growing interest in NLP. At Cimpress she has driven CV integrations to enhance customer design experiences, and earlier roles at Tata Elxsi include leading AI-on-Edge work that was recognized in NASSCOM and Tata InnoVista. She contributes to open-source ML datasets—adding regional and multilingual corpora (e.g., Kannada news, medical dialogues, COVID QA, and TIMIT ASR) to the Hugging Face datasets hub—reflecting a focus on real-world, multilingual data challenges. Comfortable across Python-driven ML stacks, she blends hands-on engineering with cross-functional collaboration and a continuous-learning mindset cultivated through active involvement in Machine Learning Tokyo.
code10 years of coding experience
job9 years of employment as a software developer
bookBachelor's degree, Electrical, Electronics and Communications Engineering, Bachelor's degree, Electrical, Electronics and Communications Engineering at BMS IT,VTU
languagesEnglish, Kannada, Hindi
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Github Skills (10)

machine-learning10
nlp10
python10
data-science10
datasets10
pytorch9
tensorflow9
pandas9
computer-vision8
speech8

Programming languages (3)

JavaScriptJupyter NotebookPython

Github contributions (5)

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huggingface/datasets

Dec 2020 - Mar 2021

🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
Role in this project:
userML Engineer & Data Scientist
Contributions:5 reviews, 5 commits, 4 PRs in 2 months
Contributions summary:Vrinda contributed to the Hugging Face datasets repository by adding several new datasets focused on machine learning tasks. This involved creating dataset scripts for Kannada news classification, medical dialogue (Chinese and English), and COVID QA (Chinese and English). Their work includes data card creation, README updates, and the integration of datasets from external sources like Kaggle and UC San Diego. The user also worked on incorporating the TIMIT ASR dataset.
ml-modelstensorflownatural-language-processingmanipulationdata-science
Contributions:28 commits, 27 pushes, 1 branch in 1 day
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