Vinitra Swamy
CEO And Co-Founder at Scholé AI
Lausanne Metropolitan Area Switzerland
Summary
👤
Senior🎓
Top SchoolVinitra Swamy is a founder and AI researcher with 11 years of experience building production-grade ML infrastructure and education technologies; she currently leads Scholé, an EPFL/UC Berkeley spinoff focused on personalized upskilling for the AI era. With a PhD from EPFL on explainable, human-centric AI for personalized education and recognition as a “Rising Star in Data Science,” she bridges rigorous research (15+ publications at venues like NeurIPS and ICLR) with product execution. Previously she was a core engineer on Microsoft’s ONNX team, optimizing model interoperability and contributing key tooling and model migrations that improved deployment efficiency across Bing, Azure and Office. She also teaches GenAI at Harvard and has extensive experience scaling teaching operations—from leading Berkeley’s Data 8 GSI program to lecturing large classes—combining pedagogy with systems expertise. Known for moving models from research to robust production, she pairs deep ML systems knowledge with a passion for lifelong learning and scalable educational impact.
11 years of coding experience
7 years of employment as a software developer
Master of Science - MS Computer Science, Master of Science - MS Computer Science at University of California, BerkeleyDoctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at EPFL
Stackoverflow
285reputation
29kreached
10answers
0questions
Github Skills (23)
python10
scikit10
machine-learning10
onnx10
git-lfs10
cicd10
deep-learning10
scikit-learn10
model-conversion10
modeling10
testing9
keras9
version-control9
automation7
automations7
Programming languages (8)
Github contributions (5)
onnx/models
Jan 2019 - Sep 2020
A collection of pre-trained, state-of-the-art models in the ONNX format
Role in this project:
MLOps Engineer
MLOps EngineerContributions:28 commits in 1 year 8 months
Contributions summary:Vinitra's primary contribution was migrating large model files to Git LFS within the ONNX models repository. They added and configured Git LFS for various pre-trained models, including Alexnet, ResNet, VGG, and YOLO, as well as models from diverse areas like emotion recognition and machine comprehension. The user also addressed a batch normalization bug and updated CI/CD configuration. This work streamlined model management and improved the efficiency of the repository.
downloadpytorchartdeep-learningpre-trained
onnx/onnxmltools
Nov 2018 - May 2020
ONNXMLTools enables conversion of models to ONNX
Role in this project:ML Engineer
ML EngineerContributions:38 commits in 1 year 6 months
Contributions summary:Vinitra primarily contributes to the `onnxmltools` repository, focusing on converting machine learning models to the ONNX format. Their commits involve updating the library to support newer ONNX operator sets (opsets), specifically opsets 8, 9, and 10, which includes changes to core functions, tests, and operator converters for various machine learning models. They demonstrate a deep understanding of ONNX and the intricacies of model conversion, making adjustments to existing code to ensure compatibility and functionality with different ONNX versions. The user also refactors code and incorporates changes from related projects to maintain consistency.
python-librarypytorchdeep-learningmachine-learningonnx
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