Neha Patki
Co-Founder, SVP Of Product at DataCebo
Boston, Massachusetts, United States
Summary
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Rockstar🎓
Top SchoolNeha Patki is a product leader and AI researcher with 13 years of experience building data- and ML-driven products, currently serving as Co-Founder and SVP of Product at DataCebo in Boston. She combines hands-on AI research—authoring a patented algorithm for synthetic multi-table data at MIT—with product roles at YouTube and Google where she launched creator tools, analytics, and Trust & Safety features. An active open-source maintainer on sdv-dev (notably CTGAN/SDV), she bridges research, release management, and engineering by shepherding dependency updates, bug fixes, and production releases for synthetic data tooling. Neha is fluent in translating complex ML capabilities into user-centered product strategy and has a track record of shipping at scale across consumer and developer-facing platforms. Her background spans end-to-end delivery from patented algorithms to millions of users on Smart TV devices, reflecting both technical depth and operational rigor.
13 years of coding experience
6 years of employment as a software developer
Master of Engineering (MEng) Computer Science and Electrical Engineering, Master of Engineering (MEng) Computer Science and Electrical Engineering at Massachusetts Institute of TechnologyCupertino High School
English, Marathi, French
Stackoverflow
71reputation
536reached
3answers
0questions
Github Skills (15)
version-control10
data-generation10
release-management10
machine-learning10
python10
generative-adversarial-network10
generative-ai10
deep-learning9
pandas8
datatable7
tabular7
synthetic-data7
sdv6
synthetic6
google-colaboratory6
Programming languages (2)
Github contributions (5)
sdv-dev/SDV
Jul 2021 - Jul 2021
Synthetic data generation for tabular data
Role in this project:
ML Engineer
ML EngineerContributions:1 release, 38 reviews, 13 commits in 6 days
Contributions summary:Neha primarily contributed to the SDV library by updating dependencies related to core components like CTGAN, RDT, and SDMetrics, ensuring compatibility and incorporating the latest versions. They addressed bug fixes related to constraint implementation and improved documentation. Moreover, the user made version bumps for the SDV library, indicating their involvement in release management and potentially contributing to new feature releases.
relational-datasetssynthetictime-seriessynthetic-datamulti-table
sdv-dev/CTGAN
Jul 2021 - Jul 2021
Conditional GAN for generating synthetic tabular data.
Role in this project:Release Manager & Version Control
Release Manager & Version ControlContributions:1 release, 3 reviews, 9 commits in 5 days
Contributions summary:Neha primarily focused on managing the project's versioning and release process. They bumped the project's version multiple times, transitioning from development versions to a final release. The user also updated dependencies, specifically the version of the RDT package. Finally, the user merged branches to prepare for releases.
pytorchdeep-learningconditionaltabular-datagenerative-adversarial-network
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