Fabiana Clemente
Senior Director - Distinguished Engineer at AI Infrastructure Alliance
San Francisco, California, United States
Summary
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Rockstar🎓
Top SchoolFabiana Clemente is a senior technology leader and Distinguished Engineer with 8+ years of experience building data-centric AI and production-grade generative systems. Currently leading the Synthetic Data Center of Excellence at KPMG US and serving as CTO at YData, she specializes in synthetic data generation, data quality tooling, and privacy-preserving GenAI architectures for regulated industries. She combines an applied-math and forecasting background with hands-on engineering — contributing core features to popular open-source projects like ydata-profiling and implementing GAN/CGAN models in ydata-synthetic. Fabiana mentors large engineering teams, drives product and platform design, and champions a shift toward data-first ML through community leadership in the Data-Centric AI Community and AI Infrastructure Alliance. Notably, her work bridges research and production: she ships visualization and profiling improvements used by thousands of data teams while prototyping transformer-based retrieval and RAG patterns for structured data. Based in San Francisco, she focuses on practical, responsible ML that improves real-world model reliability.
8 years of coding experience
3 years of employment as a software developer
Master's degree Information management with a specialization in knowledge management and Business Intelligence, Master's degree Information management with a specialization in knowledge management and Business Intelligence at NOVA IMS Information Management SchoolMaster's degree Applied econometrics and forecasting, Master's degree Applied econometrics and forecasting at ISEG - Lisbon School of Economics & ManagementLicentiate degree Applied mathematics, Licentiate degree Applied mathematics at Faculdade de Ciências da Universidade de Lisboa
Stackoverflow
96reputation
1kreached
10answers
0questions
Github Skills (24)
python10
data-science10
pandas10
machine-learning10
exploratory-data-analysis10
generative-adversarial-network10
deep-learning10
tensorflow10
data-profiling10
synthetic-data10
data-analysis10
jupyter9
exploratory9
matplotlib9
time-series9
Programming languages (6)
Github contributions (5)
ydataai/ydata-synthetic
May 2020 - Oct 2022
Synthetic data generators for tabular and time-series data
Role in this project:
ML Engineer
ML EngineerContributions:82 reviews, 123 commits, 125 PRs in 2 years 5 months
Contributions summary:Fabiana implemented and added code for a CGAN (Conditional Generative Adversarial Network) and a GAN architecture within the `ydata-synthetic` repository. Their work included adding model files for CGAN and GAN, and also adding an example Jupyter Notebook to demonstrate the synthesis of tabular data using the credit fraud dataset. The user's commits focused on defining and training the generator and discriminator components of the GAN models, along with model saving functionality.
pythondata-generatorssynthetictime-seriesgan-architectures
ydataai/ydata-profiling
Mar 2022 - Jan 2023
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
Role in this project:Backend Developer
Backend DeveloperContributions:10 releases, 152 reviews, 29 commits in 10 months
Contributions summary:Fabiana contributed significantly to the `ydata-profiling` repository, focusing on enhancing the core data profiling and exploratory data analysis capabilities. Their work involved implementing a time-series heatmap visualization feature and refactoring existing plotting functionalities. Furthermore, the user made code modifications across multiple files, which included updates to the profile report generation logic, and enhancements to tests and overall code structure. These changes focused on improving the library's functionalities.
pythonjupyter-notebookpandas-profilingbig-data-analyticsstatistics
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