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https://github.com/ledell/ledell


https://github.com/ledell/ledell

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README

          

### Hi there 👋

I am the Chief Scientist at [Distributional](https://distributional.com), where we're building an automated analytics and testing platform for LLM and Agentic AI applications. I am also the founder of [DataScientific, Inc.](https://datascientific.com), an AI Advisory and Consulting firm specializing in the development and implementation of cutting-edge AI solutions. Previously, I was the Chief Machine Learning Scientist at [H2O.ai](https://h2o.ai), a leading AI company known for producing [H2O](https://github.com/h2oai/h2o-3), an open source, distributed machine learning platform, along with Driverless AI, h2oGPT, LLMStudio, and a range of other Enterprise AI systems. My tenure at H2O.ai was marked by the creation and leadership of the development team for the [H2O AutoML](http://docs.h2o.ai/h2o/latest-stable/h2o-docs/automl.html) algorithm (the first open source enterprise AutoML platform), where I also spearheaded efforts in explainable/interpretable AI, algorithmic fairness and AI benchmarking and measurement.

Additionally, I am the founder of [WiMLDS (Women in Machine Learning and Data Science)](https://github.com/wimlds) and a co-founder of [R-Ladies Global](https://github.com/rladies), both organizations aimed at promoting diversity and inclusion in the AI field. I also collaborate with the [OpenML](https://github.com/openml) organization to develop open source benchmarking tools for machine learning, including the industry standard benchmark for AutoML systems (AMLB).

#### Selected open source software contributions 📦

Author or co-author:

- [H2O](https://github.com/h2oai/h2o-3): Scalable Machine Learning & AutoML Platform
- [H2O AutoML Wave App](https://github.com/h2oai/wave-h2o-automl): Wave App (web GUI) for H2O AutoML (Python)
- [h2o4gpu](https://github.com/h2oai/h2o4gpu/tree/master/src/interface_r): R interface for H2O4GPU, machine learning on GPUs
- [rsparkling](https://github.com/h2oai/sparkling-water/tree/master/r): R interface for H2O Sparkling Water, machine learning on Spark
- [OpenML AutoML Benchmark (AMLB)](https://github.com/openml/automlbenchmark): Benchmarking Framework for AutoML tools (Python)
- [cvAUC](https://github.com/ledell/cvAUC): Computationally efficient confidence intervals for CV AUC estimates in R
- [subsemble](https://github.com/ledell/subsemble): R package for ensemble learning on subsets of data
- [SuperLearner](https://github.com/ecpolley/SuperLearner): R package for Super Learning (Stacked Ensembles)
- [meetupr](https://github.com/rladies/meetupr): R interface to the meetup.com API
- [rHeathDataGov](https://github.com/rOpenHealth/rHealthDataGov): R interface to the HealthData.gov Data API

#### Selected keynote presentations 👩🏻‍🏫

- [AutoML Conf 2025](https://github.com/ledell/automl-2025-keynote/): Towards Automated Evaluation of LLM Applications
- [R/Medicine 2025](https://github.com/ledell/rmedicine-2025-keynote/): Model Evaluation: From ML to GenAI
- [JuliaCon 2022](https://github.com/ledell/juliacon-2022-keynote): APIs & Community: Building for Success
- [NeurIPS 2021](https://github.com/ledell/neurips-2021-keynote): Towards Responsible ML Benchmarking
- [useR! 2020](https://github.com/ledell/useR2020-automl): Responsible Automation: Towards Interpretable & Fair AutoML
- [LatinR 2019](https://github.com/ledell/LatinR-2019-keynote): Scalable Automatic Machine Learning in H2O