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Building AI agent analytics
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Building AI agent analytics
997 followers · 31 following

Achievements

Achievement: Pair Extraordinairex2Achievement: QuickdrawAchievement: YOLOAchievement: Arctic Code Vault ContributorAchievement: Pull Sharkx3Achievement: Starstruckx2

Achievements

Achievement: Pair Extraordinairex2Achievement: QuickdrawAchievement: YOLOAchievement: Arctic Code Vault ContributorAchievement: Pull Sharkx3Achievement: Starstruckx2

Organizations

@rOpenHealth @wimlds @BerkeleyBiostats @rladies

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ledell/README.md

Hi there 👋

I am the Chief Scientist at Distributional, where we're building an automated analytics and testing platform for LLM and Agentic AI applications. I am also the founder of DataScientific, Inc., 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, a leading AI company known for producing H2O, 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 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) and a co-founder of R-Ladies Global, both organizations aimed at promoting diversity and inclusion in the AI field. I also collaborate with the 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: Scalable Machine Learning & AutoML Platform
  • H2O AutoML Wave App: Wave App (web GUI) for H2O AutoML (Python)
  • h2o4gpu: R interface for H2O4GPU, machine learning on GPUs
  • rsparkling: R interface for H2O Sparkling Water, machine learning on Spark
  • OpenML AutoML Benchmark (AMLB): Benchmarking Framework for AutoML tools (Python)
  • cvAUC: Computationally efficient confidence intervals for CV AUC estimates in R
  • subsemble: R package for ensemble learning on subsets of data
  • SuperLearner: R package for Super Learning (Stacked Ensembles)
  • meetupr: R interface to the meetup.com API
  • rHeathDataGov: R interface to the HealthData.gov Data API

Selected keynote presentations 👩🏻‍🏫

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  1. h2oai/h2o-3 h2oai/h2o-3 Public

    H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K…

    Jupyter Notebook 7.5k 2k

  2. phd-thesis phd-thesis Public

    My UC Berkeley Ph.D. dissertation (2015).

    9

  3. h2oai/h2o-automl-paper h2oai/h2o-automl-paper Public

    H2O AutoML paper

    R 5 3

  4. openml/automlbenchmark openml/automlbenchmark Public

    OpenML AutoML Benchmarking Framework

    Python 451 146

  5. h2oai/awesome-h2o h2oai/awesome-h2o Public

    A curated list of research, applications and projects built using the H2O Machine Learning platform

    390 75

  6. automl-2025-keynote automl-2025-keynote Public

    AutoML Conf 2025 Keynote