I am a seasoned Applied Machine Learning Research Scientist/data scientist/Engineer leader. My expertise is in building Statistical/Machine Learning models(Bayesian and Frequentist Modeling techniques) to help the business realize its data journey. Currently work for h2o.ai as the Lead Machine Learning Scientist/Engineer, exploring and figuring out possibilities of generative AI one commit at a time.
- Also, exploring and helping improve ways to evaluate LLM models
- I'm currently leading efforts on LLM2SQL assistant for QnA on structured tabular data using SQL generation, https://github.com/h2oai/sql-sidekick
- Fun project with LLMs for image generation, https://github.com/h2oai/wave-image-styling-playground
- Responsible for Model Analyzer, a unified interactive framework for simulation (What-If scenarios) and adversarial robustness to continuously explore and evaluate predictive model's behavior and limitations.
- Responsible for building (including driving cross-organizational product and business strategies) AutoInsights under the guidance of Dr. Leland Wilkinson (Chief Scientist). AutoInsights is an automated self-service AI/ML system designed to discover hidden insights (auto EDA) and publish them as interactive, engaging, and actionable insights using natural language narratives.
- Responsible for driving ML innovation/product and business strategies to improve the model interpretation ideas in h2o Driverless AI MLI.