Clinical ML Research, MD, and NLP/NLU Scientist focusing on building applications for clinical care. Believes that through context-driven engineering can transform the entire health system at a scale far greater than any number of clinic visits.
Experience as a Machine Learning Research Scientist and Health AI
- Improve performance of relationship extraction models for medical conditions, drugs, diagnostic tests, treatments and procedures.
- Boost Named-Entity Recognition model quality by scaling up entity-level annotation system.
Experience as a Deep Learning Senior Research Engineer
- Improved interpretability for BERT models by extending integrated gradients saliency implementation to support
- Created custom sub-domain vocabulary extension for pretrained Bert language models (biobert. pubmedbert) using
- Enabled extension of models to foreign languages using transfer learning/few-shot learning on translated text.
- Created guidelines, ontologies, label quality processes and metrics to improve ground truth quality from clinicians
multilabel classification for up to 60 labels with custom color map cycles.
private data to improve performance on in-domain downstream NER/Token classification tasks.
Masters in Medical Informatics and Computer Science and Healthcare Management certification from Yale School of Management. Currently working in ML scientist and healthcare AI at AWS.