Over the past two years, I’ve focused on applying LLMs and related technologies to build complex multi-agent systems that support research and patient recruitment. I lead architecture and implementation of the backend for Muse, a clinical trial recruitment tool developed in partnership with Sanofi and OpenAI.

Beyond general web application development in Python and TypeScript (React, NestJS), I’ve worked across the AI/ML stack: from computer vision for state-of-the-art data extraction in scientific literature, to multi-agent systems for complex decision-making and agentic web scraping.

Automated, optimized, and expanded upon system for transforming vast amounts of hospital data from disparate sources into the OMOP Common Data Model, facilitating the data's use in MSK's cancer research, as well as writing RESTful APIs to facilitate interaction between terminology-focused graph databases with other internal applications.

Contributed on the front and back end to the development of two key applications within Omni, the Marketing Science and Data software suite used across agencies within Annalect’s parent company Omnicom Media Group. Both applications used Python 3 with Flask for an API driving an AngularJS front-end.

Applied Python 3 (including common DS/ML Python packages such as scikit-learn, numpy, Pandas) SQL (Redshift/PSQL), JavaScript (AngularJS), HTML, CSS, Docker, and AWS (Batch, Lambda, Redshift, S3).