I designed and built an end-to-end Retrieval-Augmented Generation (RAG) system to transform raw legislative text into validated, context-aware, and easily visualizable outputs.
Support a federal agency by helping them provide an enterprise approach to data and AI governance as well as provide recommendations on aligning investments and activities to an …
Support a federal agency by helping them utilize a MLOps platform, drafting guidance for governance policies, and piloting with a couple MachineLearning projects.
Dive into the complexities of building reliable AI models in high-stakes environments, where data integrity can mean the difference between success and unintended consequences.
Support federal agency staff with understanding evolutionary algorithms and adapting them for use within their environment.
As an individual contributor, I helped assess key steps to modernize a complex data engineering and analysis process built in Excel.
Leading an accelator program to kickstart companies interested in supporting the federal government.
A talk offered to the UMass Amherst Student Chapter of SIAM sponsored by the SIAM Visiting Lecturer series.
A talk offered to the Dublin Area Student Chapter of SIAM sponsored by the SIAM Visiting Lecturer series.
As the Project Lead, we supported CDC's efforts in upskilling their staff in a variety of data science competencies from time series regression to data wrangling to communicating …