I’m broadly interesting in the interplay between neuroscience and machine learning, specifically around the fields of machine learning explainability, interpretability, and model monitoring. This includes keeping up to date with popular MLOps techniques and deployment strategies.

Right now, I work as a data scientist at IBM in the Watson AI for IT operations product. As part of the machine learning operations team, I examine how machine learning models perform in production and how we can monitor degradation of our productionized algorithms in real time, without ground truth.