Benjamin Fenelon is a machine learning engineer on Kitware’s Computer Vision Team. He contributes his strong programming skills to develop robust solutions for real-world problems and is responsible for validating, optimizing, and deploying advanced algorithms.

Prior to joining Kitware, Ben worked as a graduate student researcher on a National Institute of Standards and Technology (NIST) project, where he utilized Large Language Models (LLMs) for self-supervised clustering of high-dimensional healthcare data. He also interned at Massachusetts General Hospital Lab in the Medical Analytics Group, where he prototyped an automated feature selection/engineering pipeline for radiomics data. Additionally, he served as a programmer for the University of Southern California on the Heartsteps 2.0 project, a Biomedical Image Processing and Machine Learning Co-op at MIT Lincoln Laboratory, and a Corporate Application Development Intern at ISO New England.

Ben has contributed innovative work on various projects. Notably, he engineered distributed model inference for a large-scale brain mapping project. He also researched the compatibility of fairness and privacy in the empirical malfare minimization framework.

Ben holds a Master’s degree in computer science and dual Bachelor’s degrees in computer science and mathematics from the University of Massachusetts Amherst. His honors thesis focused on the analysis of private path planning for UAVs in the context of differential privacy.