Emilio is a data scientist on the Research Computing and Data Services team, working with researchers across the university to advance data science projects and provide consulting. He also teaches workshops in SQL, Python, and R. His technical skills include web scraping, natural language processing (NLP), computer vision, and predictive and statistical modeling. He has collaborated on projects such as scraping job postings from diverse sources using local, high-performance computing (HPC), and cloud resources; extracting information with NLP techniques (including rules, entity recognition models, and large language models); extracting text from and searching over 410,000 PDF documents on an HPC cluster; and building a computer vision pipeline to calculate metrics from images and videos of medical procedures.
He holds a PhD in sociology and an MS in statistics from Northwestern University, with a research focus on the sociology of data and artificial intelligence. For his dissertation, Emilio investigated how companies have used machine learning since the mid-1990s, as well as the background behind popular open-source libraries. He also studied how Americans perceive the fairness of predictive automation in the context of credit scores, criminal justice, and hiring using an inductive, predictive approach.
Emilio also has a BA and MA in law, enriching his interdisciplinary interests and collaboration across various research domains. He reviews papers for Practice and Experience in Advanced Research Computing, has reviewed data science book proposals for Manning Publications, and completed internships at Meta and Slack, where he gained experience with large-scale data and creating production metrics. Emilio is certified in Mental Health First Aid and is passionate about spirituality, mindfulness, and yoga.