Everaldo Aguiar is a part-time lecturer at in the Khoury College of Computer Sciences at Northeastern University’s Seattle campus. He received his PhD from the University of Notre Dame, where he was affiliated with the Interdisciplinary Center for Network Science & Applications.
His PhD research focused on the development, deployment, and evaluation of machine learning models to detect, ahead of time, students that may be at risk of underachieving their academic goals. He was a fellow at the Eric & Wendy Schmidt Data Science for Social Good Fellowship, and a visiting researcher at the Center for Data Science and Public Policy at the University of Chicago, where through a variety of partnerships with large school districts, he was able to incorporate his predictive models to early warning systems that continuously monitor hundreds of thousands of students, informing educators when individual attention to a particular student may be needed.
He now works as a data scientist at Concur Technologies, where his research work is being leveraged and applied to highly complex and extremely large datasets. Some of his recent projects involved the development of predictive models that extract important token values from receipt images, and lightweight machine learning approaches to matching receipt images to their corresponding credit card feeds in real time.