Matt is the technical lead at GLUE. Wearing many hats, his role lies at the intersection of data engineering, data analysis, system administration, project management, and mentorship. He is responsible for the technical vision and growth of the lab's work in Brazil, hiring staff members and designing data solutions to expand the lab's research on land-use in one of the world's most ecologically important countries.

In his day-to-day activities, Matt oversees a team of academic staff that develop and maintain GLUE's data platform. Integrating socio-environmental information on rural properties in Brazil with animal health records that describe movements of cattle across the country, this product provides researchers with a clear picture of the Brazilian cattle sector fit for study. The platform also powers Visipec, a supply chain monitoring application used by meatpackers, and supplies key insights to federal prosecutors in Brazil responsible for enforcing the country's environmental laws.

In 2013, Matt received a B.S. in mathematics and linguistics with a certificate in computer science from the University of Wisconsin-Madison. He started working for the lab the same year as a student hourly processing relational data, becoming a full-time staff member shortly after. In 2015, Matt was accepted to the university's computer science graduate program with a focus on databases. While working towards his degree, Matt spent a summer in Seattle as a Software Development Engineering (SDE) intern at Amazon on the Prime team. This was a formative learning experience which gave him the opportunity to weigh a career in industry against one in scientific data; he chose the latter. Matt graduated in 2017 with an M.S. in computer science and returned to full-time work at the lab.

Outside of leadership and team skill-building, Matt's professional interests largely concern entity resolution, the problem of determining the real-world objects that data on disk describe. In 2018, Matt helped to obtain a Data Science Initiative grant, partnering with a professor from his graduate program to evaluate entity matching (EM) techniques over GLUE's data. This work used py_entitymatching, an open-source package bundling common EM methods which Matt maintained 2019-2021. In 2023, Matt gave a lightning talk at the university's Research Bazaar on using TF-IDF embeddings to efficiently find similar strings across database records.

In his personal life, Matt is very curious and enjoys learning about most things. He likes spending time outside with his wife and dog and delights in reading, dining, drawing, chatting over coffee, and making art with code.