Gabriel Schubiner, MEng
Gabriel Schubiner, MEng, is a data engineer for the Data, Informatics and Sharing of Knowledge (DISK) team within the Center for Strategic Data Initiatives (SDI) as well as the Innovation Engineering team within the Center for Data Analytics, Innovation and Rigor at the Child Mind Institute. Gabriel earned a bachelor’s degree in computer science from Columbia University and a master’s degree in computer science and engineering from the University of Washington.
Gabriel previously worked in research engineer roles at Carnegie Mellon University and Google Research. Their work for those organizations combined diverse research and machine learning applications, ranging from spoken dialogue systems to multimodal reinforcement learning and applications of large-language models.
Gabriel has a strong background in artificial intelligence, natural language processing, and data infrastructure. They are passionate about building stable infrastructure to promote impactful, reliable research and aim to create positive and ethical advances through their work. Gabriel will be leading data extraction, transformation, and loading (ETL) processes for the Child Mind Institute’s data sharing initiatives.
Education
- MEng, Computer Science and Engineering, University of Washington
- BA, Computer Science, Columbia University
