Daniel Schweigert is a Senior Scientific Data Engineer in the AMDD department at TRI. He works on the data pipeline architecture for the matr.io platform as well as on the training and deployment of predictive machine learning models.
Daniel Schweigert graduated with a MS in Physics from the Freie Universität Berlin. Prior to joining TRI he has worked on inorganic thin film devices for photovoltaic and optical applications. During his career, Daniel has gained valuable experience in high througput material screening and in warehousing of large scale material and experiment data sets.