Sungjin Nam

Sungjin Nam is a Senior Research Scientist specializing in Measurement Research and Development at ACT, with a focus on creating an automated essay scoring engine utilizing transformer models. Previously, Sungjin served as a Research Scientist II at Pearson, where the work involved developing autoencoder models and Bayesian networks to enhance personalized learning. Academic experience includes a PhD in Information Science from the University of Michigan, where research centered on deep learning applications in vocabulary systems and student behavior analysis. Additional roles include a Machine Learning Intern at Adobe and a PhD Research Intern at Echo360, Inc., contributing to predictive modeling and software development in educational contexts.