Shi (Scott) Pu is Data Scientist II on AI and Machine Learning team at ACTNext. Prior to joining the team, he worked as a Data Scientist at Purdue University, building models to predict students’ retention and graduation, as well as the university’s course enrollment.
He obtained his Ph.D. degree in Higher Education from the Pennsylvania State University, his Master of Arts degree in Mathematics of Finance from Columbia University, and his Bachelor of Science degree in Computer Science from the National University of Singapore.
In general, Scott’s research interests lie in effectively using data and appropriate machine learning models to forecast student success and to automatically assess engagement. His current interest focuses on using deep learning to extract useful insights from students’ text and image data. Relating to this, he is also interested in designing and evaluating timely interventions that aim to aid at-risk students.
At ACTNext, His current works include (semi-) automatic generation of human-readable paragraphs and forecasting students’ performance in digital learning.
Contact: Scott.Pu (at) act.org