Luyao Peng is a data scientist at ACTNext. She received her PhD in Applied Statistics from University of California, Riverside. She received her masters degree in Linguistics and Applied Linguistics from Beijing Language and Culture University, China.
During her PhD study, she was the lead author of the R package MMeM (Multivariate Mixed-effects Model) and developed a web application of applying Kernel Principal Component Analysis (KPCA) to detect abnormal responses in essays and paper-pencil examinations.
At ACTNext, she works in the Automated Scoring team and conducts innovative research for CRASE— ACT’s automated scoring engine. Her research focused on computational linguistics that applying both deep learning methods and statistical theories into the realm of Natural Language Processing (NLP). Specifically, she builds new algorithms to automatize essay scoring, detect cheating behaviors in examinations and to perform different variety of NLP tasks such as sentiment analysis/classification, question answering and topic modeling.
Contact: pengl (at) act.org