Christopher Hamill is an assistant research engineer in ETS’s Natural Language Processing (NLP) Artificial Intelligence (AI) lab. He received an M.A. in language testing (with distinction) from Lancaster University (Lancaster, United Kingdom) in 2016, an M.A. (summa cum laude) in linguistics with a graduate certificate in cognitive science from the University of Colorado at Boulder in 2012, and a B.A. in Asian studies with minors in linguistics and Korean language and literature from the George Washington University in 2009.
Hamill’s current work focuses on automated content scoring and feedback generation using deep neural models. In the past, he has also done considerable data engineering work as well as deep learning model building and evaluation using the SpeechRater® automated scoring service as part of efforts to develop novel key points detection capabilities for use with TOEFL iBT® test items. Prior to joining the NLP AI Lab, Hamill’s work at ETS involved applied linguistics research into standard setting, test validity, and score reporting for the TOEFL® test, the TOEIC® test, and K–12 populations.