I am a Ph.D. student in the Department of Computer Science at North Carolina State University. I graduated from Furman University in Greenville, South Carolina with a B.S. in both Mathematics and Computer Science. Although I am originally from South Carolina, I also spent five years living in Clermont-Ferrand, France.

Throughout my time at Furman, I developed an interest in the broad area of artificial intelligence, which is my primary research interest. I enjoy exploring the many applications of machine learning, and I am also interested in the mathematical theory that goes behind it. My work currently focuses on machine learning applications in educational technologies, such as intelligent tutoring systems and game-based learning environments. I am particularly interested in statistical methods that can overcome the challenges of small datasets, such as Bayesian analysis. I am also interested in multimodal data streams, such as sensor data and language. Outside of academics and research, I enjoy spending time outdoors, watching and playing sports, reading, and exercising.

Education

Ph.D., Computer Science (currently enrolled)
North Carolina State University, Raleigh, NC

M.S., Computer Science (2019)
North Carolina State University, Raleigh, NC

B.S., Computer Science and Mathematics (2017)
Furman University, Greenville, SC

Honors

NCSU Dean’s Doctoral Fellowship (2017-2018)
Furman Bell Tower Scholarship (2013-2017)
Member: Pi Mu Epsilon, Upsilon Pi Epsilon, Furman Shucker Leadership Institute

Publications

Andrew Emerson, Andy Smith, Fernando Rodríguez, Eric Wiebe, Bradford Mott, Kristy Elizabeth Boyer, and James Lester. Cluster-Based Analysis of Novice Coding Misconceptions in Block-Based Programming. To appear in Proceedings of the Fifty-First ACM Technical Symposium on Computer Science Education, Portland. [PDF]

Michael Geden, Andrew Emerson, Jonathan Rowe, Roger Azevedo, and James Lester. Predictive Student Modeling in Educational Games with Multi-Task Learning. To appear in Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, New York. [PDF]

Nathan Henderson, Andrew Emerson, Jonathan Rowe, and James Lester. Improving Sensor-Based Affect Detection with Multimodal Data Imputation. Proceedings of the Eighth International Conference on Affective Computing and Intelligent Interaction, pp. 669-675, Cambridge, England. [PDF]

Andrew Emerson, Andy Smith, Cody Smith, Fernando Rodríguez, Wookhee Min, Eric Wiebe, Bradford Mott, Kristy Elizabeth Boyer, and James Lester. Predicting Early and Often: Predictive Student Modeling for Block-Based Programming Environments. Proceedings of the Twelfth International Conference on Educational Data Mining, pp. 39-48, Montreal, Canada, 2019. [PDF]

Andrew Emerson, Robert Sawyer, Roger Azevedo, and James Lester. Gaze-Enhanced Student Modeling for Game-based Learning. Proceedings of the Twenty-Sixth ACM Conference on User Modeling, Adaptation and Personalization, pp. 63-72, Singapore, 2018. [PDF]