Andrew Hornback

Andrew is a PhD student in Computer Science specializing in Machine Learning and Interactive Intelligence. He is interested in Artificial Intelligence and Computational Biology. Prior to Georgia Tech, he did research in financial derivatives with Dr. Robert E. Whaley at Vanderbilt University.

Dalton Bassett

Dalton is a computer science master’s student at Georgia Tech. He joined DILab’s IBID project in December 2020 as a researcher and developer. His research interests include natural language processing, reading comprehension, and leveraging machine learning to increase access to information for everyone.

Jae Ro

Jae is a MS Computer Science student at Georgia Tech (specializing in Interactive Intelligence) currently working on the AI Business Model Canvas Assistant (Errol) project. He is passionate about exploring the potential Artificial Intelligence and Machine Learning have on transforming industries and augmenting human capabilities. Accordingly, his research interests lie in Natural Language Processing, Cognitive Computing, and Computational Creativity. In his free time, Jae enjoys playing basketball, hiking, and kayaking.

Aditi Dutta

Aditi Dutta is a Computer Science Masters student at Georgia Tech graduating in December 2020. She is the current lead developer on the Jill Watson project team at DILab focused on conducting research and development of an artificially intelligent agent that performs the role of a virtual teaching assistant on discussion forums for online courses. The agent, Jill, is designed to have the ability to answer online student queries related to the course syllabus and allows instructors the flexibility to customize Jill’s knowledge and skills. Aditi’s research interests lie in natural language understanding, artificial intelligence, and human-computer interaction. Aditi is an avid reader and loves all-things-math.

Preethi Sethumadhavan

Preethi is a master’s student in Computer Science (specializing in Machine Learning) at Georgia Tech. She recently joined DILAB and is currently working on Quantitative modelling in the VERA project. Her primary interests include Knowledge Based AI, Machine Learning and NLP.

Shan Jing

Shan is a researcher on the Jill Watson project. As a member of the JW team, she is studying human-AI interaction in learning context and how AI technology can serve a better role and co-evolve in this ecosystem. Currently, Shan is pursuing a Master’s degree in Computer Science (specializing in Human Computer Interaction) at Georgia Tech.