We are advised by Lifu Huang. Our team is named after our main intellectual merit, a large-scale multi-modal instructional knowledge graph, that guides the robot to execute a broad range of daily tasks. Our vision is to build a trustworthy partner to humans that is capable, intelligent, communicative, knowledgeable, and efficient.
Minqian L. — Team leader
Minqian is a first-year PhD student at the Computer Science department of Virginia Tech advised by Prof. Lifu Huang. He obtained his Bachelor's Degree in Computer Science at South China University of Technology. His primary research interests lie in the field of natural language processing and machine learning, including information extraction, continual learning and few/zero-shot learning for NLP, task-oriented dialogue system, and multimodal learning.
Ying S.
Ying is a PhD student of Computer Science at Virginia Tech. Ying's research interests lie in deep learning, natural language processing and multi-modal machine learning, the vibrant multi- disciplinary research field that focuses on integrating and modeling multiple communicative modalities, including linguistic, acoustic and visual messages. Ying's enthusiasm is to build more human-like interactive agents to better understand, interpret and reason about the world around us. Ying obtained a Master of Science degree in Intelligent Information Systems from Carnegie Mellon University and a Bachelor’s degree from School of Software Engineering, Fudan University.
Lifu Huang — Faculty advisor
Lifu Huang is an assistant professor of the Computer Science Department at Virginia Tech, where he leads the Natural Language Processing Lab. At VT CS, he is also a member of the Sanghani Center for Artificial Intelligence and Discovery Analytics.