This taskbot's vision is to be able to guide customers through a variety of tasks in a natural manner.
Our taskbot will keep track of conversations and use context-specific communication strategies to accomplish the task effectively while keeping customers engaged. Our system will handle clarification questions and naturally resolve any ambiguities that may arise during a conversation.
Rich Magnotti - Team leader
Magnotti is a second year PhD student in Computer Science at Rutgers University. His research is in natural language processing, planning and plan recognition in multi-modal conversational systems. Specifically, he is interested in creating socially cognizant conversational agents which make intelligent and context-aware decisions to establish common ground.
George is a Ph.D. student at Rutgers University. His research interest is to advance the field of VR/ MR/ AR through establishing common ground between virtual and human agents using Multi-Modal input and output. Before joining the Ph.D. program, he gained 5 years of experience in Software Development and Project Management, where he worked as a Delivery Lead, Architect, Lead Back End Developer, Business Analyst, and Project Manager.
Ji is a fourth-year PhD Student in Rutgers Univeristy. His advisor is Professor Yongfeng Zhang. His research fields are sequential recommendation, machine learning and logical reasoing. He gained knowledge graph related experience when he was a research intern.
Joo is a second year PhD student in Linguistics at Rutgers University. Her interest lies in phonetics and phonology, which explore how speech sounds are produced and perceived not only in human-human interaction, but also in human-computer interaction. Specifically, she focuses on how the phonetic details of intonation and prosody in languages influence speech production and perception.
Khalid is a PhD candidate at Rutgers University working under the supervision of Dr. Matthew Stone. His general research interests lie in the area of Natural Language Processing with key focus on how to build interactive systems which exhibit human-like behavior. Other than research some of his hobbies include solving programming problems, thinking about and experimenting with new ideas, playing games, and travelling with friends.
Li is a fourth-year Ph.D. student of Computer Science at Rutgers, advised by Professor Yongfeng Zhang. His research topics mainly focus on Automated Machine Learning (AutoML) for Recommendation Systems (RS). Duirng his Ph. D. he has done three projects in chronological order: (1) Non-Sampling Knowledge Graph Embedding Framework; (2) Explainable AI in Science Discovery; (3) Efficient Loss Function Search on Recommender Systems. He was a research scientist intern at Amazon in the summer of 2022 and will be returning to internship at Amazon in the summer of 2023.
Moe is a PhD student in Public a policy and Planning at Rutgers University. Her interdisciplinary work focuses on the integration of social impacts into research and design workflows, the regulation of emergent technology, and the construction of networks of association, community, and mutual obligation in a fragmented world.
Ravishankar is a third-year undergraduate student at Rutgers University studying Computer Science. Her previous experience includes backend software engineering at Google, Fidelity, Develop For Good, and the Robert Wood Johnson Hospital. Her interests include conversational AI, natural language processing, and data science. Ramitha is also interested in projects that develop AI ethically and responsibly with a convergence of Big Data for social good impact.
Yu is a third-year PhD student in the Department of Linguistics at Rutgers University. Her main research areas are in semantics and syntax. She enjoys using mathematical methods to represent the internal structure and meaning of natural languages under the superficial combination of words. Yu has specific interests in decomposing the semantics of the indefiniteness in nominal systems — including classifiers, demonstratives, anaphors, stripping (ellipsis), and how negation functions with indefinites.
Matthew Stone - Faculty advisor
Stone is a full professor and department chair, Rutgers CS. Received his PhD from Penn in 1998. Program chair, NAACL 2007. General chair, SIGDIAL 2014. Tutorial on multimodal dialogue at ACL 2020. Senior area chair for multimodality, COLING 2022. 50+ papers in NLP/AI/Linguistics conferences and journals.
Yongfeng Zhang - Faculty advisor
Zhang is an Assistant Professor in the Department of Computer Science at Rutgers University. His research interest is in Machine Learning, Machine Reasoning, Information Retrieval, Recommender Systems, Natural Language Processing, Explainable AI, and Fairness in AI. He has rich research experience on dialog systems, conversational search, conversational recommendation, language models, knowledge graph reasoning, and personalized agents. He serves as associate editor for ACM Transactions on Information Systems (TOIS), ACM Transactions on Recommender Systems (TORS), and Frontiers in Big Data. He is a Siebel Scholar of the class 2015 and an NSF career awardee in 2021.