Joyce Y. Chai

Computer Science and Engineering
3632 Beyster
University of Michigan
Ann Arbor, MI 48105
Office phone: 1-734-764-3308
Email: chaijy AT

Teaching  |  Research  Brief Bio   | SLED

My research interests are in the area of natural language processing, situated dialogue agents, human-robot communication, and artificial intelligence. I'm particuarly interested in language processing that is sensorimotor-grounded, pragmatically-rich, and cognitively-motivated. My recent work has focused on grounded language processing to facilitate situated communication with robots and other artificial agents. I'm a member of Michigan AI Lab and direct the Situated Langauge and Embodied Dialogue (SLED) research group . I am also affiliated with Michigan Robotics Institute.


EECS 692: Advanced Artificial Intelligence , Winter 2022

Exploration of advanced topics in Artificial Intelligence, especially in the intersection of language, vision, machine learning, planning, decision making, and cognitive modeling towards embodied AI agents that can communicate, learn, reason, and act. Emphasizes research methods and practice, through explicit instruction, analysis of current literature, replication of published findings. Coursework comprises extensive reading, research and writing assignments, presentations, and a term project.

EECS 595: Natural Language Processing, Fall 2021

The field of Natural Language Processing (NLP) is primarily concerned with computational models and computer algorithms to process human languages, for example, automatically interpret, generate, and learn natural language. In the past twenty years, the rise of the world wide web, mobile devices, and social media have created tremendous opportunities for exciting NLP applications. Recent advances in machine learning (e.g., deep learning) have also paved the way to tackle many NLP problems in the real world. This course provides an introduction to the state of the art in modern NLP technologies. In particular, the topics to be discussed include: syntax, semantics, discourse, deep learning for NLP, and their applications in information extraction, machine translation, and dialogue systems.

EECS 492: Introduction to Artificial Intelligence, Winter 2021

Introduction to the core concepts of AI, organized around building computational agents. Emphasizes the application of AI techniques. Topics include search, logic, knowledge representation, reasoning, planning, decision making under uncertainty, and machine learning.