Chien-Ming Huang, a John C. Malone Assistant Professor in the Department of Computer Science, studies human-machine teaming and creates innovative, intuitive, personalized technologies to provide social, physical, and behavioral support for people with a variety of abilities and characteristics, including children with autism spectrum disorders.
Huang directs Johns Hopkins’ interdisciplinary Intuitive Computing Laboratory and is a member of JHU’s Malone Center for Engineering in Healthcare and the Laboratory for Computational Sensing and Robotics. An expert in human-robot and human-computer interaction, Huang is particularly passionate about using novel technologies to help special-needs populations. Drawing on human-computer interaction (HCI), robotics, and artificial intelligence (AI), Huang’s research has significant applications in healthcare, education, and manufacturing.
His lab develops interactive robot systems that work cooperatively with people to increase task performance and enhance user experience. Specifically, Huang’s team focuses on deciphering human behavioral cues (e.g., eye gaze) for recognizing task intent, synthesizing intuitive robot behaviors to facilitate collaborative activities, and developing interfaces and methods for people to re-skill robots to perform custom tasks.
Huang, who joined the Hopkins faculty in 2017, has received several awards, including being named a prestigious John C. Malone Assistant Professor at JHU. In 2018, he was selected for the Association for Computing Machinery’s (ACM) Conference on Human Factors in Computing Systems (referred to as CHI) Early Career Symposium and its New Educators Workshop for the ACM’s Special Interest Group on Computer Science Education. As a PhD candidate, Huang received “Best Paper Runner-up” and “Best Student Poster Runner-up” honors at the 2013 Robotics: Science and Systems (RSS) conference and was named a 2012 Human-Robot Interaction (HRI) Pioneer.
Huang, a member of the Association for Computing Machinery, has published in Science Robotics and other top-tier journals and has received media coverage from MIT Technology Review, Tech Insider, Science News, and Science Nation. Huang is an associate editor for ACM Transactions on Human-Robot Interaction and guest editor for Frontiers in Robotics and AI “Towards Real World Impacts: Design, Development, and Deployment of Social Robots in the Wild.” In addition to numerous conference presentations, he served as a registration chair for the 2018 International Conference on Human-Robot Interaction, co-organized several conference workshops, including the 2018 RSS conference and the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems. He is also a frequent participant of conference program committees and reviewers of journals and conference papers and National Science Foundation proposals.
He received his BS in Computer Science (2006) at National Chiao Tung University in Taiwan, his MS in Computer Science (2010) at the Georgia Institute of Technology, and his PhD in Computer Science (2015) at the University of Wisconsin–Madison. He completed his postdoctoral research at Yale University.