As we build and transition into the autonomous future, it is critical to place people at the center of our technological innovations. These technologies must be designed for users from the ground up, and how they will be used must shape the research of such technology. Human-computer interaction must take a leadership role in ensuring that the technology introduced into our world is usable, safe and secure—and promotes a better society.

At Johns Hopkins, HCI research is highly multidisciplinary, with relevant faculty spread across areas within Computer Science, as well as other departments in the Whiting School of Engineering, the School of Medicine, the Bloomberg School of Public Health, the School of Nursing, and the Applied Physics Laboratory.

Research Groups and Labs

Advanced Robotics and Computationally AugmenteD Environments Lab

The ARCADE Lab develops collaborative intelligent systems that support clinical workflows to increase access to—and expand the possibilities of—highest-quality health care. In designing these systems, they pioneer human-centered solutions that are enabled by synergistic advancements across imaging, computer vision, machine learning, and interaction design and that are embodied in emerging technology such as mixed reality and robotics.

Intuitive Computing Laboratory

The Intuitive Computing Laboratory focuses on designing and building intuitive interaction capabilities for computing and robotics technologies to be integrated into human environments to enhance supported task performance and user experience.

Laboratory for Computational Sensing and Robotics

The LCSR’s mission is to create knowledge and foster innovation to further the field of robotics science and engineering. The center’s researchers see robotics as an essential link between computation and action that enhances the health, safety, and efficacy of humanity.

Malone Center for Engineering in Healthcare

The Malone Center for Engineering in Healthcare brings together engineers, clinicians, and care providers who are leveraging data analytics in novel ways, pioneering new technologies, and applying systems engineering principles to speed the deployment of research-based innovations that will enhance the efficiency, effectiveness, and consistency of health care.

Putting users at the center of explainable AI development

In new commentary, researchers explain why developers must tailor AI systems and algorithms to their intended users.