Human-computer interaction (HCI) research centers on designing technologies that serve people first.
We study how individuals and groups engage with digital systems and translate these insights into the design of more usable and accessible technologies. Our work spans interactive developer tools, collaborative platforms, accessibility technologies, creativity support systems, and human-AI collaboration. We create systems that enhance productivity, creativity, and well-being while ensuring broad societal benefit and ethical responsibility through rigorous empirical research and user-centered design.
The department’s HCI research is closely connected to the Mason Autonomy and Robotics Center (MARC), where faculty and students explore how humans interact with intelligent and autonomous systems. MARC provides specialized laboratories for virtual and augmented reality, human-robot interaction, and immersive simulation environments. These facilities enable researchers to design, test, and refine user-centered technologies that prioritize accessibility, usability, and seamless collaboration between people and machines.
Focus Areas
Game Design and Visualization
Graphics and visualization research at George Mason pushes the boundaries of how we see and interact with digital spaces. Faculty develop new rendering algorithms, 3D modeling techniques, and simulation frameworks that enable richer and more realistic environments. Visualization work translates complex data into interactive visual formats, empowering scientists, engineers, and policymakers to understand patterns and make informed decisions. Game design research complements these efforts by exploring interactive storytelling, simulation-based learning, and immersive training environments—advancing both entertainment technologies and educational applications.
Computer Science Education
Computer science education research aims to improve how computing is taught, learned, and applied. Faculty investigate how students acquire programming knowledge, design curricula to expand participation, and build technologies that personalize learning. This work addresses challenges in retention and skill development using learning analytics, cognitive modeling, and evidence-based pedagogy. By innovating teaching strategies and educational tools, our researchers prepare the next generation of computer scientists to thrive in an evolving technological landscape.