Research Labs and Centers

We live amidst real-time data flows, with sensors measuring everything from air quality to traffic, with our cell phones and social media yielding information about our whereabouts and activity levels, with buildings reporting on their energy consumption and maintenance. The role of machine learning in smart cities is to provide a seamless and data-driven operating environment. This is only one of the visions/goals of smart cities but one that is the focus of our research. Our research focuses on devising new algorithmic, statistical, mathematical, machine learning, artificial intelligence, and hybrid methods to tackle complex problems in urban computing and intelligent transportation, in addition to analytical and visualization methods to make sense of spatial-temporal data. We leverage the data to make cities smarter, environmental resources sustainable, and quality of life better for citizens.

The Alignment Lab or A Lab's mission is to amplify people’s capability of interacting with machine learning and AI. Through novel interactive designs, A-lab helps people derive better data-driven decisions and job-improving task performance for varying professionals. Specific research directions of A Lab are as follows: (1) Building human efficient and effective data acquisition environments which can boost data annotators’ annotation performance as well as the quality of data, (2) Understanding interactive design that can enable data scientists and subject-matter experts to understand better and build high-performing and accountable ML models, and (3) Creation of human-AI collaboration tools that can practically boost professionals’ productivity and creativity.

The Sun Security Laboratory (SunLab) was founded by Professor Kun Sun. We are located at George Mason University. Our mission is to conduct basic and applied systems and network security research. Our current research areas include trustworthy computing, moving target defense, software security, cloud/container security, AI security, and mobile phone security.

The HCD Lab was created in 2016, currently, our research team includes two post-doctoral research fellows (international visiting scholars), 5 PhD students, and 1 undergraduate research assistant. We are a multidisciplinary team of researchers conducting research projects on Human-Computer Interaction. Our research projects have concrete real-world applications while advancing science on fundamental research.

TrailsLAB, directed by Aditya Johri, is committed to developing a critical understanding of the role of technology, including AI, for learning and social development, and for improving teaching and education in this field.

The MEDIA Lab, directed by Professor Zhisheng Yan, conducts research in enabling next-generation cyber-human systems – immersive multimedia computing on smart headwear. The goal is to advance human capabilities and experience through virtual reality, augmented reality, and 360 video systems. Current research areas include utilizing computer vision, multimedia, the Internet of Things, mobile computing, and adversarial machine learning to advance immersive computing.

The Community Informatics Lab aims to understand the dynamics of local communities, technology-enabled groups, and local information inequality by leveraging computational methods and social theories. Also, the lab designs and builds computing systems that help solve community-driven information issues.

The Humanitarian Informatics Lab conducts use-inspired research aligned with the United Nations' Sustainable Development Goals via the interdisciplinary science of design, analysis, and evaluation of information systems that augment the information processing capabilities of human workers within public organizations at local, national, and international levels. Our scientific passion is to create new knowledge in the semantic, structured information representation, integration, and processing of unstructured data from the Web and designing human-centered computing solutions to address information overload challenges for real-time decision support in organizations such as emergency services. We apply this research to crisis management from mitigation to responding to natural crises (e.g., hurricanes), societal crises (e.g., hate, gender stereotyping), and human crises (e.g., social engineering, terrorism).

The Personalized Learning in AIT (PLAIT) laboratory was created to support the innovative learning environment in the College of Engineering and Computing. It aims to bring together the efforts of researchers, teaching faculty, instructional designers, and students to stimulate and promote a nourishing learning environment for CEC students. PLAIT provides a space for innovative collaboration and inspires pioneers in education to explore and experiment with revolutionary ideas destined to transform the learning experience for everyone.

CAHMP is part of the beginning of a new and transdisciplinary research field on to how to structure and optimize reciprocal relationships between humans and assistive computing systems.

Learn more about the Center for Adaptive Systems of Brain-Body Interactions.

The Institute for Digital InnovAtion (IDIA) engages researchers, innovators, and scholars across Mason in cutting-edge work to shape the future of our digital society, promoting equality, well-being, security, and prosperity.

Learn more about the Center for Secure Information Systems (CSIS).

Learn more about the CRSC (Center for Resilient and Sustainable Communities).

The Learning Agents Center conducts basic and applied research on the development of cognitive assistants that: learn problem-solving expertise directly from subject-matter experts, support experts, and non-experts in problem-solving and decision-making, and teach their problem-solving expertise to students. Major research areas include instructable agents, evidence-based reasoning, ontologies and rules, multistrategy learning with an evolving knowledge representation, graphical user interfaces, integrated logic and probabilistic reasoning in uncertain and dynamic environments, mixed-initiative reasoning, crowd problem solving, modeling experts' reasoning, learning-based knowledge engineering, natural language processing, and intelligent tutoring systems. The Center also aims to support teaching in its areas of expertise, particularly instructable cognitive assistants, machine learning, knowledge acquisition, intelligent agents, artificial intelligence, and its applications.