The Center for Artificial Intelligence and Research (CAIR) advances AI systems that operate across physical, interactive, and connected environments. Located in Pangborn Hall, CAIR brings together faculty, doctoral scholars, students, and partners to develop intelligent systems that can sense, reason, communicate, and act in real-world settings.
CAIR’s work spans Physical AI, Interactive AI, AIoT, multimodal perception, signal and image processing, autonomous systems, robotics, and responsible agentic AI. Through interdisciplinary research and applied innovation, CAIR focuses on building AI technologies that are trustworthy, human-centered, secure, and ready for real-world impact.
"Why Physical AI"
Artificial intelligence has spent the past several years mastering language understanding it, generating it, and reasoning through it. The next frontier is more tangible: AI that can perceive the world, move through it, and act within it.
This is Physical AI intelligent systems that combine perception, reasoning, and control to operate in real environments, not only digital ones. Unlike a language model that can describe how a robot should move, Physical AI must respond to uncertainty, adapt to obstacles, interpret sensor data, and make decisions in real time.
At CAIR, Physical AI is the foundation of our research vision. It connects directly to our other two pillars, Interactive AI and AIoT, by enabling intelligent systems to engage with people, coordinate across connected devices, and operate within complex physical environments.
From robotics and autonomous platforms to vehicles, drones, and sensor-driven systems, CAIR is developing AI that does more than understand the world. It is learning to act within it.
Explore our Research Areas to learn how CAIR is shaping the future of intelligent systems.
Interactive Physical AI for Rehab, Education, and Alzheimer’s Monitoring
Multimodal Sensor Fusion, Edge AI, and Robust Physical Perception
Responsible, Ethical, and Compliance-Aware Agentic AI
Multimodal Evaluation, Communication, and Human Feedback Systems