People
Embodied AI hosts a dynamic community of researchers and scientists focused on creating the next generation of robots, with advanced perception, learning and collaborative abilities that can integrate computer vision and novel sensors to interpret sensory data, refine motor skills and improve through experience.
Partnerships and Organization
(Corporate Partnerships)
Assistant Professor: Language Technologies Institute & Robotics Institute (Courtesy) | School of Computer Science
Research Interests: Grounded and embodied natural language processing – placing perception and interaction as central to how language is learned and understood.
(Robot Learning Days)
Associate Professor: Robotics Institute | School of Computer Science
Research Interests: Perceptual robot learning, i.e. developing new methods at the intersection of robot perception and planning for robots to learn to interact with novel, perceptually challenging and deformable objects.
(Outreach)
Assistant Professor: Robotics Institute | School of Computer Science
Research Interests: Developing algorithms and representations to enable robots to learn versatile manipulation skills over time. The ability to learn skills and adapt opens up new robot applications, from taking care of the elderly to assisting in hazardous environments.
Members of REAL Center
Professor: Robotics Institute | School of Computer Science
Research Interests: Eenabling robots to learn strategies (tricks, hacks) to do tasks from direct instruction, googling and using the web, observation, and practice (reinforcement learning).
Assistant Professor: Robotics Institute | School of Computer Science
Research Interests: Interactive and Trustworthy Robotics: how to enable robots to safely interact with the "open world". We broadly draw upon methods from optimal control, dynamic game theory, uncertainty quantification, and deep learning.
Assistant Professor: Robotics Institute | School of Computer Science
Research Interests: Robotic Caregiving and Human Interaction (RCHI) Lab, which focuses on developing new robot learning, mobile manipulation, and sensing methods, with applications in physical human-robot interaction and healthcare.
![Katerina Fragkiadaki](/xrtc/images/core-faculty/katerina.jpeg")
Associate Professor: Machine Learning Department & Robotics Institute (Courtesy) | School of Computer Science
Research Interests: Building machines that understand the stories that videos portray, and, inversely, in using videos to teach machines about the world.
Assistant Professor: Robotics Institute | School of Computer Science
Research Interests: Robot grasp and motion planning in dynamic environments using cloud-based high-performance computing, optimization, and deep learning.
Assistant Professor: Machine Learning Department | School of Computer Science
Research Interests: The intersection of neuroscience & AI to reverse-engineer animal intelligence and build the next generation of autonomous agents, safely and responsibly.
Associate Research Professor: Robotics Institute | School of Computer Science
Research Interests: I am interested in creating persistent robots that can co-exist with humans in shared environments, learning to improve themselves over time through continuous training, exploration, and interaction
Assistant Professor: Robotics Institute & Machine Learning Department (affiliate) | School of Computer Science
Research Interests: The intersection of Computer Vision, Machine Learning & Robotics. Our ultimate goal is to build agents with a human-like ability to generalize in real and diverse environments. We believe understanding how to continually develop knowledge and acquire new skills from just raw sensory data will play a vital role in achieving this goal.
Associate Professor: Machine Learning Department | School of Computer Science
Research Interests: Deep Learning, Probabilistic Graphical Models and Large-scale Optimization.
Assistant Professor: Robotics Institute | School of Computer Science
Research Interests: The intersection of learning and control, spanning the entire spectrum from theory and foundations, algorithms, to real-world applications in robotics and autonomy. The ultimate goal is to develop reliable, adaptive, and efficient learning and control methods for embodied intelligence with agility.
Associate Professor: Robotics Institute | School of Computer Science
Courtesy: Civil and Environmental Engineering, Computer Science Department, Robotics Institute
Research Interests: Leading the CMU Safe AI Laboratory, Zhao aims to create trustworthy AI that is robust, safe, generalizable as well as explainable, verifiable, and human-centric. His long-term goal is to develop fundamental theories and practical technologies to safely deploy AI to address some of the world's most pressing problems.