
Explore state-of-the-art View Transformers for 3D object manipulation in robotics, including RVT and RVT-2, offering improved task success, faster training, and real-world applicability.

Explore cutting-edge robot learning techniques and advancements in AI-driven robotics through expert presentations and discussions at the Mila seminar.

Explore the interdependence of planning and perception in robotics, focusing on physical property learning, multi-modal sensing, and uncertainty modeling for improved task performance.

Explore compositional AI system design and physics-integrated learning algorithms for robotics and autonomy. Discover methodologies for reliable deployment and rapid hardware control implementation.

Explore cutting-edge research in prosthetics and smart limb control. Discover open problems and current solutions in neuroprosthetics, reinforcement learning, and human-robot interaction for improved functionality and usability.

Explore recent advancements in using large pretrained networks for robot control, from basic concepts to practical applications in robotics research.

Explore efficient action representation techniques for enhancing robot learning, focusing on helpful abstractions and theoretical aspects of reinforcement learning.

Explore advancements in general-purpose home robots, including vision-language models, rapid skill learning, and multi-fingered dexterity. Discover challenges and solutions for creating adaptable, cost-effective domestic assistants.

Explore advancements in robotic manipulation, combining classical and learned methods. Discover projects on extrinsic contact learning, visuo-tactile SLAM, and in-hand object rotation using vision and touch.

Explore cutting-edge approaches for building adaptable generalist robots, focusing on in-context learning, unsupervised reinforcement learning, and leveraging foundation models for improved generalization and task versatility.

Explore advancements in machine learning for robotics, focusing on creating versatile and dexterous robots through supervised learning and the development of Large Behavior Models.

Explore methods for integrating human knowledge into robot learning abstractions, focusing on feedback as a prior, personalized interface, and framework for user-aligned reward functions.

Explore visual feedback integration for precise legged robot coordination in challenging terrains and manipulation tasks, focusing on dynamic, scalable skills for real-world applications.

Explore robotics' dual role in achieving UN Sustainable Development Goals. Analyze potential to enable 46% of targets while inhibiting 19%, focusing on economic, social, and environmental impacts.

Explore structured world models for physical interactions in robotics. Learn novel representations and structural priors for effective model-based planning and complex manipulation tasks.

Explore innovative methods for training robots using imperfect simulators, focusing on navigation and pick-and-place tasks. Learn about leveraging large-scale learning, hierarchical control, and foundation models for real-world deployment.

Explore RoboCat, a multi-embodiment, multi-task generalist agent for robotic manipulation. Learn about its ability to generalize across tasks and robots, and its potential for autonomous improvement.

Explore data-driven solutions for fine robotic manipulation, enabling low-cost hardware to perform intricate tasks with superhuman precision using imitation and reinforcement learning techniques.

Explore MFEM's enhanced capabilities through libCEED integration, including support for simplices, mixed meshes, and p-adaptivity. Discover performance gains across various HPC architectures.

Explore scalable design and optimization using MFEM for large-scale scientific simulations. Learn about topology and shape optimization algorithms, gradient-based techniques, and implementation strategies for industrial problems.

Explore cutting-edge finite element research through student presentations on topics like µFEA, entropy stabilization, Maxwell's equations, and thermo-mechanical solves using MFEM.