Soft robots have the potential to adapt their morphologies and behavioral control policies to changing tasks and environments. Inspired by the dynamic plasticity of living organisms and the general adaptability of animals, this talk will discuss several shape-shifting soft robot platforms for multi-task performance and multi-environment locomotion—for example, robotic skins, robotic fabrics, and robots with […]
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Reliable forecasts of the Earth system are crucial for human progress and safety from natural disasters. Artificial intelligence offers substantial potential to improve prediction accuracy and computational efficiency in this field, however this remains underexplored in many domains. Here we introduce Aurora, a large-scale foundation model for the Earth system trained on over a million […] |
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Structural failure is a critically important design consideration in many engineering applications. Nature provides a number of interesting examples of lightweight structural features that exhibit outstanding failure characteristics. Recent progress in additive manufacturing has facilitated precise control over geometric features, allowing for the implementation of bio-inspired structural designs on a layer-by-layer basis. In this thesis, […] |
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Flow systems in nature, whether animate or inanimate, have evolved in time toward greater efficiency by adapting, or ‘morphing’, their configuration to decrease resistance to the currents flowing through them. Observations at various scales indicate that the distribution of flow, i.e. the connection of a point (source/sink) to a volume (sink/source) or vice-versa, is the […] |
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Designing miniaturized robots and bioelectronic devices will enable access throughout the entire human body, leading to novel procedures at the cellular level and offering localized diagnosis and treatment with unprecedented precision and efficiency. However, the soft, complex, and multi-dimensional nature of biological systems poses significant challenges for mechanical design, manufacturing, materials engineering, and functional integration […] |
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Recent advancements in hardware and software are bringing autonomous aerial vehicles closer than ever to finally delivering on futuristic visions of flying cars and package delivery drones. However, the safe deployment of autonomous aircraft at scale in urban environments poses significant challenges, one of which being uncertainties contributed by complex spatial and temporal winds. Clusters […] |
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Robotic systems, particularly at small scales, require efficient actuation and sensing solutions that maintain compactness. We are interested in systems where sensing and actuation are seamlessly integrated, specifically using impedance-related properties—such as electrical resistance, induced electromotive force (emf), and inductance— for free self-sensing in actuators without additional sensors. We explore three main example applications: (1) […] |
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Accurate simulations of physical phenomena governed by partial differential equations (PDEs) are foundational to scientific computing. While traditional numerical methods have proven effective, they remain computationally intensive, particularly for complex, large-scale systems. This talk introduces the neural operator, a machine learning framework that approximates solution operators in infinite-dimensional spaces, enabling efficient and scalable PDE simulations […] |
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