During the MIT Science Policy Initiative’s Congressional Visit Days, PhD students and postdocs met with legislators to share expertise and advocate for science agency funding.

The fellowships provide five years of funding to doctoral students in applied science, engineering, and mathematics who have “the extraordinary creativity and principled leadership necessary to tackle problems others can’t solve.”

MIT CSAIL’s frugal deep-learning model infers the hidden physical properties of objects, then adapts to find the most stable grasps for robots in unstructured environments like homes and fulfillment centers.

With generative AI models, researchers combined robotics data from different sources to help robots learn better.

A new quantum-system-on-chip enables the efficient control of a large array of qubits, moving toward practical quantum computing.

A new approach could streamline virtual training processes or aid clinicians in reviewing diagnostic videos.

“Alchemist” system adjusts the material attributes of specific objects within images to potentially modify video game models to fit different environments, fine-tune VFX, and diversify robotic training.

Research sheds light on the properties of novel materials that could be used in electronics operating in extremely hot environments.

MIT CSAIL researchers enhance robotic precision with sophisticated tactile sensors in the palm and agile fingers, setting the stage for improvements in human-robot interaction and prosthetic technology.

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