26 Facts About Daniela Rus

Daniela Rus serves as director of the MIT Computer Science and Artificial Intelligence Laboratory, and the Andrew and Erna Viterbi Professor in the Department of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology.

Daniela Rus is the author of the books Computing the Future, The Heart and the Chip: Our Bright Future with Robots, and The Mind's Mirror: Risk and Reward in the Age of AI.

Daniela L Rus was born in Romania before immigrating to the United States with her parents.

Daniela Rus's father, Teodor Rus, is an emeritus professor of computer science at the University of Iowa.

Daniela Rus received a Master of Science in computer science in 1990 and a Doctor of Philosophy in computer science in 1993, both from Cornell University.

Daniela Rus started her academic career as a professor in the Computer Science Department at Dartmouth College before moving to MIT in 2004.

Daniela Rus was the recipient of an NSF Career award and an Alfred P Sloan Foundation fellowship, and of the 2002 MacArthur Fellowship.

Daniela Rus has published an extensive collection of research articles that span the fields of robotics, artificial intelligence, machine learning, and computational design.

Daniela Rus has spoken and written widely about larger topics in technology, like the role of robotics and AI in the future of work, AI for Good, and computational sustainability.

Daniela Rus co-founded the companies LiquidAI, ThemisAI, Venti Technologies, and The Routing Company.

Daniela Rus has contributed some of the first multi-robot system algorithms with performance guarantees in distributed robotics, by introducing a control-theoretic optimization approach for adaptive decentralized coordination.

Daniela Rus's group has developed self-configuring modular robots that can alter their physical structures to perform different tasks.

Daniela Rus was an early contributor to the field of soft robotics, which some researchers believe has the potential to outperform traditional hard-bodied robotics in a range of human environments.

Daniela Rus's work has introduced self-contained autonomous robotic systems such as an underwater "fish" used for ocean exploration and dexterous hands that can grasp a range of different objects.

Daniela Rus has created inexpensive designs and fabrication techniques for a range of silicon-based robots and 3D-printable robots, with the goal of making it easier for non-experts to make their own.

Daniela Rus's projects have often drawn inspiration from nature, including the robotic fish and a trunk-like robot imbued with touch sensors.

Daniela Rus has explored the potential of extremely small-scale robots, like an ingestible origami robot that could unfold in a person's stomach to patch wounds.

Daniela Rus is working on a new class of machine learning models that she calls "liquid networks" that can more accurately estimate uncertainty, better understand the cause-and-effect of tasks, and even that can continuously adapt to new data inputs rather than only learning during the training phase.

Daniela Rus' research has involved developing machine learning systems for a range of use cases and industries, including for autonomous technologies for vehicles on land, in the air and at sea.

Daniela Rus has worked on algorithms to improve autonomous driving in difficult road conditions, from country roads to snowy weather, and released an open-source simulation engine that researchers can use to test their algorithms for autonomous vehicles.

Daniela Rus has created feedback systems that allow human users to subconsciously communicate through brainwave activity whether a robot has made a mistake in manufacturing environments.

Daniela Rus's group has worked on projects geared towards helping the physically disabled.

In recent years Daniela Rus has worked with MIT colleague Wojciech Matusik to create methods for 3D-printing robots and other functional objects, often made out of multiple different types of material.

Daniela Rus has 3D-printed soft robots with embedded electronics, items with tunable mechanical properties, and even "smart gloves" that could help with grasping tasks for people with motor-coordination issues.

Daniela Rus's group has developed methods for 3D-printing materials to sense how they are moving and interacting with their environment, which could be used to create soft robots that have some sort of understanding of their own posture and movements.

Daniela Rus was elected a member of the National Academy of Engineering in 2015 for contributions to distributed robotic systems.