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Daniela L. Rus
DanielaRus-By-DanielJackson.jpg
Daniela Rus headshot (credit Daniel Jackson)
Born
Cluj-Napoca, Romania
Nationality Romanian American
Citizenship American
Alma mater Cornell University
Awards AAAS member (2017)
NAE member (2015)
MacArthur fellow (2002)
IEEE fellow (2009)
AAAI fellow (2009)
ACM Fellow (2015)
Scientific career
Fields Robotics; AI; Computer Science
Institutions Dartmouth College;
Massachusetts Institute of Technology
Doctoral advisor John Hopcroft
Doctoral students Mac Schwager, Cynthia Sung, Carrick Detweiler, Stephanie Gil, Sejoon Lim, Robert Katzschmann, Wilko Schwarting, Lucas Liebenwein, Alexander Amini, Qun Li, Lillian Chin, Teddy Ort

Daniela L. Rus is a roboticist and computer scientist, Director of the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL), and the Andrew and Erna Viterbi Professor in the Department of Electrical Engineering and Computer Science (EECS) at the Massachusetts Institute of Technology.

Biography

Daniela Rus has carved a permanent mark on the field of computer science and robotics [1]. Her journey into the world of science and technology began with a solid academic foundation. Rus earned her Bachelor's and Master's degrees in Computer Science from the University of Bucharest, Romania, before pursuing a Ph.D. in Computer Science at Cornell University [2]. Her early academic pursuits set the stage for a career marked by innovation and groundbreaking research. The academic career of Daniela Rus has been marked by an unrelenting pursuit of knowledge and an unwavering commitment to advancing robotics and artificial intelligence. After obtaining her Ph.D., she acted as a faculty member at esteemed institutions, including Dartmouth College, where she held a tenure position [1]. Her research during this period laid the groundwork for the innovative projects she would later lead. In 2007, Rus joined the Massachusetts Institute of Technology (MIT), a move that proved pivotal for both her career and the field of robotics. Her leadership roles quickly helped shape the direction of cutting-edge research at MIT, where she soon became a Professor of Electrical Engineering and Computer Science [1]. At the heart of Daniela Rus's contributions lies her groundbreaking work in robotics. With a focus on developing robots capable of autonomous decision-making and adapting to dynamic environments, her research has consistently pushed the boundaries of what is possible in the field [2]. One of her notable projects involves the development of modular robots—robots made up of individual modules that can reconfigure themselves to adapt to different situations [3]. From disaster response, where flexibility is essential, to space exploration, where robots need to adapt to challenges of unknown environments, this research has implications for a wide range of applications [3]. Rus's research also extends to swarm robotics, a field that explores the coordination and collaboration of large groups of robots to achieve collective goals [3]. Agriculture is one industry that could benefit from this work, where swarms of robots may work together to monitor and maintain crops [3]. In 2012, Daniela Rus assumed the role of director of MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL), one of the world's leading research laboratories in the field [1]. This position highlighted not only her research prowess but also her leadership and management skills. Under Rus's guidance, CSAIL has continued to be at the forefront of cutting-edge research in artificial intelligence, machine learning, and robotics [1]. Daniela Rus's contributions to science and technology have not gone unnoticed. She has received numerous awards and honors, underscoring the impact of her work on the scientific community. She has been recognized for her contributions to robotics with the Engelberger Robotics Award [2]. Moreover, she has been named a fellow of the American Academy of Arts and Sciences, further confirming her status as an industry leader [2]. Daniela Rus's influence extends beyond her research and academic achievements. She is an advocate for diversity and inclusion in STEM fields, particularly encouraging the involvement of women in technology [4]. Her commitment to fostering an inclusive environment for the next generation of scientists and engineers is evident in her various outreach efforts and engagements.

Work

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

In her work Rus has sought to expand the notion of what a robot can be, exploring such topics as soft robotics, self-reconfigurable modular robots, swarm robotics, and 3D printing. Her research approaches the study of the science and engineering of autonomy as integrated hardware-software, or body-brain systems. She has said that she views the body of the robot as critical in “defining the range of capabilities of the robot,” and the brain critical in “enabling the body to deliver on its capabilities."

To this end, she has developed a range of algorithms for computation design and fabrication of robots, for increasing the learning capabilities of machines in safety-critical applications, and for coordinating teams of machines and people. In addition to contributing fundamentally to the design, control, planning, and learning for agents, Rus also considered what is necessary for robots to be deployed in the world. One example is her project to develop self-driving vehicles.

She has also 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.

Robotics

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. Key to these results is the tight coupling between perception, control, and communication. The control algorithms are decentralized, adaptive, and provably stable.

Her group has developed self-configuring modular robots that can alter their physical structures to perform different tasks. This includes sets of robotic cubes that use angular movement to assemble into different formations, and magnet-controlled robots that can walk, sail and glide using different dissolvable exoskeletons. She has also worked on algorithms for robots to fly in swarms, and for boats to autonomously navigate the canals of Amsterdam & self-assemble as floating structures.

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. Her 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. 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.

Her projects have often drawn inspiration from nature, including the robotic fish and a trunk-like robot imbued with touch sensors. She has also explored the potential of extremely small-scale robots, like an ingestible origami robot that could unfold in a person's stomach to patch wounds. Other work has revolved around robots for a range of logistics environments, including one that can disinfect a warehouse floor in 30 minutes.

AI and Machine learning

Rus and her team are trying to address some of the key challenges with today's methods for machine learning, including data quality and bias, explainability, generalizability, and sustainability. She 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. Rus' research has also 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. She has worked on algorithms to improve autonomous driving in difficult road conditions, from country roads to snowy weather, and also released an open-source simulation engine that researchers can use to test their algorithms for autonomous vehicles.

Human/robot interaction

Many of the Distributed Robotics Lab's projects have focused on enabling smoother and more natural interaction and collaboration between humans and robots. 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. Using wearable body sensors, she has developed systems that enable users to more smoothly control drones and work with to lift and transport goods.

Her group has also worked on projects geared towards helping the physically disabled. They have collaborated with the Andrea Bocelli Foundation to create wearable systems to help guide the visually impaired, as well as a “smart glove” that uses machine learning to interpret sign language.

Computational design and fabrication

In recent years 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. She 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. Her 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.

Awards

In 2017, Rus was included in Forbes "Incredible Women Advancing A.I. Research" list.

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

A select list of her awards include:

See also

Kids robot.svg In Spanish: Daniela L. Rus para niños

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