Daniela L. Rus | |
---|---|
Born | Cluj-Napoca, Romania |
Nationality | Romanian American |
Citizenship | American |
Alma mater | University of Iowa Cornell University |
Awards | NAS member (2024) 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 | Cynthia Sung |
Daniela L. Rus is a Romanian-American 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. She is the author of the books Computing the Future and The Heart and the Chip.
Daniela L. Rus was born in Romania before immigrating to the United States with her parents. Her father, Teodor Rus, is an emeritus professor of computer science at the University of Iowa.
She earned her bachelor's degree in computer science in 1985 from the University of Iowa, before getting a PhD in 1993 at Cornell University under the supervision of John Hopcroft. [1] She started her academic career as a professor in the Computer Science Department at Dartmouth College before moving to MIT in 2004.
Since 2012 she has served as Director of MIT Computer Science and Artificial Intelligence Laboratory (CSAIL), which - with more than 125 faculty and 1500+ members - is the university's largest interdepartmental research lab.
As director of CSAIL, she launched a number of research programs and initiatives, including the AI Accelerator program, Toyota-CSAIL Joint Research Center, [2] Communities of Research (CoR), a postdoctoral program called METEOR, Future of Data Trust and Privacy, Machine Learning Applications, Fintech, Cybersecurity. As head of CSAIL's Distributed Robotics Lab, Rus focuses her research on the science and engineering of autonomy, with the goal of developing systems that seamlessly integrate into people's lives to support them with cognitive and physical tasks.
Rus is a member of the National Academy of Engineering (NAE), the American Academy of Arts and Sciences (AAAS), the National Academy of Sciences (NAS) and a fellow of ACM, AAAI, and IEEE. She was also the recipient of an NSF Career award and an Alfred P. Sloan Foundation fellowship, and of the 2002 MacArthur Fellowship. [3]
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. [4] 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." [5]
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 [6] and AI [7] in the future of work, AI for Good, and computational sustainability.
Rus is also involved in corporate governance. In March 2023, logistics company Symbotic appointed her to its board of directors. In October 2023, AI SaaS company SymphonyAI appointed her to its board of directors, where she still serves as of July 2024. [8]
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. [9] 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, [10] and magnet-controlled robots that can walk, sail and glide using different dissolvable exoskeletons. [11] She has also worked on algorithms for robots to fly in swarms, [12] and for boats to autonomously navigate the canals of Amsterdam & self-assemble as floating structures. [13]
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. [14] Her work has introduced self-contained autonomous robotic systems such as an underwater “fish” used for ocean exploration [15] and dexterous hands that can grasp a range of different objects. [16] Rus has created inexpensive designs and fabrication techniques for a range of silicon-based robots and 3D-printable robots, [17] 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. [18] She has also explored the potential of extremely small-scale robots, like an ingestible origami robot [19] 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. [20]
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, [21] better understand the cause-and-effect of tasks, [22] and even that can continuously adapt to new data inputs [23] 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 [24] to snowy weather, [25] and also released an open-source simulation engine that researchers can use to test their algorithms for autonomous vehicles.
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. [26] Using wearable body sensors, she has developed systems that enable users to more smoothly control drones [27] and work with to lift and transport goods. [28]
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 [29] to help guide the visually impaired, as well as a “smart glove” that uses machine learning to interpret sign language. [30]
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, [31] items with tunable mechanical properties, [32] and even “smart gloves” that could help with grasping tasks for people with motor-coordination issues. [33] 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.
In 2017, Rus was included in Forbes "Incredible Women Advancing A.I. Research" list. [34]
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:
Gerald Jay Sussman is the Panasonic Professor of Electrical Engineering at the Massachusetts Institute of Technology (MIT). He has been involved in artificial intelligence (AI) research at MIT since 1964. His research has centered on understanding the problem-solving strategies used by scientists and engineers, with the goals of automating parts of the process and formalizing it to provide more effective methods of science and engineering education. Sussman has also worked in computer languages, in computer architecture, and in Very Large Scale Integration (VLSI) design.
Computer Science and Artificial Intelligence Laboratory (CSAIL) is a research institute at the Massachusetts Institute of Technology (MIT) formed by the 2003 merger of the Laboratory for Computer Science (LCS) and the Artificial Intelligence Laboratory. Housed within the Ray and Maria Stata Center, CSAIL is the largest on-campus laboratory as measured by research scope and membership. It is part of the Schwarzman College of Computing but is also overseen by the MIT Vice President of Research.
Charles Eric Leiserson is a computer scientist and professor at Massachusetts Institute of Technology (M.I.T.). He specializes in the theory of parallel computing and distributed computing.
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The following outline is provided as an overview of and topical guide to artificial intelligence:
Yann André LeCun is a French-American computer scientist working primarily in the fields of machine learning, computer vision, mobile robotics and computational neuroscience. He is the Silver Professor of the Courant Institute of Mathematical Sciences at New York University and Vice-President, Chief AI Scientist at Meta.
Andrew Yan-Tak Ng is a British-American computer scientist and technology entrepreneur focusing on machine learning and artificial intelligence (AI). Ng was a cofounder and head of Google Brain and was the former Chief Scientist at Baidu, building the company's Artificial Intelligence Group into a team of several thousand people.
Machine ethics is a part of the ethics of artificial intelligence concerned with adding or ensuring moral behaviors of man-made machines that use artificial intelligence, otherwise known as artificial intelligent agents. Machine ethics differs from other ethical fields related to engineering and technology. It should not be confused with computer ethics, which focuses on human use of computers. It should also be distinguished from the philosophy of technology, which concerns itself with technology's grander social effects.
Julie Shah is the Department Head of Aeronautics and Astronautics at the Massachusetts Institute of Technology and director of the Interactive Robotics Group at the MIT Computer Science and Artificial Intelligence Laboratory.
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Mary-Anne Williams FTSE is the Michael J Crouch Chair for Innovation at the University of New South Wales in Sydney Australia (UNSW) based in the UNSW Business School.
Regina Barzilay is an Israeli-American computer scientist. She is a professor at the Massachusetts Institute of Technology and a faculty lead for artificial intelligence at the MIT Jameel Clinic. Her research interests are in natural language processing and applications of deep learning to chemistry and oncology.
Carol Elizabeth Reiley is an American business executive, computer scientist, and model. She is a pioneer in teleoperated and autonomous robot systems in surgery, space exploration, disaster rescue, and self-driving cars. Reiley has worked at Intuitive Surgical, Lockheed Martin, and General Electric. She co-founded, invested in, and was president of Drive.ai, and is now CEO of a healthcare startup, a creative advisor for the San Francisco Symphony, and a brand ambassador for Guerlain Cosmetics. She is a published children's book author, the first female engineer on the cover of MAKE magazine, and is ranked by Forbes, Inc, and Quartz as a leading entrepreneur and influential scientist.
Ashutosh Saxena is an Indian-American computer scientist, researcher, and entrepreneur known for his contributions to the field of artificial intelligence and large-scale robot learning. His interests include building enterprise AI agents and embodied AI. Saxena is the co-founder and CEO of Caspar.AI, where generative AI parses data from ambient 3D radar sensors to predict 20+ health & wellness markers for pro-active patient care. Prior to Caspar.AI, Ashutosh co-founded Cognical Katapult, which provides a no credit required alternative to traditional financing for online and omni-channel retail. Before Katapult, Saxena was an assistant professor in the Computer Science Department and faculty director of the RoboBrain Project at Cornell University.
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Cynthia R. Sung is an American roboticist known for her research on foldable robots. She is Gabel Family Term Assistant Professor of Mechanical Engineering & Applied Mechanics, with a secondary appointment in the Department of Computer and Information Science, at the University of Pennsylvania.
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Chelsea Finn is an American computer scientist and assistant professor at Stanford University. Her research investigates intelligence through the interactions of robots, with the hope to create robotic systems that can learn how to learn. She is part of the Google Brain group.