Northwestern’s AI-Driven, Rapid, Experimental Automation Machine (DREAM) Cloud Lab will be housed within the Synthetic Biology Foundry, a shared research facility equipped with advanced robotics and protein-engineering tools. The foundry is co-located with the Querrey InQbation Lab, Northwestern’s startup incubator hub. Photo by Jimmy Boratyn
By Kritika Agarwal
Imagine you’re a biotech researcher interested in designing a protein for use in a new vaccine – but you’re at a rural institution with limited access to labs and equipment. Instead of giving up on your idea because of lack of resources, you use a cloud-based interface to describe what you would like your protein to do. AI models then propose promising designs, and – after a rigorous biosafety and bioethics check – robotic systems at an autonomous lab on the other side of the country build the protein and test its functionality.
It may sound like science fiction, but that is exactly what an AI-directed protein-engineering cloud lab at Northwestern University is seeking to accomplish in the next four years, with $20 million in support from the National Science Foundation. The university’s AI-Driven, Rapid, Experimental Automation Machine (DREAM) Cloud Lab “aims to become a national resource to dramatically accelerate the development of new medicines, sustainable materials, agricultural technologies and other biotechnology innovations” by designing, building, and testing proteins.
And Northwestern isn’t alone. The NSF recently announced that it is investing $380 million in similar AI-enabled automated labs across the United States. The investment will result in a national network of “cloud labs” that will “test, scale, and demonstrate new methods and tools” to advance science and engineering.
Each lab in the network will specialize in a different area – from materials science to biotechnology to chemistry to electronics to advanced manufacturing – and will allow researchers from across the nation to simply “order studies online,” according to Boston University, which also received $20 million for its Design, Automation, Manufacturing, and Processes (DAMP) Laboratory. The labs will be able to communicate with each other, “enabling studies requiring different capabilities to jump from lab to lab as they progress,” BU explains.
According to Carnegie Mellon University, another recipient, “This network will … develop shared standards, open software, data resources and autonomous scientific workflows to accelerate discoveries in key areas.” Together, the network of labs has the potential to revolutionize how researchers do science by broadening access to cutting-edge labs and tools, speed up the pace of innovation, and help tackle some of America’s most pressing challenges.
Accelerating the Pace of Scientific Discovery with AI-Driven Labs
According to the NSF, its $380 million investment represents a core agency contribution to the U.S. government’s Genesis Mission, which seeks to double the pace of scientific discovery in the next decade.
Among the 20 labs selected to create the national network, 14 are at AAU institutions, including Boston University; the California Institute of Technology; Carnegie Mellon University; the Georgia Institute of Technology; Johns Hopkins University; Northwestern University; the Pennsylvania State University; Purdue University; Rice University; Stanford University; the University of California, Santa Barbara; the University of Chicago; the University of Maryland; and the University of Utah. Other AAU institutions are also part of the initiative as joint collaborators. Each lab was selected because of its existing scientific talent and expertise, world-class infrastructure, and leading capabilities in AI and robotics.
To give another example of the type of work these institutions will engage in, Rice University’s Revolutionizing AI-Driven Autonomous Experimentation for Next-Generation Semiconductor Synthesis (READINESS) project will allow researchers to simulate experiments in a virtual laboratory using a “digital twin” before conducting them with physical equipment. According to Rice, the lab will initially focus on “two-dimensional materials, oxide semiconductors and diamond thin films, which have the potential to support faster electronics, lower-power computing, quantum devices and other emerging technologies.”
Helping America Win the Global Technology Race
AI-powered autonomous labs are an important front in the global technology race, and NSF’s recent investment aligns with recommendations AAU has made to Congress and to the administration. In June 2025, in response to a request for ideas from Sens. Mike Rounds (R-SD) and Martin Heinrich (D-NM) on how to accelerate American science, AAU recommended that Congress establish new funding for “AI-powered laboratories that … allow scientists to design and conduct experiments remotely, efficiently, and at scale.” These labs, AAU noted, “are a source of great promise as engines of scientific discovery.”
Similarly, AAU encouraged the Department of Energy earlier this year to find ways to “leverage research universities’ expertise in designing, building, and operating test beds across technology areas.” The fact that 14 of the 20 new labs are at AAU member institutions demonstrates that research universities are essential to driving this national effort and in helping the United States lead in critical technologies.
AI-powered autonomous labs are truly at the forefront of science. As Carnegie Mellon Vice President for Research Theresa Mayer says about the university’s AI Science Foundry, “By integrating artificial intelligence with robotics, autonomous laboratories, advanced instrumentation and high-performance computing, we’re creating an intelligent research environment where scientists can ask bigger questions, explore vastly larger experimental spaces and dramatically shorten the path from idea to discovery.”
Kritika Agarwal is assistant vice president for communications at AAU.