In a clinical trial and study supported by Brown scientists and alumni, a participant regained nearly fluent speech using a brain-computer interface that translates brain signals into speech with up to 97% accuracy.
Over the course of an eight-week summer accelerator focused on personal and commercial development, the Nelson Center for Entrepreneurship’s Breakthrough Lab is supporting student entrepreneurs develop 11 different ventures.
Using the scientific principles behind fluid mechanics, students in a School of Engineering course produced stunning imagery brought to life via high-speed photography.
In a breakthrough that could help revolutionize wireless communication, researchers unveiled a novel method for manipulating terahertz waves, allowing them to curve around obstacles instead of being blocked by them.
The novel approach helps advance wireless sensor technology and paves the way for one day using large populations of inconspicuous sensors in implantable and wearable biomedical microdevices.
Researchers found that one of the most promising electrolytes for designing longer lasting lithium batteries has complex nanostructures that act like micelle structures do in soaped water.
Experiments by a Brown-led research team investigated belly flop mechanics and found surprising insights about air-to-water impacts that could be useful for marine engineering applications.
The research can help unlock answers around how cells assemble themselves during embryonic development and what happens when this fundamental process goes awry.
Using a brain-computer interface, a clinical trial participant who lost the ability to speak was able to create text on a computer at rates that approach the speed of regular speech just by thinking of saying the words.
A team of Brown-led engineers show that a sphere held almost completely under flowing water induces drag forces several times greater than if it were fully submerged, detailing new and interesting physics of drag resistance.
Developed by a team of Brown-led researchers, Pleobot is a krill-inspired robot offering potential solutions for underwater locomotion and ocean exploration, both on Earth and moons throughout the solar system.
A new imaging technique opens a path toward long-term study of blood vessels in aging brains and could help predict neurodegenerative diseases decades before symptoms begin.
Two teams from Brown were among 28 selected this year through DEPSCoR, which is designed to strengthen basic research infrastructure at higher education institutions and propel forward science in areas important to U.S. defense.
Fluid mechanics researchers from Brown University and the University of Toulouse found that surfactants give the celebratory drink its stable and signature straight rise of bubbles.
A team of Brown University researchers created a solution to a nanoscale resolution challenge that has for decades limited the study of materials that could lead to more energy efficient semiconductors and electronics.
The newly launched Initiative for Sustainable Energy will serve as a campus hub for driving technological advances in sustainable energy and preparing the next-generation of leaders in net-zero-carbon energy solutions.
SBUDNIC, built by an academically diverse team of students using off-the-shelf parts, was confirmed to have successfully operated in orbit, demonstrating a practical, low-cost method to cut down on space debris.
The work by a research team made up largely of Brown graduate and undergraduate students addresses a critical biomedical need and has the potential to be widely adapted by clinicians to monitor antidepressants in patients.
In an important step toward a medical technology that could help restore independence of people with paralysis, researchers find the investigational BrainGate neural interface system has low rates of associated adverse events.
Researchers from Brown and MIT suggest how scientists can circumvent the need for massive data sets to forecast extreme events with the combination of an advanced machine learning system and sequential sampling techniques.
Brown University researchers have developed a new technology for evaluating the structural integrity of metal structures, such as pipelines, to prevent catastrophic failure.
The lab of George Karniadakis, professor of applied mathematics and engineering, leads the charge of developing physics-informed neural networks to diagnose and predict the severity of arterial aneurysms.
The new process, which is more effective and efficient than conventional methods, has the potential to significantly impact cancer diagnostics as well as other fields of research.
A new study associated with the BrainGate consortium offered significant clues about how humans learn and form long-term memories; the findings could provide insights for developers of assistive tools for people with paralysis.
A new material developed at Brown University can respond to the presence of bacterial enzymes by releasing a cargo of therapeutic nanoparticles, which could prove particularly helpful in wound dressings.
Scholars from Rice and Brown universities say that next-generation wireless networks that use the technology could be designed with built-in defenses against the ‘metasurface-in-the-middle’ attack.
A self-propelled robotic swimmer, developed by Brown University students and faculty, could help researchers better understand the complex swimming behaviors of bacteria and other microorganisms.
Pulse oximeters often provide inaccurate readings for people with darker skin, a significant health disparity that physics Ph.D. student Rutendo Jakachira is working to eliminate.
With a massive shift under way toward more home-based health care delivery, more than 90 medical professionals and technologists gathered virtually to explore the challenges and opportunities that change presents.
A new 3D connective tissue model gives researchers a sophisticated tool to understand the underlying mechanisms of connective tissue disorders and test potential treatments.
The discovery of electrical signals in the brain associated with OCD could enable an emerging type of adaptive deep brain stimulation therapy as an improved treatment.
With the help of an advanced machine learning technique, researchers from Brown University suggest strategies for improving the performance of epidemiological models used to predict the course of pandemics.
A new kind of neural interface system that coordinates the activity of hundreds of tiny brain sensors could one day deepen understanding of the brain and lead to new medical therapies.
A new infectious disease model that accounts for people’s ‘level of caution’ or ‘sense of safety’ accurately captures surges and declines in COVID-19 cases since March 2020 — and could help predict how the pandemic will eventually end.
Brown University researchers have developed a technique that could allow deep brain stimulation devices to sense activity in the brain and adjust stimulation accordingly.