Research

National Institutes of Health Javits Award to bolster building the brain’s blueprint

Nathan Kahl — Thu, 23 Jul 2026 18:20:03 +0000

National Institutes of Health Javits Award to bolster building the brain’s blueprint Nathan Kahl Thu, 07/23/2026 - 14:20

The goal of Giorgio Ascoli’s three decades of research is to gain a more complete understanding of one of science's most complex systems: the human brain. And this year the 91�� professor of bioengineering and neuroscience received one of the National Institutes of Health's (NIH) most prestigious recognitions for established investigators.

Giorgio Ascoli. Photo by Ron Aira/Office of University Branding

Ascoli's long-running program was selected for an NIH Javits Neuroscience Investigator Award, providing seven years of support and additional funding to advance his research into the structure and function of the brain.

The award is especially significant for George Mason, as Ascoli's is the first Javits Award recipient at the university. The award is reserved for a small number of exceptionally highly rated research proposals; the National Institute of Neurological Disorders and Stroke, the institute that supports Ascoli's research, only gives this distinction to a handful of grants each year.

Ascoli's proposal received a priority score in the top 3 percent of all applications reviewed. The Javits recognition converts Ascoli’s funding from what is categorized at NIH as an R01 grant—and which he has successfully renewed since 1999—into an R37, giving a longer timeline and more security. “Because there is a more extended time frame, it really gives the lab a chance to think longer term. I can now take research risks that I could not normally take.”

His work focuses on the intricate structures that allow nerve cells to communicate with one another. Unlike most cells in the body, neurons possess elaborate branching structures that extend from the cell body. These structures receive and transmit signals, creating vast networks through which the brain processes information.

Ascoli compares the structures to a blueprint. "If you're an engineer and you're given a machine and you want to understand how this machine works, the best thing that you can get is a blueprint," he said.

For decades, Ascoli's lab has charted the diversity and organization of these neuronal structures, creating quantitative models of the brain's cellular architecture. A central outcome of that work is NeuroMorpho.Org, a publicly accessible database that collects and standardizes data on the structure of neurons from research groups around the world.

“The impact of our research goes beyond the typical impact of a single lab, which is publications, discoveries, etc. This reaches out more broadly and with longer-term consequences for scientific research,” he said. Researchers worldwide contribute data, which are standardized, annotated, and made freely available for anyone to download, analyze, and use in computational models.

The Javits-supported research will build on that foundation by combining neuroinformatics, computational neuroscience, and the study of learning and memory. Ascoli and his team will use data-driven computational models to simulate brain networks and investigate how their structure supports the brain's ability to learn and retain information.

A particular focus is the hippocampus, a region of the brain closely associated with learning and memory. The work aims to better understand how the architecture of neural circuits contributes to different forms of memory, including conscious memories of events and experiences.

The research could help scientists make predictions about how the brain functions and then test those predictions experimentally. The approach also reflects the increasingly interdisciplinary nature of modern neuroscience, bringing together biology, computer science, engineering, and data science.

“Never before has the neuroscience community had access to so much data and such mighty computational resources for analysis and modeling,” he said. “We are tantalizingly close to making exciting breakthroughs in the century-old quest to link neural architecture to cognitive function.”

The Javits Award will give Ascoli and his team additional time and resources to continue building his brain blueprint, one neuron and one connection at a time.

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NSF CAREER award allows researcher to look under AI’s hood

Nathan Kahl — Mon, 20 Jul 2026 16:30:48 +0000

NSF CAREER award allows researcher to look under AI’s hood Nathan Kahl Mon, 07/20/2026 - 12:30

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Ziyu Yao

Artificial intelligence (AI) systems are now part of everyday life, writing software, tidying up your shopping list, and answering questions. While we know they sit on top of large language models (LLMs), we still understand surprisingly little about what happens inside these systems or what is helping them generate responses.

Ziyu Yao. Photo provided

91�� Department of Computer Science Assistant Professor Ziyu Yao received a prestigious National Science Foundation (NSF) CAREER award for $674,100 over five years to peel the layers back on AI. Specifically, Yao will develop new methods for understanding the internal mechanisms of LLMs. Her research aims to make these AI systems more transparent and useful.

"We use language model–powered products every day, but we have very limited understanding of how they actually work," Yao said. Most efforts to evaluate AI systems focus on their behavior. Researchers give a model a prompt and judge the quality of its response. Yao's work instead focuses on mechanistic interpretability, an emerging field that examines what happens inside a language model as it processes information.

"If we send something to the model, we want to see how it extracts features or signals from my input and gradually performs computations before producing an answer," she said.

As language models have grown dramatically in size, that task is increasingly difficult. Today's leading models contain potentially hundreds of billions of parameters. And Yao said, "The interpretability research community has not caught up. Many traditional approaches cannot be efficiently applied to today's language models."

The project focuses specifically on AI-powered code generation, in which users describe a programming task in natural language and an AI system generates software code. Code generation is an increasingly important application of LLMs, with uses including software engineering and scientific research.

Yao's team will investigate how LLMs apply programming syntax, recall semantic knowledge, and perform deliberate reasoning while writing code. The researchers will also study how training data and learning methods influence those internal mechanisms and explore how interpretability insights can be used to improve AI coding systems.

Current interpretability studies often require researchers to manually design experiments, collecting internal model signals and analyzing the results. Yao plans to develop a framework that automates much of that process using AI itself, allowing researchers to study LLMs more efficiently.

At the same time, she wants interpretability research to produce practical benefits rather than simply satisfying scientific curiosity.

"We want to build the bridge between what we discover about language models and how that knowledge can improve them," Yao said. "Can interpretability actually help us build better AI systems?"

Although commercial AI systems such as ChatGPT are proprietary, Yao and colleagues primarily study open-weight language models that are downloadable. These models are becoming increasingly competitive with commercial systems while supporting the transparency needed for scientific research.

An expectation with the award and a hallmark of the CAREER program is a plan for broader impact. Yao hopes to expand AI literacy through outreach programs, create new curricula and open-source educational resources, provide undergraduate research opportunities, and foster collaborations between researchers in artificial intelligence and software engineering.

"I think we should encourage the younger generation to embrace AI," Yao said. "But at the same time, they should be skeptical, think critically, and be careful about what they are reading from AI."

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Air pollution simulation reinforces public health data on the dangers of airborne toxins

sholla4 — Fri, 17 Jul 2026 13:55:43 +0000

Air pollution simulation reinforces public health data on the dangers of airborne toxins sholla4 Fri, 07/17/2026 - 09:55

Hot summer days often lead to poor air quality. High temperatures and high air pressure systems cause pollutant buildups, creating ground-level ozone that can lead to a variety of health issues. And as climate change increases summer temperatures around the globe, being able to track and predict air quality is becoming a public health priority.

B.H. Baek. Photo provided

B.H. Baek, research associate professor in 91��’s Center for Satellite and Earth Science Research in the College of Science, is developing air quality and emissions modeling systems to help track and predict local and regional air pollutants and their adverse human health impacts.

Benzene, toluene, ethylbenzene, and xylenes—collectively known as BTEX—are common air pollutants, originating from various industrial and manufacturing processes, vehicle emissions, and natural sources such as forest fires. This suite of toxic air contaminants is particularly prevalent in urban environments, as well as near industrial facilities such as power plants and factories. Short- and long-term exposure to BTEX compounds can cause a variety of health issues, including elevated risks of cancer, respiratory diseases, neurological effects, and adverse birth outcomes.

Baek is developing high-resolution, year-long ambient concentration fields for the Louisville, Kentucky, region. This project expands on his previous work developing an air pollution simulation model for the U.S. Gulf Region, home to more than 120 petroleum refineries and subsequently elevated BTEX and styrene emissions.

“We know where the power plants and refineries that produce these emissions are located. We have a map of where the people are driving and living. And with that data, we generate this map of our concentration throughout the region based on the observation data, the estimated emission sources that we have, and the meteorologist data,” Baek explained.

Cross-referenced with hospitalization data and blood samples from residents of the Gulf region from 2011 to 2016, the model provided a more complete picture of both exposure to and the impacts of styrene and BTEX on public health outcomes.

Unlike other highly contaminated areas Baek has worked in, historic monitoring of BTEX in Louisville is much more limited. “It’s a smaller city surrounded by trees, so despite the BTEX contamination, public health has not been a major issue,” said Baek. “It has not been monitored to the same extent.”

Baek and his team will use their toxic simulation data to help fill in the gaps. Called “data fusion,” the model will combine observational data from real-time measurements via a novel mobile app—developed by Professor Yue Cheng from Texas A&M University—with emissions data collected from the Environmental Protection Agency (EPA).

"The main benefit is public health,” said Baek. “Epidemiologists need more accurate data for them to link to their studies of the health effects of air toxin exposure. Now, the model can be expanded for the future to come.”

Baek also notes how this model could support air-quality tracking and predictions as climate change progresses. “We’ll be able to see how climate change will impact the regional scale,” he said.

Baek is already using the simulation to help fill the gaps in the EPA’s National Emissions Inventory; this data will be publicly available once published.

“We developed this model to support the EPA’s work in regulating manufacturers,” said Baek. As the model continues to expand and develop over time with projects like these, it will help state and federal leaders make evidence-based decisions and inform advocacy around emissions regulations.

“George Mason is at the forefront of toxic air pollution work,” said Baek.

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Institute for Immigration Research launches interactive immigration timeline

Katarina Benson — Fri, 17 Jul 2026 00:18:49 +0000

Institute for Immigration Research launches interactive immigration timeline Katarina Benson Thu, 07/16/2026 - 20:18

As the United States celebrates its 250th anniversary, the Institute for Immigration Research (IIR) in the College of Humanities and Social Sciences (CHSS) at 91�� has unveiled "Immigrants & America 250: Data, Stories, and Policy Across United States History," a first-of-its-kind interactive digital timeline that explores how immigration has shaped the United States from its earliest years to present day.

The new online experience combines historical population data, landmark immigration policies, notable immigrant contributions, and archival cultural collections into a single educational resource designed for educators, researchers, policymakers, students, journalists, and the general public.

"Understanding immigration requires more than statistics or policy debates alone," IIR assistant director Marissa Kiss said. "By bringing together historical data, public policy, and personal stories, this project helps reveal the human experience behind the numbers while providing trusted information that places immigration within the broader story of America.”

The interactive experience includes:

U.S. population data beginning in 1770, with detailed immigration statistics by decade from 1840 through 2024;
Changes in immigrant populations by country and world region of birth
Eighty-three landmark immigration laws and historical events
Profiles of 80 notable immigrants whose contributions have shaped American society across science, business, sports, arts, government, education, and culture
Eleven curated collections from the Library of Congress' American Folklife Center featuring interviews, photographs, songs, music, dance, and oral histories that illustrate the lived experiences of immigrants across generations

By pairing rigorous research with historical storytelling, the timeline offers a multidimensional look at one of the defining forces in American history.

The project, developed in collaboration with the Immigrant Learning Center, the CHSSWeb team, and the American Folklife Center at the Library of Congress, reflects the institute's broader mission to generate and amplify nonpartisan research on immigration through data, arts, and public engagement. As conversations surrounding immigration continue to evolve, the institute hopes resources like the timeline will foster more informed public dialogue by providing accessible, evidence-based information grounded in historical context.

"This timeline demonstrates that immigration is not simply a contemporary issue—it is woven throughout the American story," Kiss said. "Understanding that history helps us better understand who we are as a nation today."

The release comes as communities across the country commemorate the nation's semiquincentennial, providing educators and organizations with a timely resource for exploring the role immigrants have played in shaping the United States over the past two and a half centuries.

View the interactive timeline

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George Mason researcher develops an affordable helping hand for stroke recovery

Nathan Kahl — Tue, 14 Jul 2026 19:25:34 +0000

George Mason researcher develops an affordable helping hand for stroke recovery Nathan Kahl Tue, 07/14/2026 - 15:25

For millions of stroke survivors, something as simple as picking up a glass of water or holding a sandwich is a daily challenge. Quentin Sanders wants to make those moments easier through wearable robotic technology designed to restore hand function.

The 91�� assistant professor is developing a new generation of hand exoskeletons that may help people regain independence after stroke. His lab is testing wearable devices that amplify a user's remaining muscle activity, allowing them to open and close their hand more effectively while remaining affordable enough for broader use.

Sanders' prior work focused on lower-limb prosthetics. Photo by Ron Aria/Office of University Branding

The latest prototype resembles a lightweight glove that fits over the hand and upper arm. As users attempt to move their hand, the device detects their remaining muscle activity and assists the motion.

"We instruct them to try to open their hand," Sanders explained. "When they try to open their hand, we sense whatever residual activity they have, and then the exoskeleton amplifies that."

One version of the device seeks to use wearable ultrasound technology developed in collaboration with George Mason researcher Siddhartha Sikdar, a professor in the Department of Bioengineering and director of the Center for Medtech Innovation. The system will use wearable ultrasound sensors to monitor how muscles deform as they contract, translating those signals into movement. Another simpler version uses a button embedded in the glove that users press to control the device.

While brain-controlled devices remain the long-term aspiration for many in the field, Sanders is focused on a more practical solution that builds on the muscle activity people retain after a stroke. "I would say brain-controlled systems is kind of the holy grail. In my lab, we're going one level lower to see if we can use muscle activity to control it."

The need for better rehabilitation tools is growing. Sanders noted that roughly 800,000 people experience a stroke each year in the United States, while millions more live with its long-term effects. Advances in medicine mean more people survive strokes, but many struggle to access the lengthy rehabilitation needed to regain function.

"We're at this point where you're living a long life, but you have this need for rehab," Sanders said. "You need either consistent opportunities for movement or some type of device that can help improve your quality of life."

Commercial hand exoskeletons remain scarce in the United States, and many existing systems cost tens of thousands of dollars. Making the technology more affordable and accessible has become one of the driving goals of his research.

"You've got this large population of people who need these devices who aren't getting them," Sanders said. "I'm hoping we can make this kind of low-cost, accessible version that people can use to improve some aspect of their life."

Sanders is also working to broaden who can benefit from rehabilitation technologies. Many research studies enroll only patients who meet narrow eligibility criteria, leaving others without solutions tailored to their needs.

"I think that's the other breakthrough people are working on that my lab is working on," he said. "How can we make these devices work for a larger population?"

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EV test drives are supposed to boost adoption—but they can backfire

Katelynn C Hipolito — Tue, 14 Jul 2026 14:38:54 +0000

EV test drives are supposed to boost adoption—but they can backfire Katelynn C Hipolito Tue, 07/14/2026 - 10:38

One of the biggest obstacles to wider adoption of electric vehicles (EV) is completely invisible and unquantifiable. It’s the belief in many consumers’ minds that the range restrictions of EV make it a bad option for them. Doubts about mobility, whether or not they are well-founded, can run neck-and-neck with curiosity in the minds of consumers, keeping them from making the switch from ICE (internal combustion engine) to EV.

Hang Ren, professor in the information systems and operations management. Photo provided

These doubts are beyond the remedial reach of automakers and sustainability-minded policymakers. Within the EV ecosystem, auto dealerships are the ones most directly responsible for allaying buyers’ concerns. Newly published research by Ioannis Bellos and Hang Ren, professors in the information systems and operations management area at Costello College of Business at 91��, focuses on one of the main levers at the dealers’ disposal: extended test drives. Bellos and Ren’s paper in Production and Operations Management was co-authored by Vishal Agrawal of Georgetown University.

Test drives have become a standard addition to the EV dealer’s toolkit. For example, BMW's Extended Test Drive Program lets customers use an EV for several days, and Volvo's Test Drive+ lends cars for up to four days. In some cases, government-sponsored initiatives such as Drive Electric USA (a partnership with the U.S. Department of Energy) have worked at the local level to facilitate test drives intended to educate consumers about EV.

“A car’s advertised range is public, but the range a driver actually gets depends on personal habits and conditions they can only learn through hands-on experience—which is why dealer demonstrations like extended test drives matter,” say Bellos and Ren. In other words, test drives can prevent range-based doubts from overtaking curiosity. Indeed, if consumers are pleasantly surprised by their experience with the EV, they can leave doubt in the dust, as they zoom ahead all the way to an accomplished sale.

But it can also work the opposite way, as the researchers found using a game-theoretic model of plausible buying conditions. Included in the model were buyers with a range of mobility needs. In the hypothetical scenario, consumers’ natural (pre-test drive) inclination was to favor EV if their needs were high, since high-needs drivers spend more on fuel and EV is gas-free. As in real life, however, even these simulated consumers would not purchase an EV if their overall impression was unfavorable.

Ioannis Bellos, professor in the information systems and operations management. Photo provided

“Offering demonstration service does not always mean that you’ll be convincing the customer to switch to EV,” Bellos says. “As a matter of fact, it may do the opposite—if the test drive convinces the customer that the achievable range is not enough to meet their need.”

The reseachers’ model shows that as EV technology begins to mature, becoming cheaper to produce and thus more profitable, the dealer’s incentive is to offer as many extended test drives as possible to boost sales. But once production costs fall below a certain threshold, the profit potential of EV becomes so high that dealers would be wise not to risk turning a percentage of customers away (or toward conventional ICE vehicles) by offering test drives.

In addition to implications for dealer profits, this dynamic has environmental significance. “If we consider two customers—one who takes a test drive and decides EV is not a good fit, and another who is convinced to purchase an EV after a test drive—the net effect on adoption is zero. They cancel each other out,” says Ren. “Yet the net emissions can increase, because that first customer probably drives more—that’s the reason they were interested in EV in the first place.”

Test drives, then, can be net-negative for the planet to the extent that they deter heavy-use drivers from switching to EV by resolving their range-based doubts.

The researchers also found that test drives can negate the impact of tightening CAFE standards from the U.S. Department of Transportation, which set mandated fuel-economy levels for all automakers. One result of CAFE standards is to encourage production of more fuel-efficient EV as opposed to ICE vehicles. CAFE does not apply to dealers, however. As higher fuel-economy standards pressure automakers to raise wholesale prices for ICE vehicles, the expected switch from ICE to EV is inhibited by the unfavorable impression left in some consumers’ minds by the test drive. The researchers found this can flip the policy's intended effect: Without test drives, tougher CAFE standards reliably push EV adoption up, but once dealers offer test drives, a strict-enough standard can actually leave adoption lower than it would otherwise be.

Bellos and Ren conclude that “dealer demonstration is a powerful but double-edged lever that must be deployed strategically.” The environmental and financial benefits of try-before-you-buy are likely tied to the EV market’s growing pains, and may diminish as it matures.

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The new art of herding robots

tdonnel — Mon, 13 Jul 2026 16:15:27 +0000

The new art of herding robots tdonnel Mon, 07/13/2026 - 12:15

As autonomous systems grow in number and complexity, researchers at 91�� are tackling a critical question: How can a single human operator manage an entire swarm of robots? Professors Alexander Brodsky, Cameron Nowzari, and Daigo Shishika are designing smart-swarm technologies to help military planners coordinate unmanned aerial and ground vehicles within Human-Machine Integrated Formations.

The urgency of this work comes from rapidly evolving real-world conditions. Drone incursions are increasing in both frequency and affordability, explained Nowzari, adding, “It still requires a centralized and expensive response from the Air Force just to take down a $200 drone.”

Astroswarm logo. Image provided.

Swarm robotics offers an alternative. By deploying many low-cost systems, the team aims to shift the economics of defense. “To take out a $200 drone, we want to do it in less than $2,000,” Nowzari explained.

But this introduces a new bottleneck: human attention. “If you have one pilot per robot, you’ve defeated the purpose,” he said. The goal is for “one or two people to manage, coordinate, monitor, and control hundreds of robots.”

The team’s goal is to enable military planners to assemble, adapt, and deploy swarm-control and coordination systems using mo dular,building-block components, reducing complexity while improving mission effectiveness.

They are building a Smart Swarm system with three components: a Swarm Decision Guidance Assistant, Swarm Operations Assistant, and Adversarial Risk Assistant. Together, these tools help operators interpret data, assign tasks, and respond to changing conditions without being overwhelmed.

This human-centered philosophy extends to the interface itself. The team is developing tools such as tablet-based dashboards where operators can issue commands and monitor activity. Deciding what information to display is a major research question.

“If we show them everything, it’s overwhelming,” Nowzari said. “They can’t do anything with it.” The challenge of data overload is top of mind for American military leaders taking lessons from Ukraine, he added.

A frame from Astroswarm. Image provided.

To explore these questions, the project incorporates an unexpected element: a video game. Built by undergraduate researcher Gagan Manjunatha, the simulator translates swarm behavior into an interactive, accessible format. In the game, called Astroswarm, players design simple algorithms to control fleets of spaceships defending a target, mirroring real-world swarm coordination.

Using intuitive, block-based coding, players can program their ships, experimenting with strategies in real time. The system then collects this data and runs large-scale simulations. “We’ll collect simulations and run many trials and see who has the best algorithm for defending a point,” explained Manjunatha.

The game is designed to be accessible to a wide audience while generating valuable insights into how humans design and adapt swarm behaviors. Supported by a $966,836 award from the U.S. Department of the Army, the research will continue through 2028.

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Faculty philanthropy fuels quantum innovation with $3 million gift

ckearney — Fri, 10 Jul 2026 18:50:35 +0000

Faculty philanthropy fuels quantum innovation with $3 million gift ckearney Fri, 07/10/2026 - 14:50

Quantum science is a revolution in the making, and a recent donation by Department of Physics and Astronomy Professor Paul So has placed 91�� at the forefront of understanding and harnessing its capabilities.

Paul So. Photo by Hamiltonian Artists

Through a generous $3 million gift from So’s SYYK Foundation, George Mason’s College of Science will be able to advance the education of the next generation of quantum scientists. The gift will establish an endowed professorship within the Department of Physics and Astronomy. The university seeks an esteemed faculty member to fill this role, with a preference for a scientist who has expertise in quantum sciences, “someone with new ideas,” said So, “who will create a vibrant space in the department.”

“It’s important to think about quantum as a revolutionary and game-changing leap ahead in our ability to compute, to sense the world around us, and to communicate with each other,” said Patrick Vora, associate professor in the Department of Physics and Astronomy, and director of George Mason’s Quantum Science and Engineering Center.

The goal of the professorship is to build a community of learning around quantum technology, said Vora. “It will catalyze new collaborations between faculty members, but always, at the end of the day, our biggest impact is going to be in training our students.”

Quantum mechanics describes the behavior of subatomic particles and their properties. Understanding and controlling those properties could drive significant advances in engineering and technology, said Vora, who is leading George Mason’s Quantum Leap, one of seven newly funded catalyst projects in the university’s Grand Challenge Initiative.

“Your phone runs on quantum science, your computer runs on quantum science,” So added. “New materials, new technologies, and new applications will all rely on quantum.” That could include enhanced weather prediction as well as faster drug discovery and development.

So founded SYYK with his brother Peter, a professor of mechanical and biological engineering at MIT, to continue their mother’s philanthropic efforts after her death in 2021. The charitable nonprofit has a broad mission but prioritizes gifts to educational and cultural institutions.

“Even when we were growing up in Hong Kong, my parents supported local schools,” So said. “They appreciated that education was the foundation of a kid’s future, the foundation of society’s future.”

So believes that strengthening the quantum science program at George Mason will attract top students to the university and encourage more cross-pollination between disciplines like math, computer science, and engineering.

“One of the biggest challenges of realizing quantum technology is less about the ‘quantum’ and more the people,” Vora said. “Developing the science into an industry will require a significant expansion of the workforce. The only way that you can do that is by expanding representation in the workforce. And there are few things that George Mason does as well as providing opportunity for people who may not have had it before.”

So is optimistic that the investment in quantum will better position students to take advantage of the unique opportunity George Mason offers. “We’re right here in the National Capital region, near so many tech companies,” he said, “and there’s a lot of support from the government to develop quantum.”

Indeed, the federal government recently announced that it would inject $2 billion into quantum development, funding nine domestic computer companies to build quantum infrastructure. The White House, meanwhile, also issued executive orders to accelerate the migration of federal computing systems to systems that can protect them from quantum cyberattacks. Quantum-related job postings have tripled in the last 15 years with an average salary of $131,000.

The structure of the new professorship is a novel one at George Mason. The professor’s salary will be covered by the College of Science, while proceeds from the endowment will serve as discretionary funding to support graduate students. The donation also includes a percentage of the gift applied as “current use” funds, available now to provide support while the endowment yield grows.

“Paul So’s extraordinary generosity gives George Mason the ability to move with both urgency and ambition in quantum science,” said Cody W. Edwards, dean of the College of Science. “This endowed professorship will help us recruit a field-shaping scholar, support graduate students, and accelerate the collaborations needed to prepare the next generation of quantum scientists and innovators. It is a gift with immediate impact, long-term vision, and profound significance for the College of Science, George Mason, and the commonwealth.”

Given the surge in quantum investment and jobs around the country, So hopes the gift will encourage additional giving to support quantum at George Mason. “Compared to what is needed, this is just the start,” he said.

“We’re talking about a generation-scale technological shift,” said Vora. “Bringing on this new faculty member, around which our current and future faculty members can collaborate and coalesce, will really change what it looks like to be a quantum scientist in the future.”

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Can AI help make medical records less biased? New study suggests yes—with caveats

Heather Carroll — Fri, 10 Jul 2026 16:50:49 +0000

Can AI help make medical records less biased? New study suggests yes—with caveats Heather Carroll Fri, 07/10/2026 - 12:50

Large language models can identify judgmental language in clinical notes but the settings play a major role in accuracy.

Teenu Xavier PhD, RN. Photo provided

“Addict,” “non-compliant,” “failed treatment,” and “obese person” are examples of stigmatizing language that can appear in medical records. At 91��’s College of Public Health, researchers are exploring whether artificial intelligence (AI) can help identify this kind of language in clinical notes before it impacts patient care.

Nurse scientist Teenu Xavier and colleagues found that large language models (LLMs) show promise in identifying stigmatizing language in clinical documentation, but their performance is highly dependent on their settings. Model size, temperature settings, prompting strategies, and even note type can substantially influence results.

One finding was consistent across every model tested: Providing examples of stigmatizing language improved accuracy.

“Simply selecting an LLM is not enough when used for clinical documentation,” said Xavier, an assistant professor in the School of Nursing. “Careful attention must be paid to settings and prompting before these tools can be reliably used in health care environments.”

Why does this matter?

The use of stigmatizing language in clinical documentation can reinforce bias and affect a patient’s future care. AI tools may be able to help identify this kind of language, promoting more equitable care and improving patient trust and experience.

“Pre-trained models, when optimized for identifying stigmatizing language, could help enable more timely interventions and modifications to the documentation process,” Xavier said. “Our research highlights the need for continued collaboration between health care professionals and AI developers to create tools that improve communication, reduce bias, and improve the overall patient experience.”

What are the detailed study findings?

The largest LLM (trained on large amounts of data) was the best at predicting “stigmatizing” language (94%), but the worst at predicting “not stigmatizing” correctly (47%).
The smallest LLM was the best at predicting “not stigmatizing” correctly (99.7%), but worst at predicting “stigmatizing” correctly (2%).
When researchers gave the LLM an example of stigmatizing language, accuracy improved in all models.
Emergency provider notes were most accurately (69%) categorized as “stigmatizing” or “non-stigmatizing,” and plan of care notes had the lowest accuracy (56%). Misclassifications most commonly arose in long, clinically dense notes where neutral descriptions of complex illness or adverse events were mistaken by the models for judgmental language.
Larger models worked best at lower temperature (how predictable or random the LLMs’s output is when making a classification) and smaller models improved with higher temperature, which means the LLM took more risks in interpretation.

“Detecting stigmatizing language with large language models: mind the settings” was published in JAMIA Open in April 2026. Co-authors include Jane M. Carrington from the University of Florida and Joshua Lambert from the University of Cincinnati.

Thumbnail photo by issaronow from Adobe Stock.

Key Takeaways

A George Mason study found that large language models show promise in identifying stigmatizing language in clinical documentation, but their performance is highly dependent on their settings, such as model size, temperature settings, prompting strategies, and note type.
The ability to detect and correct stigmatizing language early can reduce bias in patient care and lead to improved patient trust and better health outcomes.
Continued collaboration between health care workers and AI developers is needed to create tools that enhance communication, reduce bias, and improve the overall patient experience.

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George Mason researcher develops interactive tool to measure carbon footprint of AI use in K-12 education

Katarina Benson — Fri, 10 Jul 2026 15:53:35 +0000

George Mason researcher develops interactive tool to measure carbon footprint of AI use in K-12 education Katarina Benson Fri, 07/10/2026 - 11:53

As artificial intelligence (AI) applications like ChatGPT become more commonplace in K-12 classrooms, school district leaders and policymakers will face the challenge of ensuring these tools are used in an ethical, responsible, and environmentally sustainable way. Seth B. Hunter, associate professor of education leadership and senior fellow in the EdPolicyForward center at 91��, has developed an interactive tool to help.

The tool enables school district policymakers to make better informed decisions on selecting AI software that meets the learning needs of their students and promotes environmental sustainability.

Seth Hunter. Photo by John Boal Photography

“The many conversations I’ve had with leaders across the commonwealth and nation have focused almost exclusively on the potential benefits of AI—benefits that, I should point out, we don’t yet understand well,” said Hunter. “Almost no one is talking about the costs beyond the purchase price. This tool is one way to start filling that gap—by estimating a cost that’s seemingly invisible: the additional energy and emissions that come with putting these tools in students’ hands.”

The tool enables users to input data on the total number of students enrolled in a school district, the number of students expected to use AI (based on surveys from peer-reviewed research), the anticipated number of daily queries they are likely to conduct, and the level of AI processing power needed to handle those queries. It also allows users to select their state from a dropdown menu. Next to each state is a number indicating the amount of carbon dioxide in grams released per kilowatt hour of electricity consumed.

Using these inputs, the tool calculates the increases in kilowatt hours and the carbon emissions generated by AI use. To help users better understand the significance of these estimates, the tool translates the data into every day, real-world equivalents—such as the number of miles driven with a car, the number of days a lightbulb could run continuously, or how many times a smartphone could be charged.

In addition, the tool shows what the trajectory of carbon emissions associated with the use of AI in schools will be through 2031 if no policies are put in place to reduce the associated carbon footprint.

“Even leaders with very little technical understanding of AI have many opportunities to influence its energy consumption, and it starts with a simple conversation with the vendor,” Hunter stated. “I’m not talking about choosing one brand over another, like Gemini versus ChatGPT. I'm talking about the type of model. Within a single company’s family of models, the ones built to ‘reason’ or ‘think’ through problems at length currently consume far more energy than lighter models designed for simpler tasks. The most useful question a procurement office can ask is how much a model relies on that extended ‘reasoning,’ and whether a lighter model would meet students’ needs.”

School district leaders will need to consider several factors, such as the complexity of the task the AI tool will be used to support. For example, if an AI chatbot is used to help students with multi-step math problem-solving, it will use more energy than simpler tasks such as quick factual lookups or summarizing an article. Increases in energy requirements and carbon emissions will also be influenced by the number of students accessing AI and the average number of daily queries they conduct. The type of energy source used in the school district will also have an impact. Renewable energy sources like solar, wind, or hydropower produce less carbon compared to power sources like coal.

“No one wants their students to fall behind in what can feel like an AI arms race,” said Hunter. “But I argue that policymakers and system leaders should ask how much those advantages outweigh the financial, environmental, and social costs. This tool doesn’t make that decision for anyone, but it estimates one of the costs that usually gets left out, so leaders can weigh student learning and environmental sustainability in the same conversation.”

Test out the interactive tool: "The Carbon Footprint of AI in K–12 Education"

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