AI Research
Studying Falls to Save Lives

For older adults, falling is a major concern. It’s the leading cause of injury for those over 65 and the consequences can be life-threatening.
“Falling itself isn’t the issue—it’s the injury that’s really harmful for older adults,” says Syracuse University exercise science professor Yaejin Moon, who lost two of her grandparents to fall-related injuries.
The experience of losing a family member, friend or neighbor from complications after a fall is all too universal. That’s why Moon and Ph.D. student Reese Michaels G’24 are using cutting-edge research tactics—combining advanced artificial intelligence (AI) video analysis with traditional lab research—to learn how people fall and how to prevent serious injury.
Analyzing Falls With AI and Custom Code
AI-powered tools like OpenPose and WHAM are replacing traditional motion-tracking markers, allowing researchers to study movement more easily in real-world settings.
Traditionally, studying human movement meant attaching motion-tracking markers to the body—a technique common in gaming, film and movement science. Today, however, advances in AI make it possible to analyze movement directly from standard video footage.
“If we take a video—even from an iPhone—and input it into the system, the AI can automatically detect key body points and track motion. We don’t need markers anymore,” explains Moon, referring to AI-based pose estimation algorithms such as OpenPose.
Working with researchers in Canada, Moon and Michaels have access to over 1,700 real-life fall videos from surveillance footage in long-term care facilities and hospitals. Using OpenPose and Michaels’ custom code, the research pair track body position and extract biomechanical data to identify which types of falls result in injury and evaluate which movements protect against harm.
“It’s like having access to a black box for accidents,” Moon says. “We can analyze exactly what happened.”
Although Michaels had no prior coding experience, he took a graduate-level Python course through Syracuse’s School of Information Studies. “It was trial by fire, but I was able to write code for one of our projects, and I realized I could apply those skills in a meaningful way to research,” says Michaels, who started working with Moon in the Falk College of Sport as an exercise science master’s student two years ago.
“He can calculate things like velocity of the fall, acceleration and knee angle at the moment of impact—very specific biomechanical outcomes—all generated through his own programming,” Moon says.
As the AI models continue to improve, the team’s research also advances. “These newer AI models can track movement in three dimensions rather than two,” Michaels explains. “That gives us much more insight into things like joint angles during a fall, which opens the door to more realistic and accurate analysis.”
“The goal is to implement this kind of technology in long-term care settings to get real-time insights into how people move and how injuries happen,” Michaels says.
Falk College professor Yaejin Moon (left) uses a special treadmill to simulate sudden loss of balance, while motion-capture cameras track how participants respond.
In the lab, the AI models are validated using a specialized treadmill that safely simulates balance loss. The treadmill can move forward, backward and side to side while participants wear a safety harness and adjust to the sudden changes in movement. Motion-capture cameras record every step and reaction.
Falls happen in three phases: the initial phase (standing or walking normally), the loss-of-balance phase (when the fall begins) and the impact phase (when the body hits the ground).
New AI models allow researchers to track movement in 3D, greatly improving the accuracy and realism of fall analysis.
“The perturbation treadmill is used to study that second phase—the moment when balance is lost,” Moon says. “We analyze how people react to losing balance and how they try to recover.”
The research also explores dual-task conditions—how cognitive load impacts the ability to recover balance. Participants are asked to perform mental tasks, such as listing animals or counting backward from 100 by sevens, while walking. This adds a layer of realism, simulating situations where older adults might be distracted by thinking, talking or multitasking while moving.
“Do we recover balance faster when we’re focused solely on walking? Or is our response slower or different when our attention is divided?” Moon inquires.
Research in the Real World
Ph.D. student Reese Michaels G’24 is the lead author of two studies—one published in Scientific Reports and another currently under review in the Journal of Biomechanics.
So, how will this ongoing research impact people’s everyday lives? Moon breaks it down into three key components: “First is understanding the mechanisms—how the body and mind work together during a fall. Second is developing intervention programs. And third is improving technology.”
Michaels, who is now in his second year of the exercise science Ph.D. program, is especially focused on improving technology.
A third-degree black belt in Taekwondo, Moon began her research by teaching older adults how to fall safely using martial arts. Now, she and Michaels are using AI tools to better understand falls and develop new ways to prevent serious injuries.
“One of our next steps is feeding outputs from pose estimation models into a machine learning algorithm that could predict impact force—how hard someone hit the ground,” explains Michaels. “That would give us a direct measure of whether a fracture or injury occurred.”
The pair is also working to make their video analysis methods more generalizable. With ongoing AI advancements and more real-world video data, the team hopes to analyze situations that can’t be replicated in a lab, such as falls down a set of stairs, and to address different age and health groups.
By combining AI, biomechanics and real-world data, this research is not only advancing the study of falls but also laying the foundation for innovative solutions to prevent injuries in aging populations. As technology continues to evolve, their work promises to lead to more precise strategies that could significantly reduce the risks older adults face, ultimately improving their quality of life and safety.
AI Research
Brown awarded $20 million to lead artificial intelligence research institute aimed at mental health support

A $20 million grant from the National Science Foundation will support the new AI Research Institute on Interaction for AI Assistants, called ARIA, based at Brown to study human-artificial intelligence interactions and mental health. The initiative, announced in July, aims to help develop AI support for mental and behavioral health.
“The reason we’re focusing on mental health is because we think this represents a lot of the really big, really hard problems that current AI can’t handle,” said Associate Professor of Computer Science and Cognitive and Psychological Sciences Ellie Pavlick, who will lead ARIA. After viewing news stories about AI chatbots’ damage to users’ mental health, Pavlick sees renewed urgency in asking, “What do we actually want from AI?”
The initiative is part of a bigger investment from the NSF to support the goals of the White House’s AI Action Plan, according to a NSF press release. This “public-private investment,” the press release says, will “sustain and enhance America’s global AI dominance.”
According to Pavlick, she and her fellow researchers submitted the proposal for ARIA “years ago, long before the administration change,” but the response was “very delayed” due to “a lot of uncertainty at (the) NSF.”
One of these collaborators was Michael Frank, the director of the Center for Computational Brain Science at the Carney Institute and a professor of psychology.
Frank, who was already working with Pavlick on projects related to AI and human learning, said that the goal is to tie together collaborations of members from different fields “more systematically and more broadly.”
According to Roman Feiman, an assistant professor of cognitive and psychological sciences and linguistics and another member of the ARIA team, the goal of the initiative is to “develop better virtual assistants.” But that goal includes various obstacles to ensure the machines “treat humans well,” behave ethically and remain controllable.
Within the study, some “people work basic cognitive neuroscience, other people work more on human machine interaction (and) other people work more on policy and society,” Pavlick explained.
Although the ARIA team consists of many faculty and students at Brown, according to Pavlick, other institutions like Carnegie Mellon University, University of New Mexico and Dartmouth are also involved. On top of “basic science” research, ARIA’s research also examines the best practices for patient safety and the legal implications of AI.
“As everybody currently knows, people are relying on (large language models) a lot, and I think many people who rely on them don’t really know how best to use them, and don’t entirely understand their limitations,” Feiman said.
According to Frank, the goal is not to “replace human therapists,” but rather to assist them.
Assistant Professor of the Practice of Computer Science and Philosophy Julia Netter, who studies the ethics of technology and responsible computing and is not involved in ARIA, said that ARIA has “the right approach.”
Netter said ARIA approach differs from previous research “in that it really tried to bring in experts from other areas, people who know about mental health” and others, rather than those who focus solely on computer science.
But the ethics of using AI in a mental health context is a “tricky question,” she added.
“This is an area that touches people at a point in time when they are very, very vulnerable,” Netter said, adding that any interventions that arise from this research should be “well-tested.”
“You’re touching an area of a person’s life that really has the potential of making a huge difference, positive or negative,” she added.
Because AI is “not going anywhere,” Frank said he is excited to “understand and control it in ways that are used for good.”
“My hope is that there will be a shift from just trying stuff and seeing what gets a better product,” Feiman said. “I think there’s real potential for scientific enterprise — not just a profit-making enterprise — of figuring out what is actually the best way to use these things to improve people’s lives.”
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AI Research
BITSoM launches AI research and innovation lab to shape future leaders

Mumbai: The BITS School of Management (BITSoM), under the aegis of BITS Pilani, a leading private university, will inaugurate its new BITSoM Research in AI and Innovation (BRAIN) Lab in its Kalyan Campus on Friday. The lab is designed to prepare future leaders for workplaces transformed by artificial intelligence, on Friday on its Kalyan campus.
While explaining the concept of the laboratory, professor Saravanan Kesavan, dean of BITSoM, said that the BRAIN Lab had three core pillars–teaching, research, and outreach. Kesavan said, “It provides MBA (masters in business administration) students a dedicated space equipped with high-performance AI computers capable of handling tasks such as computer vision and large-scale data analysis. Students will not only learn about AI concepts in theory but also experiment with real-world applications.” Kesavan added that each graduating student would be expected to develop an AI product as part of their coursework, giving them first-hand experience in innovation and problem-solving.
The BRAIN lab is also designed to be a hub of collaboration where researchers can conduct projects in partnership with various companies and industries, creating a repository of practical AI tools to use. Kesavan said, “The initial focus areas (of the lab) include manufacturing, healthcare, banking and financial services, and Global Capability Centres (subsidiaries of multinational corporations that perform specialised functions).” He added that the case studies and research from the lab will be made freely available to schools, colleges, researchers, and corporate partners, ensuring that the benefits of the lab reach beyond the BITSoM campus.
BITSoM also plans to use the BRAIN Lab as a launchpad for startups. An AI programme will support entrepreneurs in developing solutions as per their needs while connecting them to venture capital networks in India and Silicon Valley. This will give young companies the chance to refine their ideas with guidance from both academics and industry leaders.
The centre’s physical setup resembles a modern computer lab, with dedicated workspaces, collaborative meeting rooms, and brainstorming zones. It has been designed to encourage creativity, allowing students to visualise how AI works, customise tools for different industries, and allow their technical capabilities to translate into business impacts.
In the context of a global workplace that is embracing AI, Kesavan said, “Future leaders need to understand not just how to manage people but also how to manage a workforce that combines humans and AI agents. Our goal is to ensure every student graduating from BITSoM is equipped with the skills to build AI products and apply them effectively in business.”
Kesavan said that advisors from reputed institutions such as Harvard, Johns Hopkins, the University of Chicago, and industry professionals from global companies will provide guidance to students at the lab. Alongside student training, BITSoM also plans to run reskilling programmes for working professionals, extending its impact beyond the campus.
AI Research
AI grading issue affects hundreds of MCAS essays in Mass. – NBC Boston

The use of artificial intelligence to score statewide standardized tests resulted in errors that affected hundreds of exams, the NBC10 Investigators have learned.
The issue with the Massachusetts Comprehensive Assessment System (MCAS) surfaced over the summer, when preliminary results for the exams were distributed to districts.
The state’s testing contractor, Cognia, found roughly 1,400 essays did not receive the correct scores, according to a spokesperson with the Department of Elementary and Secondary Education.
DESE told NBC10 Boston all the essays were rescored, affected districts received notification, and all their data was corrected in August.
So how did humans detect the problem?
We found one example in Lowell. Turns out an alert teacher at Reilly Elementary School was reading through her third-grade students’ essays over the summer. When the instructor looked up the scores some of the students received, something did not add up.
The teacher notified the school principal, who then flagged the issue with district leaders.
“We were on alert that there could be a learning curve with AI,” said Wendy Crocker-Roberge, an assistant superintendent in the Lowell school district.
AI essay scoring works by using human-scored exemplars of what essays at each score point look like, according to DESE.
DESE pointed out the affected exams represent a small percentage of the roughly 750,000 MCAS essays statewide.
The AI tool uses that information to score the essays. In addition, humans give 10% of the AI-scored essays a second read and compare their scores with the AI score to make sure there aren’t discrepancies. AI scoring was used for the same amount of essays in 2025 as in 2024, DESE said.
Crocker-Roberge said she decided to read about 1,000 essays in Lowell, but it was tough to pinpoint the exact reason some students did not receive proper credit.
However, it was clear the AI technology was deducting points without justification. For instance, Crocker-Roberge said she noticed that some essays lost a point when they did not use quotation marks when referencing a passage from the reading excerpt.
“We could not understand why an individual score was scored a zero when it should have gotten six out of seven points,” Crocker-Roberge said. “There just wasn’t any rhyme or reason to that.”
District leaders notified DESE about the problem, which resulted in approximately 1,400 essays being rescored. The state agency says the scoring problem was the result of a “temporary technical issue in the process.”
According to DESE, 145 districts were notified that had at least one student essay that was not scored correctly.
“As one way of checking that MCAS scores are accurate, DESE releases preliminary MCAS results to districts and gives them time to report any issues during a discrepancy period each year,” a DESE spokesperson wrote in a statement.
Mary Tamer, the executive director of MassPotential, an organization that advocates for educational improvement, said there are a lot of positives to using AI and returning scores back to school districts faster so appropriate action can be taken. For instance, test results can help identify a child in need of intervention or highlight a lesson plan for a teacher that did not seem to resonate with students.
“I think there’s a lot of benefits that outweigh the risks,” said Tamer. “But again, no system is perfect and that’s true for AI. The work always has to be doublechecked.”
DESE pointed out the affected exams represent a small percentage of the roughly 750,000 MCAS essays statewide.
However, in districts like Lowell, there are certain schools tracked by DESE to ensure progress is being made and performance standards are met.
That’s why Crocker-Roberge said every score counts.
With MCAS results expected to be released to parents in the coming weeks, the assistant superintendent is encouraging other districts to do a deep dive on their student essays to make sure they don’t notice any scoring discrepancies.
“I think we have to always proceed with caution when we’re introducing new tools and techniques,” Crocker-Roberge said. “Artificial intelligence is just a really new learning curve for everyone, so proceed with caution.”
There’s a new major push for AI training in the Bay State, where educators are getting savvier by the second. NBC10 Boston education reporter Lauren Melendez has the full story.
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