Research

First-of-its-kind research identifies beneficial prenatal vitamins to reduce risk of infant death

Jennifer Pocock — Thu, 30 Jan 2025 15:19:14 +0000

First-of-its-kind research identifies beneficial prenatal vitamins to reduce risk of infant death Jennifer Pocock Thu, 01/30/2025 - 10:19

In This Story

Dongqing Wang, PhD, MPH

Assistant Professor of Global and Community Health Dongqing Wang publishes landmark analysis on the impacts of prenatal vitamins on mothers and newborns in the Lancet Global Health

Dongqing Wang, PhD, MPH

Dongqing Wang, an assistant professor of Global and Community Health at George Mason’s College of Public Health, is pioneering research in prenatal nutritional interventions. His latest report identifies prenatal supplements that reduce health risks to small and vulnerable babies. This research was published in the prestigious Lancet Global Health journal and funded by the Bill and Melinda Gates Foundation.

Wang found that compared to folic acid and iron alone, a multiple micronutrient supplement led to a 27% lower risk of giving birth to “small vulnerable newborn types,” or babies who suffered from preterm birth, low birthweight, and small-for-gestational-age birth—the three groups most likely to result in infant death.

In the past, these birth outcomes were all treated as separate conditions. Wang, however, delves into emerging science to look at different combinations across the three outcomes. Low birthweight, for example, can occur because of a short pregnancy, and growth restrictions can lead to babies born too small for their developmental age.

“Small vulnerable newborn types may have distinct mechanisms, health impacts, and intervention strategies,” says Wang. “This work is the first to examine the effects of prenatal multiple micronutrient supplements and small-quantity lipid-based nutrient supplements on the emerging outcomes of small vulnerable newborns.”

Folic acid and iron have been used to support prenatal health since the 1970s. Wang explored the effects of two additional types of prenatal supplements on women in low- and middle-income countries: prenatal multiple micronutrient supplements (MMS), similar to a common multivitamin, and small-quantity lipid-based nutrient supplements (SQ-LNS), which provide caloric nutrition and fatty acids in addition to vitamins.

He found that nearly all of these vitamins conferred some type of benefit—and some of them were hugely beneficial.

“This study underscores the important promise of nutritional supplements in prenatal care in low- and middle-income countries,” says Wang. “In particular, the protective effects of prenatal multiple micronutrients on most small vulnerable newborn types, particularly those with the greatest mortality risk, strongly supports switching from iron and folic acid supplements to MMS as the standard care.”

Combining 16 different studies, Wang analyzed how prenatal nutrition correlates to the occurrence of small vulnerable newborns. He believes that the right prenatal supplements can help mitigate them. Since more than 90% of pregnancies resulting in low birthweight occur in low- and middle-income countries, including those in sub-Saharan Africa and South Asia, Wang focused this work on those regions.

The Lancet Global Health published "The effects of prenatal multiple micronutrient supplements and small-quantity lipid- based nutrient supplements on small vulnerable newborn types in low- and middle- income countries: a meta-analysis of individual participant data” in January 2025. Additional authors include Enju Liu, Nandita Perumal, Uttara Partap, Ilana R. Cliffer, Janaína Calu Costa, Molin Wang, Wafaie W. Fawzi, and more than 40 data contributors from all over the world who provided the individual participant data used in this landmark analysis.

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George Mason scientists partner to create genetic markers for endangered species

Katarina Benson — Wed, 29 Jan 2025 15:37:16 +0000

George Mason scientists partner to create genetic markers for endangered species Katarina Benson Wed, 01/29/2025 - 10:37

Scientists have long recognized that both wild and captive populations of endangered species are at a high risk for loss of genetic diversity due to their rarity. With small or isolated populations, genetic diversity can be lost through stochastic or random genetic drift, or through breeding between close relatives. Therefore, proper management of captive populations is critical to ensure long-term sustainability.

Haw Chuan Lim. Photo provided

The struggle, however, is how to efficiently and economically collect and analyze high-resolution genetic data that can fill the knowledge information gaps in effective breeding practices.

Haw Chuan Lim, associate professor in ��AV’s Department of Biology, saw an opportunity to combine the experience and knowledge of other experts in the field to develop a novel genomic tool to address this issue.

Lim’s proposal, “Development of a novel genotyping panel for powerful and cost-effective evaluations of population structure and kinship in the critically endangered mountain bongo,” was approved for funding by the 4-VA @ Mason Advisory Board.

Lim and his PhD student Karen Holm assembled their team — Aakrosh Ratan, assistant professor, University of Virginia; Klaus-Peter Koepfli, senior research scientist, Smithsonian-Mason School of Conservation; and Budhan Pukazhenthi, research physiologist, Smithsonian Conservation Biology Institute. 4VA funding was used to purchase the necessary supplies, reagents, and equipment, including DNA tests and probe sets.

The team reasoned that a study conducted on one animal could provide a platform for application to other endangered species. The Eastern mountain bongo, or antelope, a critically endangered native to Kenya, was chosen as a test species. Although fewer than 140 bongos remain in the wild, there are approximately 160 bongos in U.S. zoos and several hundred more on private ranches. As such, breeding and transfer strategies that increase genetic diversity and reduce inbreeding of captive animals are critical for the survival of the species.

Eastern mountain bongo. Photo courtesy of the Lim Lab

The researchers created and validated the application of a novel genetic probe-set that was used to generate data from different types of genetic markers, such as ease of genotyping, presence throughout the genome, and high information content.

Researchers collected four types of samples—whole blood, fecal swabs, tissues, and extracted DNA—from 39 North American conservation centers and zoos to begin the project. This resulted in a total of 207 samples from both current and historical ex situ populations (populations outside of the native ranges).

Lim and his team evaluated the effectiveness of the probe-set in generating high-quality genetic data from different sample types and for different genetic marker types. The data obtained are now being accessed for their ability to produce accurate information on animal kinship, genetic diversity, and population structure, which will ultimately be used to guide precise captive breeding programs.

Some preliminary data, as well as a chromosome-level genome assembly, have already been published by the National Center for Biotechnology Information and online at DNA Zoo, a conservation consortium website.

A high-quality genome serves as an invaluable resource for species conservation because it can be used for many types of research such as those focused on detecting deleterious mutations. The results from this study will contribute to the Association of Zoos and Aquariums Species Survival Plan for the species.

“The 4-VA@Mason funding got us started, and now we have obtained external funding to move the research even further,” said Lim.

Learn more about Smithsonian Mason School of Conservation

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Unlocking privacy with encrypted ingenuity: Security expert receives NSF CAREER award

Nathan Kahl — Mon, 27 Jan 2025 17:32:18 +0000

Unlocking privacy with encrypted ingenuity: Security expert receives NSF CAREER award Nathan Kahl Mon, 01/27/2025 - 12:32

In This Story

Evgenios Kornaropoulos

Evgenios Kornaropoulos, an assistant professor in ��AV’s Computer Science Department, focuses on computer security and applied cryptography, where he stays ahead of changes in the field. "The needs of everyday users have grown, and our technology's privacy expectations must advance accordingly,” he said. “We've moved beyond simply communicating sensitive data securely; now, we need technology capable of performing computations on sensitive data without compromising privacy.”

Evgenios Kornaropoulos. Photo provided

He recently received a National Science Foundation (NSF) CAREER award for $648,811 for his work on privacy and data security under the title “Encrypted Systems with Fine-Grained Leakage.”

The tension between the privacy of sensitive data and the functionality that users demand from their data is the focus of the NSF CAREER funding, and it has been among Kornaropoulos’ research areas for several years. He said, “The new technology that we are developing allows the user to never expose any information in the clear to the cloud while maintaining functionality. You want the cloud to do interesting computations for you without decrypting your information. If you don't decrypt, the cloud never gets to see what you are processing.”

When users store sensitive information, such as health records or financial data, with common cloud-based providers, the provider gains full access to the document's contents—essentially exposing the data in plain text to the cloud. A potential remedy is to encrypt the data before uploading it. However, this approach comes with a drawback: whenever users need to access or compute something from the encrypted data, they must download all the scrambled files locally and perform the computations on their own devices.

So how can the user still process the information but know that the cloud didn’t learn anything? “We believe that the answer is the notion of ‘cryptographic leakage’, he said. “The cloud provider still sees some accesses on encrypted data, that is, the leakage, but these observations are confusing. Our designs scale to today’s needs and come with provable guarantees that these observations cannot be meaningfully stitched together by the cloud provider to infer the sensitive data.”

Kornaropoulos said, “Searching on encrypted data is one of the biggest functionalities and we have a research thrust in which we will collaborate with industry leaders and local organizations on this problem. Specifically, we have an active collaboration with the Mason and Partners Clinics (interprofessional clinics which serve the uninsured and refugee community within Prince William and Fairfax counties in Northern Virginia) to explore the application scenarios of our technology to that setting.”

"Privacy-preserving data storage and data use is an important problem in computer security that is of critical interest to organizations that must trust their sensitive data to third-party data storage facilities," said Computer Science department chair David Rosenblum. "Evgenios is an internationally renowned leader in addressing this problem, and his NSF CAREER award will afford him the opportunity to explore novel solutions that balance strong security guarantees against practical needs for efficiency."

The NSF CAREER award is reserved for the nation’s most talented up-and-coming researchers. From the NSF website: “The Faculty Early Career Development (CAREER) Program offers NSF’s most prestigious award in support of early-career faculty who have the potential to serve as academic role models in research and education and to lead advances in the mission of their department or organization.”

The award is the most-recent of several distinctions Kornaropoulos has earned. He was elevated to IEEE Senior Member in 2024, his paper was among the finalists for the “Best Cryptographic Attack” category at Pwnie Awards 2024, and his latest work at the intersection of AI and security has gained significant media attention.

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Physics PhD student is using machine learning techniques to unlock the key to predicting solar flares

Katarina Benson — Mon, 27 Jan 2025 14:44:24 +0000

Physics PhD student is using machine learning techniques to unlock the key to predicting solar flares Katarina Benson Mon, 01/27/2025 - 09:44

João Felipe Sousa Pereira’s research on solar flares could one day help us safeguard astronauts and technology in space and even prevent widespread blackouts here on Earth. Pereira, a second-year Physics PhD student at ��AV, is studying solar physics with the goal of uncovering the precise triggers of solar flares.

João Felipe Sousa Pereira. Photo by Evan Cantwell/Office of University Branding

Pereira said solar flare prediction is key because really intense solar flares are often associated with coronal mass ejections (CMEs), which in turn can cause geomagnetic storms, carry radiation, and significantly contribute to space weather.

“CMEs, geomagnetic storms, and solar radiation can affect our satellites if we are unprepared. These events can also knock out our GPS or power grids on rare occasions,” he said. “What we really want is to figure out what is causing solar flares. We have some suspicions, but maybe machine learning techniques can find something we didn’t.”

There are already some prediction models in place now, but Pereira’s research is trying to push past the current “bottleneck” in the research. His work is not only trying to confirm previous techniques but also testing out a new one.

Pereira is the recipient of a Graduate Inclusion and Access scholarship, which works to enhance the diversity of the graduate student community at George Mason by providing scholarships for first-generation doctoral students who have been historically underrepresented within their doctoral field of study. The scholarship provides funding and an opportunities to become involved in the graduate community through special events each semester.

“The grade requirements [for the scholarship] are a little higher than those of my fellow grad students, but I think the hard work is rewarding and will help me stay on track to finish within the five years.”

João Felipe Sousa Pereira outside the Mason Observatory. Photo by Evan Cantwell/Office of University Branding

Pereira came to George Mason after completing his undergraduate degree in physics and astronomy at University of Maryland (UMD), College Park. He initially became interested in space weather his freshman year at UMD. “I had an introductory electricity and magnetism course. It seemed interesting to me to learn about solar wind, the types of phenomena that occur in space, and how the physics of it all actually impacts us on Earth.”

In his junior and senior years, Pereira worked on space weather research with his then-advisor Surjalal Sharma and became interested in continuing that research in his graduate studies. He then visited George Mason, where he met with his current advisor Jie Zhang of the Department of Physics and Astronomy. “[Zhang] helped me set up the possibilities for what can be done in this field, and he had the idea for the project that I'm working on now,” Pereira said.

On the same visit, Pereira had the opportunity to meet with graduate students who let him know that the PhD program wasn’t easy, but he would have the support he needed. He was able to see the graduate student culture with his own eyes, which helped him feel like he could belong at George Mason.

Pereira offers advice to other students considering PhD programs. “You should talk to as many people as possible—that can help guide your decision process. Some people have good experiences, some people have bad experiences, and they’re all valid. Everyone’s on their own path.”

“Pereira’s passion to research and commitment to his doctoral program are inspiring,” said Laurence Bray, senior associate provost for graduate education. “He represents the Mason Nation at heart by designing his own path to success with strength and resilience.”

Pereira’s enthusiasm for his research continues. “The reason I do physics is because I like figuring out how things work. And it's not necessarily easy, but in the end, when you have that ‘aha moment,’ it really is rewarding,” he said.

Learn more about Research at George Mason

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Using robotics to introduce AI and machine learning concepts into the elementary classroom

Colleen Rich — Thu, 23 Jan 2025 17:52:02 +0000

Using robotics to introduce AI and machine learning concepts into the elementary classroom Colleen Rich Thu, 01/23/2025 - 12:52

��AV researcher Erdogan Kaya is part of an interdisciplinary research team that is planning to introduce elementary students to the foundational concepts of artificial intelligence (AI) and machine learning using educational robotics.

George Mason professor Erdogan Kaya with some of the educational robots his team will be using with elementary school students. Photo provided

Kaya, an assistant professor in George Mason’s School of Education, and his collaborators—Hasan Deniz of University of Nevada, Las Vegas; Ezgi Yesilyurt of Weber State University; and Refika Turgut of University of South Carolina—have been awarded a $1 million grant from the National Science Foundation (NSF) “Computer Science for All” program for their project, “Cultivating Artificial Intelligence Literacy through Linguistically Inclusive Integrated Elementary Curriculum via Educational Robotics.”

“Over the years, I have seen firsthand how robotics can captivate and inspire students, making complex STEM concepts accessible and more engaging,” said Kaya. “Students gain insight into how AI systems work and develop a deeper understanding of the power of AI, which promotes foundational AI literacy.”

Approximately 600 elementary students in grades 4 and 5 from schools serving underrepresented populations in Clark County, Nevada, will participate in this study. The goal of this project is to provide the students with hands-on learning opportunities that will allow them to develop an understanding of AI and its application in science and technology.

The study will also offer professional development to 25 in-service educators to equip them with the foundational knowledge of AI and machine learning needed to teach an AI-integrated STEM curriculum.

Kaya emphasized that it is essential for young learners to acquire a level of AI literacy that includes an understanding of how AI algorithms work, how AI applications are developed, and how they can be used responsibly and creatively. He hopes that by being exposed to AI and machine learning at an early age, students will develop skills that may lead them to pursue careers in STEM.

“This project is about opening doors to AI literacy for young students, especially those from multilingual backgrounds who may not see themselves represented in tech fields,” said Kaya, who grew up in Turkiye and began learning English in middle school.

After working with multilingual learners in Title I schools in Arizona, Kaya discovered that his perspective as someone who has navigated education in multiple languages gave him insight into serving this population of students effectively.

“By integrating AI and robotics early on, we are providing a foundation in STEM that not only builds skills but instills a belief in students that they can be part of AI-intensive fields,” he said.

Educational tools, including Birdbrain Technologies’ Hummingbird Robotics®, Teachable Machine, and Snap!, a visual block-based programming environment, will be used in this study. Students will be tasked with designing automated solutions to real-world challenges that exist in their home communities, such as how to make smart homes more energy-efficient or how to develop farming robots capable of harvesting strawberries. Kaya said that projects like these will allow the students to apply AI concepts in ways that they will find more culturally relevant and meaningful.

The study will also promote the responsible and ethical use of AI by asking students to engage in critical thinking regarding the broader societal impact of AI and how bias can affect AI algorithm outputs.

Teachers using the AI-integrated curricular resources developed under this project will be able to incorporate them into their existing curricula.

“Our curriculum is designed to be flexible and integrative. By combining AI, engineering, language arts, and science into integrated lessons, teachers can address multiple subjects within a single lesson, making the most of limited classroom time,” said Kaya.

The importance of teaching the principles of AI and machine learning at an early age continues to gain traction in K-12 computer science education. Kaya notes that organizations such as the International Society for Technology in Education and Computer Science Teachers Association (CSTA) are responding with programs such as Teach AI. In addition, CSTA is updating its standards, scheduled for release in 2026, to incorporate machine learning and AI.

At the state level, Virginia’s recent updates to the Computer Science Standards of Learning (SOLs) include requirements for machine learning, further underscoring the need to prepare students in this field.

It is these changes in the field of computer science education that influenced Kaya’s decision to pursue a second master’s degree—this one in machine learning—at George Mason. “Even though I have a CS background, I recognized that machine learning and AI are becoming crucial parts of CS education,” he said. “To better serve the needs of future teachers and K-12 students, I decided to further my own education in this rapidly evolving field.”

With this project, Kaya said the goal is to equip teachers to bring AI and robotics into their classrooms with confidence, even if they do not have a technical background. “By providing practical training and readily available materials, we hope to create a ripple effect where teachers inspire their students and make AI education a reality in their classrooms,” Kaya said.

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Mason Korea students conduct environmental research on Incheon stream

Colleen Rich — Tue, 21 Jan 2025 19:07:51 +0000

Mason Korea students conduct environmental research on Incheon stream Colleen Rich Tue, 01/21/2025 - 14:07

A team of student fellows at Mason Korea's Center for Security and Policy Studies received a grant from ��AV to support their research on improving water quality in Incheon's Seunggi-cheon stream.

Mason Impact project team at work. Photo provided

Under the guidance of Mason Korea faculty members Soyoung Kwon and Dakota McCarty, the team conducted fieldwork to collect and analyze water samples as part of the Mason Impact program. The project, "Enhancing Water Quality Management of Seunggi-cheon in Incheon, South Korea: A Region-focused, Low-cost, Nature-based Approach," produced a comprehensive dataset that helped pinpoint areas of elevated pollution in the stream using advanced statistical techniques. The findings informed the development of actionable strategies to enhance local stream health.

"We started this research project with one goal: to make an impact," said global affairs major Hyunwoo Jo, one of the student fellows. "I’m glad that we’ve accomplished just that through our case study. I was able to conduct valuable—and unique—quantitative research under faculty guidance."

Mason Impact project team with their poster at Fall Student Project Showcase. Photo provided

"I believe the world can change by focusing on small things nearby. Seunggi-cheon may be unknown to those outside Incheon, it is valuable to local residents as a place for walking, exercising, and supporting various wildlife," said global affairs major Minji Kim. "Through collecting and analyzing water samples, we gained insights into environmental security that could inform policies not just for this river, but for others in Korea and beyond."

"This project was a perfect case of the power of pairing interdisciplinary research with experiential learning," said McCarty, who is an assistant professor in Mason Korea’s Department of Environmental Science and Policy. "Through their dedication, and getting their hands dirty in real-world field research, the team not only gained valuable research experience but also contributed actionable insights to improve water quality in the Seunggi-cheon stream."

"Thanks to Dr. McCarty's enthusiasm and guidance, our student fellows had a valuable time learning through experiments," said Kwon, an associate professor of global affairs and director of security policy studies-Korea. "They also learned how to translate the research outcomes into policies for community development."

The mini grant, awarded by George Mason’s Office of the Provost, supports experiential learning projects that address real-world challenges. The students presented their findings at Mason Korea's Fall 2024 Student Project Showcase.

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George Mason scientist Anamaria Berea leads team to design lunar cultural archive for the ‘Pioneers of Tomorrow’

Colleen Rich — Thu, 16 Jan 2025 21:02:59 +0000

George Mason scientist Anamaria Berea leads team to design lunar cultural archive for the ‘Pioneers of Tomorrow’ Colleen Rich Thu, 01/16/2025 - 16:02

The ASPIRE ONE Lunar Record launched early on January 15 as part of the Ghost Riders in the Sky Lunar mission from the Kennedy Space Center in Florida, with a goal of establishing a new theoretical framework for planetary-scale archival communication.

Note from team on ASPIRE ONE. Photo provided

Anamaria Berea, an associate professor of computational sciences at ��AV, led an interdisciplinary team that designed a part of the LifeShip payload—an archive to preserve our Earth’s cultural and scientific heritage. It will be placed on the Moon through Firefly Aerospace’s Blue Ghost Lander.

Firefly missions are part of NASA’s Commercial Lunar Payload Services initiative in the Artemis program.

The digital portion of the LifeShip payload, similar to the Voyager Golden Records, contains diverse content including videos, global aspirations, scientific materials, historical records, and cultural artifacts intended for future humans to access. Highlights include Daily Life video capturing global snapshots of contemporary life, an Aspirations video featuring individuals sharing hopes for the future in their native languages, and collections of images from UNESCO and World Heritage archives. A Getty images documentation of the recent COVID-19 pandemic is also included.

Firefly Blue Ghost will deliver the lunar record to the Moon's surface. Photo courtesy of NASA

“We basically created an archive that is housed on a 1GB microchip encoded with diverse content,” said Berea, who also has a PhD is computational social sciences from George Mason. “It is also engraved with NanoFiche, including Berea’s name and affiliation with ��AV.

If it lands successfully, the payload will be placed on the Moon after 45 days [early March] and live there for posterity.

“This portion of the payload includes the Apollo 11 launch code, various works of art and music, information about the Moon, Earth Constitutions, and more,” Berea shared. “Not only my face, voice, name, and work will be on the Moon for future generations, but ��AV’s legacy too.”

Learn more about Anamaria Berea’s work on George Mason’s Access to Excellence podcast.

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Using AI to uncover human smuggling networks

Teresa Donnellan — Wed, 15 Jan 2025 22:39:59 +0000

Using AI to uncover human smuggling networks Teresa Donnellan Wed, 01/15/2025 - 17:39

In This Story

Carlotta Domeniconi

Sean Luke

Guadalupe Correa-Cabrera

As vulnerable members of society, migrants are subject to exploitation. Professor Carlotta Domeniconi in the Department of Computer Science at ��AV is using artificial intelligence (AI) to combat that abuse. She is the principal investigator (PI) on a groundbreaking project aimed at understanding and modeling human smuggling networks.

Carlotta Domeniconi

In collaboration with the Department of Homeland Security’s Criminal Investigations and Network Analysis (CINA) Center for Excellence, Domeniconi and co-PIs Guadalupe Correa-Cabrera and Sean Luke are developing advanced machine learning techniques to analyze publicly available data and uncover the intricate workings of human smuggling networks between Mexico and the United States. While Domeniconi and Luke, both computer science faculty, bring expertise in machine learning, Correa-Cabrera is a professor in George Mason's Schar School of Policy and Government specializing in border studies, U.S.-Mexico relations, international security, migration studies, and illicit networks.

A significant challenge in this project is the sparsity and complexity of the data, said Domeniconi. Criminal networks are large, dynamic, and constantly evolving.

"The very nature of criminal networks—their secret nature—makes it practically impossible to gather useful data," she explained. This challenge led to the team’s innovative approach of using publicly available text data—past cases of prosecuted smugglers at both the state and federal levels in the United States as well as social media posts and news articles by and about smugglers. They are collecting data from the 1980s to 2024 to analyze the temporal dynamics of these networks.

“There are videos of smugglers actually showcasing people traveling across very difficult areas from Central America,” Domeniconi noted as an example. “You can extract a lot of information about the routes they take, where they cross the borders, and the means they use."

The team is using natural language processing (NLP) and deep learning models that are pre-trained on vast amounts of text data, enabling them to understand and extract meaningful information from the data they are collecting. Two doctoral students will support the co-PIs, one from computer science and the other from the Schar School. The team is working on automating the process of building and analyzing these criminal networks using large language models and graph mining techniques. By visualizing these networks as knowledge graphs, the team aims to mine behavioral patterns and understand how these networks adapt to changes in policy enforcement. Ultimately, this project could provide a methodology applicable to various criminal networks beyond human smuggling.

Guadalupe Correa-Cabrera

“The current project bridges the gap between machine learning and social science,” explained Correa-Cabrera. “We can replicate this same model and methodology to analyze legal cases of drug smuggling, money laundering, and arms trafficking, thereby modeling and explaining the evolution of these activities over the past few decades.”

Domeniconi's pioneering work in modeling human smuggling networks is a testament to the power of AI in addressing complex social issues. By merging domain expertise with state-of-the-art machine learning techniques, this project not only promises to unravel the clandestine operations of human smuggling but also to create a robust methodology applicable to various criminal networks. The insights gained from this research could significantly enhance national security measures, offering a strategic advantage in the fight against human smuggling and those who perpetrate this crime.

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George Mason and Virginia Tech collaborate to build science policy connections

Katarina Benson — Mon, 13 Jan 2025 18:50:00 +0000

George Mason and Virginia Tech collaborate to build science policy connections Katarina Benson Mon, 01/13/2025 - 13:50

Today, Virginia is one step closer to bridging the gap between science and policy—a critical relationship necessary to navigate a range of socio-technical issues including climate change, biodiversity loss, pandemics, and poverty. This connection was the result of a yearlong research project to identify U.S. and Virginia-based science policy programs that engage STEM-H scientists and engineers in science policy, with the goal of helping both elected officials and others access technical information to assist in decision making.

Adriana Bankston and K.L. Akerlof. Photo provided

This work was completed thanks to a coalition of faculty and students supported though a 4-VA@Mason grant. The team was led by K.L. Akerlof in ��AV’s Department of Environmental Science and Policy and Todd Schenk, chair and associate professor in the Urban Affairs and Planning Program of the School of Public and International Affairs at Virginia Tech and director of the Science, Technology and Engineering in Policy Program.

“This funding supported our cross-institutional collaboration and ability to conduct baseline research and networking that have been fundamental to understanding how the landscape of science policy training programs is evolving across the United States,” Akerlof said.

The team created a database of U.S. science policy programs and conducted a case study of those in Virginia through surveys and interviews with their leaders, with the goal of advancing best practices for professional mentorship of early career researchers and building capacity for training researchers to engage in public policy. Akerlof and Schenk were assisted in the study by science policy expert Adriana Bankston; George Mason students Kelsey Mitchell, Kate Saylor and Aniyah Syl; and Kenneth Dewberry at Virginia Tech.

Following the yearlong collaboration, the results of their research have been developed and are featured on a new website—along with program blogs and a listserv—created to support this emerging network of science policy programs.

The results showed that the majority—57%—of U.S. science policy programs are state based. These programs include student organizations, government placements and fellowships, academic certificates, degrees, and other training. However, it was recognized that there is a limited ability to implement evidence-based approaches within these programs.

The team compared program outcomes from Virginia’s science policy programs with those described in academic literature. Academic and professional scholarship in science communication and public affairs suggests that curricula for engaging scientists and engineers should broadly cover communication and policy processes, which could be improved.

In addition, they found that training programs would benefit from evaluation models and measures, although the lack of consistent theoretical foundations across this highly multidisciplinary scholarship reduces their utility. It was concluded that a common framework, which includes shared terms and relationships, is needed to promote the growth of the field.

With the results of their analysis in hand, the team, including George Mason undergraduate student Aniyah Syl and PhD student Kelsey Mitchell, helped lead a state webinar on science policy programs featuring Virginia program leaders. Syl co-presented on the project at a Virginia Sea Grant Symposium which was also the topic of an American Geophysical Union e-lightning talk.

Master’s student Kate Saylor successfully defended her thesis on the Commonwealth of Virginia Engineering and Science (COVES) Policy Fellowship and subsequently presented her results to James Aylor, president of the Virginia Academy of Science, Engineering, and Medicine.

The first of two research articles based on the project has just been accepted by the journal Evidence & Policy. A second article has also been submitted for publication. Syl and Mitchell participated as co-authors on the publications.

The team is also in conversation with the leadership of the Virginia Academy of Science, Engineering, and Medicine about the development of a new weeklong science policy program for undergraduate students from across the commonwealth’s public universities.

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Advancing sensor tech for foggy situations

Nathan Kahl — Mon, 13 Jan 2025 13:15:50 +0000

Advancing sensor tech for foggy situations Nathan Kahl Mon, 01/13/2025 - 08:15

Devices that rely on sensors to accurately navigate and perceive the world around them are more and more commonplace, from drones to autonomous vehicles to ground robots on rescue missions. Parth Pathak, an associate professor in the Department of Computer Science at ��AV, is working to ensure the sensors have 20/20 vision.

From left, Rezoan Ahmed Nazib, Parth Pathak, and Ahmad Kamari with a rescue robot that can "see" through smoke and fog. Photo provided

Pathak received $660K in funding from the Army Research Office (ARO) for this work, some of which is done in collaboration with colleagues at the University of California, Davis, where he did his post-doc.

“Conventional sensors rely on cameras or LiDAR (light detection and ranging) to pursue objects around them, but they don't work very well when there's smoke, fog, or generally a visually degraded environment,” said Pathak. “But the mmwave wireless radar sensors that we are working on don't get affected by that. If there is dirt on the sensor, well, that's okay. They can see through things and see around things."

Imagine a rescue robot going into a building filled with smoke, trying to navigate with little to no visibility, Pathak said. "These wireless sensors can enable them to perceive the environment and even self-localize without cameras, LiDARs, or other positioning systems.”

Another positive aspect of the devices is that while they can sense…they don’t sense too much, which is important for privacy concerns. The disadvantage, of course, is that when a sensor depicts an object such as a car, the resolution is not particularly good, and the images are “noisy.” Pathak is not just improving navigation and perception, but using multiple robots, for example, cooperatively. In a rescue mission, a swarm of robots can share their data, allowing them to collectively “see” a better picture.

Photo provided

“They can self-localize based on what they see, like how our brains work. But the robots only have wireless sensors to rely on, so part of the work is developing very good signatures of what they see from these very low resolution and noisy images,” said Pathak. “We can build 3D models of a room by scanning it through the wireless sensors and using machine learning to capture and recreate every minute detail. This is something that these sensors were never designed for. We are developing custom-tailored deep learning models of wireless sensing, essentially pushing the limits of what they can perceive using wireless signals.”

In addition to the research, ARO’s funding also supports testbed-to-prototype development and solution evaluation.

Pathak and colleagues published this research at the Association for Computing Machinery’s ACM Mobicom conference and have submitted it to other conferences for potential publication. Two PhD students from his team, Ahmed Kamari and Rezoan Ahmed Nazib, are working actively on the project, along with three high school students who participated in prototyping over the summer as part of George Mason's Aspiring Scientists Summer Internship Program.

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