National Science Foundation

NSF grant supports nanofabrication workforce training

Nathan Kahl — Sat, 13 Sep 2025 22:43:45 +0000

NSF grant supports nanofabrication workforce training Nathan Kahl Sat, 09/13/2025 - 18:43

�鶹��Ƶ faculty members received nearly $1 million in a grant from the National Science Foundation (NSF) to establish a program providing hands-on nanofabrication training and education to people seeking a career change.

The funding comes under NSF’s ExLENT Pivots track and will serve the national interest by expanding experiential learning pathways in emerging hardware technologies driven by nanofabrication. It focuses on increasing workforce opportunities in Northern Virginia, a region positioned for growth in emerging technology sectors, such as artificial intelligence hardware, quantum information science, data center engineering, and sustainable manufacturing.

Ahn's research focus is nanofabrication. Photo by Office of University Branding

“The most important term is ‘experiential,' and it’s rare for NSF to provide this kind of funding," said Ethan Ahn, an associate professor in the Department of Electrical and Computer Engineering and a founding director of �鶹��Ƶ Nanoelectronics Laboratory, who is the lead principal investigator (PI) on the project. "The idea here is to produce this workforce for very high tech-focused areas by applying the learning-by-doing model.”

George �鶹��Ƶ is already known as one of the commonwealth's largest producers of tech talent.

The program provides an opportunity for working professionals who are looking to change careers; even those with no STEM background are encouraged to apply, as suggested by the “pivot” track from NSF.

“We’ll take people regardless of their background, education, or readiness," said Ahn. "We’ll provide everything they need to be job-ready by training participants with both lab and soft skills, providing connections with industry, and, if hired, paying them during their summer employment."

Co-PI Jessica Rosenberg, professor of physics and director of education at George �鶹��Ƶ’s Quantum Science and Engineering Center, said, “Nanofabrication is important for a range of high-tech industries, including semiconductors, biomedical, and energy. We’re creating a program to provide the support, education, and training needed for individuals to get a job in this growing sector. It will help them meet their goals while also supporting a regional talent pipeline.”

The program will run for three years, with approximately 20 participants every year. A key component of the initial phase of the program is access to a mobile app used for virtual training. The team is developing the app because they recognize that participants may have existing responsibilities that make coming to campus a challenge. After participants complete this first phase on their own schedule, they will then go to campus to participate in a research lab for the hands-on portions of the program.

Jessica Rosenberg is director of education at George �鶹��Ƶ's Quantum Science and Engineering Center. Photo by Office of University Branding

Ahn said a particularly interesting element of the program is a guaranteed interview in the industry. They are already working with BAE Systems, General Dynamics, and Northrop Grumman and expect this number of companies participating to grow through a collaboration with the Virginia Economic Development Partnership. "The hope is that the participants will be able to turn the opportunity into a full-time position,” he said.

George �鶹��Ƶ will give program participants microcredentials, competency-based qualifications indicating a mastery of a subject, as they complete each phase of the program. This opportunity’s timing is ideal for Virginians looking to make a career change and supports the university’s efforts in building Virginia’s high-tech workforce.

Ahn was inspired to apply for the funding in part by the fact that the new Innovation District, a 3,800-acre area of Prince William County anchored by George �鶹��Ƶ’s Science and Technology Campus, co-locates the university with industry and government to create a dynamic collaboration model.

“Relationships between university and industry are common, but this also includes government,” said Ahn. “We already have this established network via the Innovation District and in my proposal I said we are going to focus on nanofabrication, which is my area of expertise. I think those things made it appealing to NSF.”

Jill Nelson, professor and associate dean for undergraduate programs, and Nathalia Peixoto, associate professor, both in the department of Electrical and Computer Engineering, are also PI's on the grant.

The program will welcome its first cohort in spring 2026.

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Engineering better vision: George �鶹��Ƶ professors lead $1.17M NIH project

Martha Bushong — Wed, 30 Jul 2025 19:12:10 +0000

Engineering better vision: George �鶹��Ƶ professors lead $1.17M NIH project Martha Bushong Wed, 07/30/2025 - 15:12

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Ningshi Yao

Quentin Sanders

Qi Wei

Understanding and treating complex eye movement disorders like strabismus has long been a challenge for clinicians. Now, researchers at �鶹��Ƶ are pioneering a new approach using robotics and artificial intelligence to engineer a better future for vision care.

Ningshi Yao, an assistant professor in the Department of Electrical and Computer Engineering, has been awarded a prestigious $1.17 million R01 grant to lead a groundbreaking four-year project. The award comes from the joint National Science Foundation (NSF) and National Institutes of Health (NIH) "Smart Health and Biomedical Research in the Era of Artificial Intelligence and Advanced Data Science (SCH)" program.

The funded project, "Study Coordinated Human Eye Movement and Strabismus Using a Novel Artificial Muscle-Driven Robotic Eyes," will be conducted in collaboration with co-investigators Qi Wei and Quentin Sanders from George �鶹��Ƶ’s Department of Bioengineering and consultant Joseph Demer in the Stein Eye Institute at the University of California, Los Angeles.

From leftt: Qi Wei (Bioengineering Department), Ningshi Yao (Electrical and Computer Engineering Department), and Quentin Sanders (Bioengineering and Mechanical Engineering Departments). Photo provided

At the core of the research is the creation of robotic eyes powered by artificial muscles that replicate the precise, coordinated movements of human eyes. “Strabismus affects more than 18 million Americans, yet current treatments often fall short, with success rates ranging from 30 to 80%,” said Yao. “Our goal is to use robotic systems and artificial intelligence to better understand how the eyes work—and ultimately improve how we diagnose and treat these disorders.”

The research team will build robotic eyes that closely mimic human biomechanics and use them as tools to study the underlying causes of strabismus. These systems will allow for a level of control and repeatability not possible in human subjects, offering a unique window into how eye muscles and connective tissues—especially the so-called “pulleys”—work together to guide vision.

To make the robotic system truly intelligent, the project will also apply reinforcement learning, a type of artificial intelligence, to discover how humans naturally control eye movements. By training the robots with real patient data and expert-informed objectives, the team hopes to reverse-engineer the strategies humans use—leading to better understanding and new treatment pathways.

In the final phase of the project, the team will integrate patient-specific data into the robotic system to simulate different surgical outcomes. This will allow ophthalmologists to test and refine treatment strategies before operating, increasing precision and improving long-term results.

The project’s impact extends beyond eye health. The robotic muscle actuators and control models developed here could advance robotics, AI, biomechanics, and even the design of soft, adaptive machines.

In addition to scientific discoveries, the research team will build educational tools and training platforms using the robotic eyes, helping to prepare the next generation of vision specialists.

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I-Corps in 3D: Streaming toward better telehealth

Nathan Kahl — Thu, 17 Jul 2025 14:19:57 +0000

I-Corps in 3D: Streaming toward better telehealth Nathan Kahl Thu, 07/17/2025 - 10:19

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A team in �鶹��Ƶ’s Computer Science Department is taking part in the National Science Foundation’s (NSF) I-Corps program to study the effectiveness of 3D streaming in telehealth environments.

Bo Han, an associate professor of computer science and expert in computer networks and security and privacy, received $50,000 for his project, Translation Potential of Next Generation Telepresence Enriched by Immersive Technologies. Nan Wu, the entrepreneurial lead on the team, said, “The idea is to build a system for immersive telepresence over the internet. It’s essentially a 3D video stream but the technical improvement is how it saves bandwidth by using user-motion prediction and content sampling, improving the quality of the experience.”

3D telehealth services may help remote patients in urgent need of care. iStock photo.

Wu explained that the technical adjustment is made based on the receiver’s movements. “Since I’m looking at the front side of you, the streaming only needs to send me the front side, not the back. I don’t need to see all around you, even though it’s 3D. Moreover, when you’re farther away, a lower-resolution stream is enough since I won’t notice the difference. And if you’re hidden behind other content, there’s no need in sending what I can’t see.”

I-Corps is, according to the NSF website, “an immersive, entrepreneurial training program that facilitates the transformation of invention to impact. This seven-week experiential training program prepares scientists and engineers to extend their focus beyond the university laboratory—accelerating the economic and societal benefits of NSF-funded and other basic research projects that are ready to move toward commercialization.”

Since the program began in 2012, I-Corps has ushered 2,500 teams, and nearly 1,400 of them launched startups that cumulatively raised $3.16 billion in subsequent funding.

A portion of the I-Corps mentoring is devoted to customer discovery. Teams must interview at least 100 potential customers to determine market interest. According to Wu, the team didn’t find a robust market for using the technology the way they initially envisioned because staff shortages is the biggest pain point in the field, not technical shortcomings. “We thought nurses could monitor patients in 3D and save time, but there are many AI tools already doing that, monitoring 40 patients at once,” he said.

Wu said they’ve shifted to using the technology emergency situations, believing the tools will be useful in high-pressure trauma care or emergency cases. “We are thinking of a situation where there is a remote expert connected to a patient in a rural area, for example, where there is no expert on site.” Wu said that more interviews are needed to determine the market demand for such use.

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Trial by virtual fire: Augmented reality project tailors training for firefighters

Sarah Holland — Thu, 22 May 2025 17:18:32 +0000

Trial by virtual fire: Augmented reality project tailors training for firefighters Sarah Holland Thu, 05/22/2025 - 13:18

For firefighters, even training is a risk. According to the United States Fire Administration, 16.6% of all firefighter fatalities in 2024 took place during training exercises. �鶹��Ƶ researcher Craig Yu is hoping to change that statistic.

Yu, associate professor of computer science, has been developing augmented and virtual reality training for most of his career, and he has a particular interest in exploring how artificial intelligence (AI) and emerging technologies could help research on human development and sports science. Through National Science Foundation’s EArly-concept Grants for Exploratory Research (EAGER) program, Yu and Joel Martin, associate professor of kinesiology, are developing just that: an augmented reality program that could help train firefighters while minimizing risk.

“Firefighters have high rates of injuries and many injuries happen during training. There is a need for training technology that can replicate aspects of emergencies while minimizing the injury risk and physical burn,” said Martin. Martin has spent the past few years working with Fairfax County Fire and Rescue to determine how they can reduce physical strain to firefighters during training exercises. “I think that technology such as immersive reality training can help to meet training needs while minimizing the physical risks of performing certain drills."

A prototype of the virtual training space from their proposal. Image provided.

Augmented—or mixed—reality uses devices such as phones or a headset to overlay 3D computer-generated content onto the real world. An increasingly accessible tool, you can find augmented reality in applications like Ikea furniture previews in your house, dinosaur encounters in the Smithsonian, and catching Pokémon in your neighborhood.

As described in their project proposal, “Adapting Mixed Reality Training Programs to Real-World Scenes to Enhance Human-AI Teaming in Emergency Responses,” the new training would utilize augmented reality to create realistic training scenarios for firefighters.

Based on a 3D digital twin of the room, the program will use AI to analyze what's in the room and create a realistic outbreak of fire: where it is most likely to start and spread, and where civilians are most likely to be.

“The program understands the environment, and it will be refined with additional input from professional firefighters,” said Yu.

Yu also notes that the scenario can be adapted for different experience levels. Simpler scenarios can be developed for new firefighters, which can then be adjusted for increasing sophistication and complexity as the trainees learn and improve. It also allows them to practice scenarios that would be difficult or impossible to replicate in a live burn, such as how to best evacuate and rescue civilians.

Most importantly, it prevents firefighters from being exposed to hazardous conditions while in training.

“I don’t ever see us replacing real fire training,” said Yu, “but this is a means to augment the training to improve the health and safety of the firefighters, as well as make training easier to deploy in a variety of buildings and circumstances. AI allows us to rapidly analyze human performance and then adaptively synthesize training programs to address weakness we observe.”

Martin and Yu are in the early phases of development but hope to deploy their initial training designs with Fairfax County Fire and Rescue soon. They both have hopes for further incorporation of AI and augmented reality technology in firefighting tools, such as headsets that can scan the environment and offer real-time feedback about potential dangers, exit strategies, and health metrics as firefighters enter hazardous zones.

“More and more virtual and immersive reality training is being used [in kinesiology],” said Martin. “I think this project demonstrates the importance of collaboration and interdisciplinary teams to solve challenges in the field.”

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George �鶹��Ƶ’s ROARS lab retains its ranking as a leader in AI safety at the 2024 International Neural Network Verification Competition

Jennifer Pocock — Mon, 19 May 2025 20:47:30 +0000

George �鶹��Ƶ’s ROARS lab retains its ranking as a leader in AI safety at the 2024 International Neural Network Verification Competition Jennifer Pocock Mon, 05/19/2025 - 16:47

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ThanhVu Nguyen

The team’s NeuralSAT advanced the frontiers of trustworthy artificial intelligence, earning second place in a highly competitive field of international teams advancing the formal verification of AI systems.

Associate Professor ThanhVu Nguyen

NeuralSAT is an open-source verification tool developed by experts in Formal Methods/AI Hai Duong and ThanhVu Nguyen, both of �鶹��Ƶ. It analyzes whether deep neural networks behave as intended, even under adversarial or uncertain conditions. The International Neural Network Verification Competition (VNN-COMP) gathers international research teams working on formal methods for AI safety—methods that are increasingly important as neural networks are deployed in autonomous systems, healthcare, finance, and other mission-critical systems.

"Our goal with NeuralSAT is to bring precision and robustness to AI systems,” said Nguyen, an associate professor in computer science, “especially as they are increasingly used in safety-critical settings."

Hai Duong is a third-year PhD candidate

Each year, the participating VNN-COMP tools are evaluated across a wide set of benchmarks that test scalability, correctness, and performance. The 2024 competition’s results were recently released.

"This year’s benchmarks pushed the boundaries of what verification tools could handle—both in terms of scale and complexity," said Duong, a third-year computer science PhD candidate. "We’re proud that NeuralSAT remained among the top performers, showing strong results across both safety and robustness categories."

NeuralSAT was developed in close collaboration with researchers across multiple institutions, including the University of Virginia’s Matt Dwyer. It builds on recent advances in symbolic reasoning, SAT solving, and abstraction. In its inaugural appearance at VNN-COMP in 2023, NeuralSAT placed fourth overall and received the New Participant Award. In addition to competitions, the tool has been featured at top-tier conferences such as the Symposium on the Foundations of Software Engineering and Computer Aided Verification.

Nguyen, who serves as an organizer and program chair of VNN-COMP 2025, emphasized the significance of the competition in shaping the research landscape.

"The field of neural network verification is rapidly maturing, and VNN-COMP has become the standard for evaluating progress," he said. "Many research papers now compare their tools against VNN-COMP results or use its benchmarks for evaluation. It's exciting to be involved in shaping the competition while also contributing a tool that pushes the research frontier."

David Rosenblum, chair of the Department of Computer Science, was thrilled with ROARS Lab’s achievement. "ThanhVu Nguyen is an established research leader on problems at the intersection of formal methods and deep learning. This team’s outstanding achievement has demonstrated the great potential impact of verification technologies for AI safety," he said.

The long-term goal of NeuralSAT, supported in part by Nguyen’s NSF CAREER Award and Amazon Research Award, is to remain at the forefront of AI verification research while evolving into a practical, scalable, and potentially commercial-grade solution for industry use.

George �鶹��Ƶ is advancing a bold vision for the future of safe and robust AI and is further expanding its leadership with the launch of Virginia's first master’s program in artificial intelligence in fall 2025. This program reflects the university’s deep commitment to cutting-edge education and the development of trustworthy, high-impact AI technologies.

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George �鶹��Ƶ scientist leads $1.8M NSF grant to address mobility challenges from urban flooding

Katarina Benson — Fri, 21 Feb 2025 19:36:52 +0000

George �鶹��Ƶ scientist leads $1.8M NSF grant to address mobility challenges from urban flooding Katarina Benson Fri, 02/21/2025 - 14:36

�鶹��Ƶ researcher Alireza Ermagun has been awarded a $1.8 million grant from the National Science Foundation (NSF) to address mobility challenges caused by nuisance flooding. The project, a collaboration with Villanova University and the University of South Carolina, centers on understanding how frequent, low-level flooding disrupts daily transportation systems and devising equitable solutions.

Alireza Ermagun. Photo provided

Nuisance flooding frequently inundates roads and overwhelms stormwater systems, creating widespread transportation challenges. Ermagun emphasizes that such flooding disproportionately affects vulnerable populations who depend on public transit, walking, or biking. “These frequent but seemingly minor floods accumulate to create major disruptions, particularly for those already facing socioeconomic and mobility barriers,” said Ermagun, the director of Mobility Observatory and Data Analytics Lab and an assistant professor in the Department of Geography and Geoinformation Science. “This project aims to ensure that every resident has access to reliable transportation, regardless of the challenges posed by flooding.”

The research focuses on three neighborhoods in Philadelphia—Kensington, Manayunk, and Germantown—and involves close partnerships with the Philadelphia Water Department (PWD), the Delaware Valley River Regional Planning Commission (DVRPC), and the Energy Coordinating Agency (ECA). The team will examine the spatial and temporal extent of flooding in these areas and develop strategic green infrastructure solutions to address mobility barriers.

“Nuisance flooding is common but difficult to assess,” said Virginia Smith, a water resource scientist at Villanova University. “These events, however, disrupt people’s lives and their ability to move around their communities. By identifying where flooding occurs and its impact, we can develop meaningful solutions to improve daily life and beyond.”

The project places a strong emphasis on engaging communities directly impacted by nuisance flooding. Peleg Kremer, a social-ecological systems scientist at Villanova University, explained, “this project brings community voices into planning, translating their lived experiences into equitable, actionable solutions.”

“Many individuals rely on stable, predictable transportation patterns in their daily lives, and disruptions can be especially harmful for the most residents. Understanding the roots of these

impacts is key to creating effective solutions,” said Brian Levy, a social scientist at the University of South Carolina.

The project also aims to innovate in green infrastructure and mobility planning, ensuring that proposed solutions are not just functional but equitable. “By reducing mobility barriers through strategic infrastructure planning, we can promote resilience in urban transportation,” said Chenfeng Xiong, a transportation scientist at Villanova University.

Reflecting on the broader vision of the project, Ermagun emphasized the importance of combining data-driven approaches with community insight. “Some solutions, like flexible pick-up and drop-off stations or subsidies for ride sharing, show promise,” he said. “But to truly address the scale of the problem, we need to explore more transformative changes, potentially redesigning urban infrastructure, from roads to sewer systems. Our research aims to provide the data and strategies necessary to identify the most effective interventions while centering the voices of those most impacted.”

With a timeline extending through August 2028, this initiative offers unique opportunities for graduate students, researchers, and community members to collaborate on cutting-edge research while contributing to lasting, positive change in Philadelphia’s neighborhoods.

“Our ultimate goal is to not only mitigate the impacts of nuisance flooding,” said Ermagun, “but also to empower communities to adapt and thrive in the face of increasing climate challenges.”

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George �鶹��Ƶ researcher gets CAREER award for quantum leaps in computing, with the help of AI

Nathan Kahl — Thu, 13 Feb 2025 17:55:11 +0000

George �鶹��Ƶ researcher gets CAREER award for quantum leaps in computing, with the help of AI Nathan Kahl Thu, 02/13/2025 - 12:55

Weiwen Jiang, an assistant professor in the �鶹��Ƶ's Department of Electrical and Computer Engineering, is an expert in quantum computing, having recently received nearly $1 million in National Science Foundation (NSF) funding to study “noise” that impacts quantum computing and to work on training the next generation of quantum experts.

Jiang’s research is all about pushing the mysterious world of quantum computing into the mainstream. “We are at the quantum utility era, which means we are going to have computational applications that can be implemented with and utilize the power of quantum computing,” he said. But Jiang knows that researchers need a boost in understanding the full quantum capability.

In January he received an NSF CAREER award for $641,778 for his work on quantum-centric computing cyberinfrastructure (QuCI). A combination of quantum computers, classical computers, and AI accelerators, QuCI is set to revolutionize

Weiwen Jiang. Photo provided

software applications handling everything from geophysics, chemistry, finance, and life sciences, because it can outperform classical computing with its speed, accuracy, and the ability to handle large, data-heavy problems. For example, the success of processing geoscience data on quantum computers can enable real-time decision-making on natural hazards, which leads to cost savings, reduced environmental impacts, and improved safety.

Jiang’s project includes three thrusts. One is using what’s called an AI-powered quantum performance predictor, which leads to an innovative and efficient ability to allocate computing resources in the moment. Jiang said, “When a batch of jobs comes into the system, we need to allocate the jobs into different quantum nodes and we want to distribute the jobs effectively.”

Another focus is bridging a knowledge gap between experts who want to run software applications but are not experts in quantum. “In order to fill this gap we do not want the expert to learn quantum computing from scratch,” he said. “We’ll find opportunities to fine-tune the configuration for quantum control optimization,” helping a non-expert user harness the power of quantum computing by combining classical central-processing unit computing with quantum. Current QuCIs require complicated decision-making to ensure correct computing results are obtained, but this can fall into the hands of users who lack quantum knowledge. Jiang’s project automates QuCI deployment, making decisions and optimizations at different stages without human interference.

A third element is to develop what’s known as fault-tolerant quantum computing, which means allowing quantum computers to operate even when encountering errors. Jiang said, “Before we submit the job, we will add fault-tolerant protocols to ensure the functional correctness and boost performance.”

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.”

Beyond the scientific impact, the project builds an easy-to-understand quantum education program, which includes building a visualization platform to make quantum computations visible. This is significantly important for beginners who easily suffer from the counterintuitive concepts of quantum computing. In addition, Jiang will create workshops, tutorials, and competitions for different research communities, contribute to a George �鶹��Ƶ-led quantum immersion program for K-12 students; and redesign a quantum curriculum at George �鶹��Ƶ with outcomes from this project.

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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

Evgenios Kornaropoulos, an assistant professor in �鶹��Ƶ’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 �鶹��Ƶ 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 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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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

�鶹��Ƶ 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 �鶹��Ƶ 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 �鶹��Ƶ’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 �鶹��Ƶ. “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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Research using AI to track Amazon rainforest species produces landmark results

Colleen Rich — Mon, 25 Nov 2024 13:47:06 +0000

Research using AI to track Amazon rainforest species produces landmark results Colleen Rich Mon, 11/25/2024 - 08:47

Thanks to the tenacity of a �鶹��Ƶ biology professor, animals in the Amazon have a lot less privacy these days, but that’s good for scientists who to want know what’s going on in the Brazilian rainforests.

David Luther recognizes the importance of playing the long game in research, but even he couldn’t have imagined the hurdles and roadblocks ahead of him following the approval of his 2019 4-VA Collaborative Research Grant proposal, “Species richness resilience to habitat fragmentation and restoration in tropical rainforests.”

His plan was to install recording equipment at 50 sites as part of the Biological Dynamics of Forest Fragments Project (BDFFP) in the Amazon rainforest of Brazil. These audio and video devices were meant to document and measure differences in animal community composition and the rate of animal recovery in secondary forest and forest fragments.

Tens of thousands of animal images, such as this ocelot, have been collected for the project from camera traps. Photo provided

The proposed budget was devoted entirely to purchasing the wide array of materials necessary for the effort — cameras, acoustic recorders, and batteries—along with the international travel needed to bring the project to fruition.

In March 2020, all of Luther’s efforts came to a halt due to the pandemic. Additionally, one of the key members of the planning team, Tom Lovejoy, passed away in December 2021. Lovejoy was recognized as one the world’s leading conservation biologists and often referred to as the “godfather of biodiversity.” With Lovejoy’s passing, Luther lost a mentor and a critical member of the team.

However, Luther stayed the course, revamping his team and rewriting the schedule. Finally, in June 2022, he received the green light to move ahead. Between June and October 2022, 136 cameras and 81 acoustic devices were installed across 50 sites at BDFFP.

Today, to Luther’s great delight, the results have proved far more successful than he could have ever anticipated. Tens of thousands of animal images from camera traps and audio recordings have already been collected.

To analyze the data, Luther built a team of 15 George �鶹��Ƶ undergraduate researchers, artificial intelligence (AI) experts, and members of Arbimon, a nonprofit organization that specializes in analyzing acoustic recordings from the tropics to identify animals.

Channel-billed toucan. Photo provided

The student volunteers on this project included Alexis Lembke, Amanda Jones, Adriana Em, Madison Cheung, Morgan Ellingsworth, and Grace Carriero. Aline Medeiros, a PhD student in environmental science and policy, helped manage the undergraduate researchers working on the audio files. Medeiros will also use the captured data as the basis of her PhD research.

Another set of students helped identify animals in the camera images and entered that information into a large database. Hibo Hassan, Jordan Seidmeyer, Katie Russell, Carolian Sanabria, Adrian Em, Alix Upchurch, Piper Robinson, Tristan Silva-Montoya, and Estefany Umana spent hours creating this treasure trove of records. Emilia Roberts, a master’s student in environmental science and policy, managed these undergraduate researchers.

Discussing the project, Luther explained that, for the acoustic recordings, they built templates for 250 bird species and trained AI models to automatically detect and classify songs for each.

“The model performed very well in our evaluations. We have already detected 201 of the 250 species,” said Luther, who teaches in the Biology Department of George �鶹��Ƶ’s College of Science. “Thanks to our model, new recordings can be passed through it to automatically detect species calls, facilitating long-term monitoring and efficient analyses moving forward. We are now working with local experts in Manaus, Brazil, to apply the same platform for frogs at our study sites in the Amazon rainforest.”

The biodiversity data is being used to assess how each species responds to variations in forest structure and recovery from forest fragmentation. Luther brought on Konrad Wessels from George �鶹��Ƶ’s Geography and Geoinformation Science Department to assist with satellite information from the Global Ecosystem Dynamics Investigation instrument, which uses high-resolution lasers to provide detail in three-dimensional forest structure. These results will build predictive models to study how the forest structure can forecast mammal and bird diversity and individual species occurrence in tropical rainforests.

In an important finding, the team has determined that the three-dimensional complexity of the forest structure, as measured by foliage height diversity, is the biggest predictor of mammal and bird diversity at this research site, and potentially others, in the Amazon rainforest.

The project continues to gain traction. The team has created a website featuring the results of the acoustic portion of the research, which has been very well received. Some of the acoustic training models have been used by teams competing for the X-Prize, a competition designed to encourage technological developments supporting “radical breakthroughs for the benefit of humanity.”

Building on the 4-VA funded study, Luther also received a $200,000 National Science Foundation grant to continue both the camera and acoustic research. Luther and Wessels recently submitted a grant to NASA to expand on the research findings and apply them to the entirety of the Amazon basin.

“Through 4-VA@�鶹��Ƶ, this project is up, running, and delivering fantastic information that will help scientists worldwide better design monitoring schemes for biodiversity in remote tropical forests, as well as those interested the relationship between habitat structure and degradation and species resilience to disturbance,” said Luther.

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