computer science

doctoral students

Research

George Mason PhD student recognized for blockchain privacy research

Nathan Kahl — Tue, 02 Jun 2026 10:51:19 +0000

George Mason PhD student recognized for blockchain privacy research Nathan Kahl Tue, 06/02/2026 - 06:51

91�� computer science doctoral student Aayush Yadav co-authored a paper that received a Distinguished Paper Award from the IEEE Symposium on Security and Privacy, one of the industry’s premier conferences in the security field. The conference typically accepts around 13 percent of submissions.

Aayush Yadav. Photo provided

The paper addresses a growing challenge in blockchain technology—how to protect sensitive transaction information before it becomes public, focusing on improving privacy protections within blockchain systems while maintaining the transparency and decentralized structure that define the technology.

His research grew out of an internship last summer with Category Labs, a company developing blockchain tools and infrastructure. The work addresses a vulnerability tied to how blockchain transactions are processed before they are officially added to the chain. Traditionally, blockchain transactions are publicly visible before they are finalized. That visibility allows entities responsible for processing transactions to potentially manipulate their order for financial gain.

“These entities can act maliciously in some way,” Yadav said. “Because this information is public, these actors know the direction of the order of the transactions before the rest of the public. And they can take advantage of that.” Consider that if an actor sees that someone is about to make a major purchase or sale, they can quickly place their own trade first, causing the market price to change. The original user then receives a worse price than expected, while the actor profits from the price movement, effectively creating a hidden cost for the user.

The team’s research focuses on encrypting transactions while they are waiting to be processed, helping prevent that kind of exploitation. The goal is to encrypt or hide transactions as they are sent, revealing them later.

The paper introduces new approaches to what researchers call “mempool privacy,” referring to the protection of transaction data before it becomes part of the public blockchain ledger. The work also explores “threshold encryption,” which requires multiple parties to work together to decrypt transaction data, helping eliminate single points of trust or failure.

Yadav, who is completing his PhD in computer science this year, said his interest in theoretical computer science and algorithms started early in his academic career. “I enjoyed the process of solving problems that were algorithmic in nature,” he said. “Thinking about these abstract things, but then also being able to solve them concretely using an algorithm, is very satisfying.”

He chose George Mason in part because of the university’s large computer science faculty and breadth of expertise. After arriving at George Mason in 2021, Yadav took his first cryptography course with Foteini Baldimtsi, an experience that shaped the direction of his research. “It had the right mix of theory and practice. The problems are very theoretical in some sense, and the way you solve them is theoretical, but at the same time they are grounded in real applications.”

“I am very proud of Aayush,” said Baldimtsi. “Throughout his PhD, he has worked on some of the most important challenges in modern cryptography, including signature protocols and privacy-preserving authentication for digital identities, while also focusing on post-quantum security. The award is a well-deserved recognition of his talent, dedication, and impact on the field.”

Later this year he will start a tenured-track faculty position at his alma mater, Rutgers University–Camden.

In This Story

Foteini Baldimtsi

More from the College of Engineering and Computing

Topics

robotics and autonomous systems

George Mason students fly into first place with no GPS, no grade, and (almost) no problems

tdonnel — Mon, 04 May 2026 18:53:10 +0000

George Mason students fly into first place with no GPS, no grade, and (almost) no problems tdonnel Mon, 05/04/2026 - 14:53

Driven by passion, persistence, and what they call “the love of the game,” a group of 91�� students affiliated with the Mason Autonomy and Robotics Center (MARC) claimed first place at the 2026 Raytheon Autonomous Vehicle Competition at EagleBank Arena on April 24, 2026.

Meah Chambers and Gagan Manjunatha at the competition. Photo by Andani Munkaila/Office of University Branding

The competition challenged student teams to design and deploy autonomous aerial and ground vehicle systems capable of executing a series of increasingly complex missions. Unlike prior outdoor iterations, the 2026 competition eliminated access to GPS, forcing teams to rely on advanced onboard sensing and visual navigation techniques to orient themselves in space. EagleBank Arena has been hosting national robotics competitions since 2023 with support from an Office of Naval Research grant to transform the venue into a robotics experimentation and sporting venue.

George Mason’s autonomous robotics team rose to the challenge. Over the course of the competition, their system successfully completed all three mission objectives, earning the top overall score and securing first place. The win capped months of late nights and creative problem-solving by a team that was not competing for a grade, credit, or formal requirement, but purely out of enthusiasm for robotics.

“This isn’t even an official club yet,” said computer science major Gagan Manjunatha. “We’re here for the love of the game.”

For many teams at the competition, participation counts as a senior design project. George Mason’s team, however, had no such structure. “A lot of teams do use this as their senior design project, but the nice thing about us not doing it is that we have people that can come back year after year,” said team lead Meah Chambers, a junior majoring in electrical engineering.

Photo by Ron Aira/Office of University Branding

“I like the hands-on experience,” she said. This was Chambers’ third robotics team competition, each of which she found rewarding. “It’s like I’ve done three mini senior designs. I like the design team experience, working on a team for an end goal.”

The technical demands of the competition were steep. Challenge one required a drone to autonomously take off from a moving ground vehicle and land back on it. The second challenge layered on autonomous search and detection, requiring the drone to identify a visual tag, communicate its location, and guide the ground vehicle to the target. A third challenge added obstacle detection and avoidance for both aerial and ground systems.

To meet those demands, the team divided into drone and ground sub‑teams, with students specializing in software, hardware, mechanical design, and systems integration. Majors across electrical engineering, computer engineering, mechanical engineering, and computer science were represented. Visual‑inertial simultaneous localization and mapping (VSLAM) replaced GPS, allowing the drone to understand its position using cameras and onboard sensors.

“We were given the challenges in September and two semesters to plan and work on our system,” said electrical engineering major Emma Misevschi. Without senior design funding or course integration, students volunteered their time over the academic year to design, build, test, and refine their system. “Everything just happened to come together this week,” she said.

Some members of George Mason's 2026 Raytheon Autonomous Vehicle Competition team. Photo by Andani Munkaila/Creative Services/91��.

Funding constraints added another layer of difficulty. While funding for system components were provided by competition sponsor Raytheon, the money arrived late in the academic year, forcing the team to borrow equipment, lean on shared research lab resources, and compress months of testing into intense overnight sessions.

Despite many team members having stayed up testing into the wee hours of the night before the competition, spirits were high at the end of the first day of the two-day competition. Chambers joked, “Two hours is like a nice nap instead of sleeping for the night.”

Computer engineering major and ground team lead Logan Teyema added the (understandably tired) motto of hustle culture, “Water is life, food is fuel, and sleep is a crutch.”

In the end, their teamwork paid off. When the judges arrived, George Mason’s system performed cleanly and consistently, earning top marks across the challenges and finishing first overall.

The full team includes Luis Anchundia, James Daniel, Konraad Ludwig, Hassan Youssef, Emma Misevschi, Thomas Fletcher, Christopher Romero-Klevisha, Toan Do, Meah Chambers, Gagan Manjunatha, Connor Roberts, William Maynard, Logan Teyema, Ellie Kwon, Rico Rodriguez, Nick Kasa, and Yousif Alani. Faculty advisors include Cameron Nowzari, Xuesu Xiao, and Ningshi Yao.

Are you interested in joining the team? Learn more on the team’s website and watch a video about their experiences.

Learn about MARC

In This Story

Cameron Nowzari

Ningshi Yao

Xuesu Xiao

Topics

competitions

Electrical Engineering

Computer Engineering

Mason Autonomy and Robotics Center

robotics

Navy veteran charts a new course with George Mason robotics

tdonnel — Mon, 09 Mar 2026 15:28:39 +0000

Navy veteran charts a new course with George Mason robotics tdonnel Mon, 03/09/2026 - 11:28

In This Story

Xuesu Xiao

As a scientist for the federal government, Naval Reservist David Eichinger’s path to a master’s degree in computer science at 91�� was less than traditional. A microbiology major turned technologist, Eichinger is now a graduate researcher in robotics. He represents the motivated, resilient students George Mason empowers, balancing academics with the demands of life beyond the classroom.

After noticing patterns in his work, Eichinger realized he needed computational tools to solve complex problems. Over the course of nine years—first in a post‑baccalaureate certificate, now in the master’s program—Eichinger built the foundation he needed.

David Eichinger. Photo provided.

“I chose the computer science program because I was interested in learning computer vision, machine learning, deep learning, and robotics to understand pattern recognition in data,” he said.

When he began exploring graduate programs, he sought proximity to his job and support for veterans in addition to an excellent program. That support system at George Mason has been critical as he balances graduate studies with military life, work, and family. It’s also one reason he believes George Mason is such a strong fit for veterans and nontraditional students like himself.

“George Mason’s [Computer Science Program] was just very flexible as far as the time of day they offer their classes,” he said, adding that classes can be either online or in person. Even more important to him was faculty access.

Today, Eichinger works in Xuesu Xiao’s robotics lab in Fuse at Mason Square, working on off-road mobility and social navigation robotics. The lab is lively, collaborative, and hands‑on. “It’s like a little makerspace to geek out on with different toys,” he said. “It is a joy to play with these robots and try to program them to move on their own.”

As a nontraditional student, Eichinger appreciates that George Mason creates space for varied pathways and goals. For veterans, career changers, and those returning to school later in life, his path demonstrates how George Mason’s computer science master’s program meets students where they are and takes them where they hope to go.

“It is not a walk in the park,” he said, “but it is worth doing if you believe in it."

Topics

Tech Talent Investment Program (TTIP)

Students use AI to solve everyday challenges at recent Fail-a-Thon

sbrown79 — Mon, 12 Jan 2026 17:35:24 +0000

Students use AI to solve everyday challenges at recent Fail-a-Thon  sbrown79 Mon, 01/12/2026 - 12:35

91�� is preparing students to transform setbacks into stepping stones with a “Fail-a-Thon," a hackathon event where failing forward is the goal.

The event, hosted by the College of Engineering and Computing, encouraged students to explore bold ideas under two themes: artificial intelligence (AI) for everyday challenges and tech for well-being and creativity.

Junior computer science major Oluwatomisin Badmus and his partner, junior applied computer science major Chesney Noye, working under the team name “AfroHacks,” took first place. 

Chesney Noye (center) and Oluwatomisin Badmus presenting at the Fail-a-thon. Photo provided.

Badmus and Noye are international students and wanted to emphasize the importance of checking in with one another within their community. The duo used an AI coding tool to build an application that allows users to log their current mood over the course of the day, and the system then uses the logged mood when responding to questions.

“You might describe it as a mood-aware AI chatbot,” explained Badmus.

They were able to complete a working version of the application to present to the judges. The team 808s won 2nd place and the Three Musketeers won 3rd. 

“I'm very passionate about AI, so I make sure to take advantage of every educational opportunity regarding AI. I hope to apply that knowledge in my work to make an impact both in and out of school,” said Badmus, an Honors College student. 

Badmus said he has participated in other George Mason hackathons and competitions at other institutions such as Morgan State, John Hopkins University, and online. Badmus encouraged Noye to participate in the event with him in hopes that he would also find the experience rewarding. 

“I’ve always wanted to participate in a hackathon, so when I saw the flyer for the Fail-a-thon, I knew it would be a great opportunity to gain experience in a relatively low-stakes environment,” said Noye, who has a concentration in software engineering.

Noye said hackathons always seemed too intimidating, but he was encouraged by the fail-a-thon's easygoing approach.

“Having an event centered around failing gave people room to go out there with their ideas, and getting to see all the projects everyone else came up with was great,” he said.

“Getting to share stories with the other participants there on where our projects failed, what weird bugs we had, and how different our initial ideas and final products ended up was a great bonding moment and really helped normalize the idea that failing is okay,” said Noye.

The students had two hours to build real-world practical projects using provided AI tools. Many of the project features were built and working, and judges and attendees could see them live during the presentations. 

Humaira Akhtari (left) with Christi Cartwright Wilcox, director, Office of Outreach Student Success and Engagement. Photo provided.

“Watching students turn ideas into functional solutions in just two hours was genuinely exciting and inspiring,” said Humaira Akhtari, a term instructor in the Department of Information Science and Technology and one of three faculty judges at the event.

Other judges included professors Socrates Dimitriadis and Maha Shamseddine from the Department of Computer Science.

“I kept telling the teams, ‘I would be the first person to use your app’ because their ideas were genuinely useful. Seeing students build practical solutions, collaborate across disciplines, and confidently present their work made the experience incredibly rewarding,” said Akhtari. “It brings me so much joy seeing my students grow beyond the classroom. Whether it’s capstone presentations, Fail-a-Thon, or Engineering Week, I love seeing how my students are thriving.” 

Students from electrical engineering, mechanical engineering, computer science, IST, and cyber security engineering participated. The mix of backgrounds really elevated the ideas and discussions, said Akhtari. 

When evaluating projects, judges looked at creativity, risk-taking, learning through failure, and how well teams communicated their ideas.  

“Rather than penalizing mistakes, we looked for evidence of iteration, reflection, and growth. The goal was to celebrate experimentation and meaningful learning,” said Akhtari. 

“Events like Fail-a-Thon create a safe space where students learn that failure is not something to avoid—it’s part of the process. This mindset is essential not only in academics, but also in entrepreneurship and real-world problem solving,” said Akhtari.

One team built a study management tool where students could upload their course syllabus, and the app would automatically generate a personalized study plan based on upcoming assignments and deadlines.

Another team designed a nutrition app that helps users track dietary preferences like Halal, vegan, and other restrictions.  

There were also projects focused on productivity, motivation, and wellness—apps that help users stay on track with their schedules, motivate them to stay consistent at the gym, or even guide users while grocery shopping based on their calorie goals.  

Topics

competitions

Hackathon

Applied computer science

Honors College

Rebecca Sutter, DNP, APRN, BC-FNP

CEC students

In This Story

Humaira Akhtari

Socrates Dimitriadis

Maha Shamseddine

Artificial Intelligence at George Mason

Anonymity’s ARX nemesis

Nathan Kahl — Mon, 20 Oct 2025 15:12:08 +0000

Anonymity’s ARX nemesis Nathan Kahl Mon, 10/20/2025 - 11:12

A team of faculty and students from 91�� recently discovered a vulnerability in a widely used anonymization tool. They presented their findings last week in Taiwan at the Association for Computing Machinery Conference on Computer and Communications Security (ACM CCS), one of the world’s most prestigious computer security conferences, with a very low paper acceptance rate.

The problem they discovered was with ARX, an open-source data anonymization tool, which provides what is referred to as k-anonymity. It is a commonly used tool in clinical settings to maintain data privacy. The discovery is particularly important at a time when more and more private data is being used in a variety settings and systems.

Evgenios Kornaropoulos, an assistant professor in the Department of Computer Science, said, “Sometimes this type of microdata is very valuable. Tools like ARX anonymize the data so it’s compliant with HIPAA, and then that data can be shared with policymakers, engineers, scientists, and others who will make policy decisions and scientific studies based on this information.”

While many people receiving medical care are comfortable with their information being included in larger data sets for purposes of medical discovery, they likely do not want personal, identifiable information released.

“For patients, and especially those from more vulnerable or marginalized communities, data privacy is not an abstract concern, it’s deeply tied to trust in the health care system," said paper co-author Rebecca Sutter, a professor in the School of Nursing, and director of the MAP Clinics. "The integrity of tools like ARX matters because they underpin how we protect patient information while advancing public health research. When anonymization fails, it’s not only a technical vulnerability, it’s a human one."

Computer science PhD student Somiya Chhillar, lead author on the paper, said that the ubiquity of ARX was a reason they chose to study it. “We wanted to see how ARX really operates and how the algorithm works. While we were doing that, we realized that a few of the steps that it takes are very opportunistic, and because of that, it leaks information that we shouldn't be finding out by just looking at the anonymized data.”

Chhillar said that ARX follows a “greedy strategy,” explaining that there is a tension between privacy and utility. When data is shared, it should be useful without leaking information. The best metric for deciding the data usefulness is measured by information loss while the data is being made private. “The algorithm tries to minimize information loss while anonymizing the data, and ideally, we want the least possible information loss. And that's the greedy aspect of it; it's not always going for the most private, it’s just going for the most utility.”

This is what backfires, said Kornaropoulos, because experts (or attackers) can reverse engineer the anonymization steps the algorithm took throughout its execution to maximize utility and figure out properties of the data that were there before and after this anonymization step.

Kornaropoulos praised his student’s dedication to the discovery, noting that Chhillar “worked on this project for a while, and this code base of ARX is an elaborate tool, with thousands of lines of code. She had to go through it to truly internalize understand everything that's going on there,” he said.

The project was supported by a Commonwealth Cyber Initiative (CCI) grant from the program, “Securing Interactions between Humans and Machines,” and as a requirement of the grant, the project crossed different parts of the university. The College of Engineering and Computing collaborated with Mason and Partners (MAP) Clinics, which provided the data.

In This Story

Learn more about Cybersecurity at George Mason

Bluetooth blues? George Mason turns a bug into a big win

Nathan Kahl — Thu, 21 Aug 2025 01:28:32 +0000

Bluetooth blues? George Mason turns a bug into a big win Nathan Kahl Wed, 08/20/2025 - 21:28

91�� College of Engineering and Computing faculty members made a significant impact at the 2025 USENIX Security Conference, in Seattle, including winning the Distinguished Artifact Award.

Photo provided

“Tracking You from a Thousand Miles Away! Turning a Bluetooth Device into an Apple AirTag Without Root Privileges,” a paper by the Department of Computer Science’s PhD student Junming Chen, PhD candidate Xiaoyue Ma, and Lannan Luo and Qiang Zeng, both associate professors, won the prestigious Distinguished Artifact Award, which was granted to only six of the 2,385 submitted papers.

Their research demonstrated how to turn Bluetooth devices into a trackable "AirTags" without requiring root privileges. The research revealed a vulnerability in Apple's Find My Network that can leverage more than a billion active Apple devices as unwitting finders. The high-quality artifact with its complete documentation and practical implementation provides researchers with an invaluable toolkit for evaluating tracking vulnerabilities in crowd-sourced location networks. Their work was previously reported by the university and received media attention in various outlets.

A crowd gathers at the team's poster session. Photo provided.

USENIX Security is one of the country’s premier cybersecurity conferences, and this year received 2,385 paper submissions with a 17% acceptance rate. The following George Mason research papers were also accepted at USENIX this year. 

Rowhammer-Based Trojan Injection: One Bit Flip Is Sufficient for Backdooring DNNs
Xiang Li, Ying Meng, Junming Chen, Lannan Luo, and Qiang Zeng, 91��

DISPATCH: Unraveling Security Patches from Entangled Code Changes
Shiyu Sun and Yunlong Xing, 91��; Xinda Wang, University of Texas at Dallas; Shu Wang, Palo Alto Networks, Inc.; Qi Li, Tsinghua University; Kun Sun, 91��

TYPEPULSE: Detecting Type Confusion Bugs in Rust Programs
Hung-Mao Chen and Xu He, 91��; Shu Wang, 91�� and Palo Alto Networks Inc.; Xiaokuan Zhang and Kun Sun, 91��

LLMmap: Fingerprinting for Large Language Models
Dario Pasquini, RSAC Labs; Evgenios M. Kornaropoulos and Giuseppe Ateniese, 91��

Explore the College of Engineering and Computing

In This Story

Qiang Zeng

Topics

AI’s blind spots, one PhD student’s clear vision

Ryley McGinnis — Mon, 11 Aug 2025 18:36:42 +0000

AI’s blind spots, one PhD student’s clear vision Ryley McGinnis Mon, 08/11/2025 - 14:36

When artificial intelligence makes a mistake, the consequences can be annoying—or they can be life-altering. For one 91�� computer science PhD student, the stakes are clear: biased algorithms in health care aren’t just a technical flaw, they’re a human risk. And with internship experience teaching him crucial skills beyond the classroom, Fardin Ahsan Sakib is ready to make a difference in health care.

Sakib’s research in natural language processing (NLP) addresses concerns that many may have when working with emerging large language models (LLMs), but when it is applied to health decisions, there could be deeper negative risks. Tools like ChatGPT pull from vast amounts of information, but they have sometimes been known to “hallucinate,” or make up information.

“Sometimes these systems are taking a shortcut to get you an answer,” said Sakib. “But regardless of where it comes from, it can provide you incorrect information.” And in the health care space, these LLMs could aid doctors, but not when they could be driving improper care.

In electronic health records (EHRs), patients’ diagnoses, medical history, and demographic data are stored and organized. This information includes social determinants of health, like employment status, family situations, or housing conditions, hidden in records.

Fardin Ahsan Sakib is seeking to bring accurate and reliable large language models' capabilities to healthcare.

“These factors can affect up to 80% of health outcomes,” Sakib said. “So it's very important that we can extract them correctly from clinical notes and that the model is not introducing any bias.”

Sakib poses a scenario: A doctor is using an NLP tool to quickly assess a new patient’s health. The LLM is pulling from the patient’s records, and the physician asks the system, “Is this patient a smoker?” The system quickly sifts through the data, and says that yes, this patient is a smoker. The physician then proceeds to make care recommendations based on this information. Maybe they order a lung cancer screening, or they speak with the patient about smoking cessation resources.

But what if that answer was incorrect? The LLM decided to take a shortcut, because, based off the information it has, it discovered that most people with similar demographic data to the patient are indeed smokers, but this one isn’t.

“There are two things at play: bias and hallucination,” said Sakib. “First, algorithms can only use the information they have, and if that information is missing an entire racial or ethnic group, it can be biased. Second, these models can use this biased information to take shortcuts, leading to them delivering false information.”

Sakib isn't simply identifying these problems; he's developing solutions. His recent research on detecting and mitigating shortcut learning in health record processing was accepted for presentation at the 63rd Annual Meeting of the Association for Computational Linguistics (ACL 2025), one of the premier NLP conferences.

That desire to build reliable and trustworthy NLP tools has driven Sakib’s academic work and his professional pursuits.

At Brillient Corporation, where he interned last summer, Sakib worked on creating a retrieval augmented generation system that connected an LLM to the Food and Drug Administration’s (FDA) knowledge base to make accessing and retrieving information faster and grounded in facts. He and his colleagues submitted a patent for this effort.

This summer, he's deep into another high-impact internship at Amazon. “Amazon wants to automate support so that when you ask for help, a large language model can try to solve the problem before handing it off to a human,” he said.

Despite the different settings, he sees clear continuity between his internships and academic work. “The industry experience helps me in my research, and my research experience helps in industry. It goes both ways,” he said. “In academia, collaboration is usually focused within a lab or research group. In industry, I’ve worked with engineers, product managers, and domain experts all at once, spanning from health regulators to AWS cloud architects. That diversity of perspectives changes how you solve problems, and I’ve brought that mindset back into my research collaborations.”

It’s that dual perspective—academic precision paired with industry scale—that he plans to take with him into industry after graduation.

“George Mason has prepared me for a lot. From day one, all of the professors have helped me grow as a researcher, a person, and as a team member,” said Sakib.

Topics

large language models

Long Nguyen and Kimmy Duong School of Computing

internships

CEC students

One tiny flip that opens a backdoor in AI

Nathan Kahl — Mon, 11 Aug 2025 13:13:32 +0000

One tiny flip that opens a backdoor in AI Nathan Kahl Mon, 08/11/2025 - 09:13

A self-driving motor vehicle is cruising along, its numerous sensors and cameras telling it when to brake, change lanes, and make turns. The vehicle approaches a stop sign at a high rate of speed, but instead of stopping, it barrels through, causing an accident. The problem will probably never be found by investigators, but instead of reading the stop sign as a stop sign, the car had been hacked to see it instead as a speed limit sign.

According to research by 91��’s Qiang Zeng, an associate professor in the Department of Computer Science, and PhD student Xiang Li and colleagues, it is remarkably simple for a would-be hacker to pull off such a feat.

“An attacker can selectively flip only one bit, and this changing of the bit from 0 to 1 allows an attacker to attach a patch onto any image and fool the AI system. Regardless of the original image input, that patched image will be interpreted as the attacker’s desired result,” said Zeng.

So, if the hacker wants an artificial intelligence (AI) system to see a stop sign as something else, or a cat as a dog, the effort is minimal. Consider a scene potentially pulled from a Mission: Impossible movie, where a corporate spy can pass himself off as a CEO, gaining access to sensitive information.

Zeng and colleagues presented a paper with the findings at USENIX Security 2025, one of the nation’s premier cybersecurity conferences.

AI systems have what’s called a deep neural network (DNN) as a key component. DNNs let AI handle complex data and perform many different tasks. They work by using numerical values, called weights, each typically stored in 32 bits. There are hundreds of billions of bits in a DNN, so changing only one is particularly stealthy, according to Zeng.

“Once the attacker knows the algorithm, then it can take literally only a couple minutes to make the change. And you won’t realize you’ve been attacked because the AI system will work as usual. Flipping one bit effectively sneaks a backdoor into AI, exploitable only by those who know the patch,” he said.

Prior work in this area typically added a patch tailored to the original image—for example, modifying a stop sign specifically so that it is misclassified as a 65 mph speed limit sign. This new research uses what’s called a uniform patch that works regardless of the original input; the hacker could cause the system to interpret various signs as a speed limit sign. This input-agnostic attack represents a newer and more dangerous threat.

When they began the project the researchers wanted to learn the minimum level of effort needed to launch such an attack, recognizing that flipping hundreds of bits is impractical and gets exponentially difficult. “It turned out, we only needed to flip one,” Zeng said with a laugh. The team named their attacking system, appropriately, OneFlip.

The researchers are now only looking at the implication for images, as image classifiers are among the most popular AI systems, though they suspect this hacking technique could also work for things like speech recognition. Zeng said that their success rate during testing was near 100% and stressed that all DNN systems are likely to be subject to such hacking.

This does not necessarily mean such hacking will run rampant. To launch the attack, Zeng said, there are two requirements: access to the exact weights (numerical values that the model learns during training of the AI system) and the ability to execute code on the machine hosting the model. For example, in cloud environments, attackers might exploit shared infrastructure where multiple tenants’ programs run on the same physical hardware.

Learn about AI at George Mason

Topics

Cyber Security

Cyber Security Research

Autonomous Cars

Costello College of Business

Research

Barbara Snyder honored by National Academic Advising Association for excellence as an advising administrator

lclarkg — Tue, 29 Jul 2025 17:50:14 +0000

Barbara Snyder honored by National Academic Advising Association for excellence as an advising administrator lclarkg Tue, 07/29/2025 - 13:50

Two members of George Mason's academic advising community were honored with regional awards from the National Academic Advising Association (NACADA) this spring. These awards recognize excellence in academic advising in NACADA Region 2, which includes Delaware, Washington, D.C., Maryland, New Jersey, Pennsylvania, and Virginia.

Barbara Snyder, director of student success and academic advising in the Costello College of Business, received the NACADA award for Excellence in Advising—Advising Administrator.

Barbara Snyder, BS Psychology ’08, director of student success and academic advising in the Costello College of Business, received the award for Excellence in Advising—Advising Administrator.

Joshua Fletcher, undergraduate academic advisor in the Computer Science Department, was honored with the award for Excellence in Advising—Primary Role Advisor. Read more about him.

Fletcher and Snyder were formally recognized at the NACADA Region 1 and 2 conference in April in Buffalo, New York.

Snyder will be a George Mason student once again this fall, when she starts the doctoral program in Education with a concentration in Higher Education. Snyder earned a master’s in student personnel in higher education from the University of Florida.

We asked Snyder to share some insights her experiences in academic advising and what it means to be recognized for her work.

How long have you worked at George Mason? How has your job changed over the years?

I began as an academic advisor in the Costello College of Business in 2011, then spent a few years at the University of Houston-Clear Lake, where I helped launch their first centralized advising center. I returned to George Mason in 2017, and since then, I’ve become the director of student success and academic advising for the Costello College of Business.

Over the years, my roles have evolved from individual advising, to shaping strategy, training, and student success initiatives at the college level. Each phase of my career has reinforced my belief that academic advising is one of the most essential components of student success.

What are your main responsibilities in your role?

I work alongside a team of directors to oversee undergraduate academic advising for more than 4,500 business majors. I co-lead the strategic vision for the office and serve as the main coordinator of onboarding and training for all new advisors.

I also oversee pre-orientation advising, orientation programming, and student-centered initiatives like the Global Engagement Scholars Program and first-generation student programming. Additionally, I serve as Costello’s undergraduate advising liaison to the university’s Academic Advising Leadership Council, working with advising leaders from each college to create a consistent and collaborative advising experience across the university.

What do you like best about your job?

I love that my work allows me to impact both students and staff. Supporting advisors in their growth, watching students achieve milestones they once doubted were possible, and designing programs that help people feel a sense of belonging—those are the moments that keep me going.

Joshua Fletcher and Barbara Snyder were recognized for excellence in academic advising at the NACADA conference in April. Photo provided

You were recognized at the recent NACADA regional conference with their Excellence in Advising—Advising Administrator award. What are your biggest takeaways from their conferences?

I’ve attended both regional and annual NACADA conferences over the years. What I appreciate most is the sense of community and shared purpose. You are surrounded by professionals who deeply care about student success and who are generous in sharing tools, ideas, and lessons learned.

I enjoy catching up with colleagues I’ve worked with through the years and connecting with new advisors entering the field. I find a lot of value in both mentoring and being mentored; those relationships and exchanges of experience are some of the most energizing parts of the conference. Every time I attend, I come back inspired.

Do any memorable moments stand out in your academic advising experience?

One that stands out was leading a full virtual orientation and advising experience for more than 1,500 students during the pandemic. We had to pivot quickly, redesign everything, and still make students feel seen and supported. It was one of the most exhausting, yet rewarding, moments of my career.

I also carry with me the many memories of supporting academic advisors throughout their professional journeys, especially those who have gone on to become leaders across campus or at other institutions. Being part of their growth is incredibly meaningful and a big part of what keeps me passionate about this work.

Academic advising at George Mason

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