Now a senior professional working at the intersection of business automation and AI integration, Lane balances a high-tech career with a people-first leadership style as the head of the College’s Computing Alumni Network. In this role, she promotes mentorship, global outreach, and the "non-linear" paths that shape a successful career.
In the following Q&A, Lane shares insights from her journey from a computer science student to an AI automation expert, discusses the "human" side of technology, and outlines her vision for growing our alumni community well beyond Atlanta.
What drew you to get involved with the Computing Alumni Network?
Honestly, it started for personal reasons. I wanted to expand my network and find my people. But what kept me engaged was something deeper. I reconnected with the College about ten years ago, and I quickly realized how much I'd missed by not being involved sooner.
There's an energy you get from staying close to a place that shaped you, and I wanted to help provide that for others the way I wished it had been for me.
Can you share a moment or initiative with the Network that you’re especially proud of?
We've had some wonderful events over the years — some that really stand out, others that were quieter but no less meaningful. Reflecting on it, what I'm most proud of is how the Network has endured the turbulence of the last few years.
Navigating the pandemic, adapting to significant changes in our supporting staff, and still showing up for students and each other — that resilience is something I don't take for granted.
How has the alumni community changed since you graduated?
I can't speak to the full arc. I got involved with the Computing Network in 2019, so my perspective is more recent. What I can say is that our focus has become more centered on the students, how we can give back, and how we can include our global alumni network.
Why do you think staying connected to the College matters, even years after graduation?
I'm living proof that it's never too late and that getting involved is more than worthwhile. The relationships you build here, the sense of shared identity with people who went through something hard and came out the other side — that doesn't expire. And the further you go in your career, the more you realize how rare it is to find a community with that kind of foundation.
You’re now working in AI automation—what excites you most about your work today?
What gets me out of bed every morning is the chance to make work more human again. There's a pattern I see everywhere right now where people are being used as the connective tissue between disconnected systems — doing repetitive, manual work that drains the meaning out of their days. It's deflating in a way that's hard to overstate. I believe automation, when done right, can give people back the time and energy. If I can add some genuine meaning back to someone's workday, that's a win I'll take every time.
How did your experience as a CS student prepare you for a career in tech and business?
Georgia Tech taught me how to adapt — and more importantly, that I could. It gave me the discipline to teach myself new things, the humility to ask for help when I needed it, and the confidence to know I can do hard things. That combination has been the through-line of my entire career. The specific technical skills matter, but it's that mindset that's carried me through every pivot and challenge since.
What advice would you give to current students who hope to follow a similar path?
Find a mentor, and don't wait until you feel like you need one. The relationships you build now — with professors, with older students, with alumni — will compound in ways you can't predict.
Also, stay curious beyond your major. The most interesting problems I've worked on sit at the intersection of technology and human behavior, and I never would have found my way there if I'd kept my head down in purely technical work or kept doing only what I already knew.
How can alumni best support students and recent graduates right now?
Mentoring is the highest-leverage thing you can do, especially for students graduating into such unpredictable times. It doesn’t have to be formal or structured mentoring. Sometimes it's just about being genuinely available, replying to an email, scheduling a coffee chat, or sharing an honest picture of what your career actually looked like, not the polished version. Students need to see that the path isn't always linear, and that people who have navigated uncertainty are willing to help them do the same.
What’s next for the Network—any upcoming priorities or initiatives you’re excited about?
Our big focus right now is growth — expanding the College of Computing alumni in Atlanta and beyond. There's a lot of Georgia Tech computing talent spread across the country and the world, and we want those people to feel that this community is for them, too, not just those of us who stayed local.
Making that geographic reach feel real, not just theoretical, is something we're actively working toward.
]]>Georgia Tech College of Computing
albert.snedeker@cc.gatech.edu
]]>TokenSmith is a citation-supported large language model (LLM) tutor that can be hosted locally on a user’s personal computer. The tutor only provides answers based on course materials, such as the textbook or lecture slides.
Associate Professor Joy Arulraj began the project with support from the Bill Kent Family Foundation AI in Higher Education Faculty Fellowship last year. The fellowship, led by Georgia Tech’s Center for 21st Century Universities, supports faculty projects exploring innovative and ethical uses of AI in teaching.
Arulraj has enlisted assistant professors Kexin Rong and Steve Mussmann to help build TokenSmith.
Mussmann said TokenSmith is a synergistic blend of a database system and a machine learning system. The model stores textbooks, textbook annotations by course staff, common questions and answers, a learning state of the student, and student feedback in a structured database system. However, machine learning plays a key role in the answer generation as well as adapting the system to the student, course staff guidance, and user feedback.
"What excites me most is demonstrating how data-driven ML and principled database systems design can reinforce each other — one providing adaptability and flexibility, the other providing structure and traceability — in a way that benefits students," Mussmann said.
Keeping the model local has been an important focus of the project. The team wanted to create an AI tutor that helps students learn from their class resources rather than just giving answers. With each response, TokenSmith cites the origin of the answer in the provided documents.
“One problem with LLMs is that they can hallucinate and provide wrong answers, but in this controlled environment, we can add these guardrails to make sure it’s actually helpful in an educational setting,” Rong said.
Rong said she feels that students often undervalue textbooks, and she hopes TokenSmith can motivate students to make better use of them.
“Textbooks can sometimes be daunting, but maybe if we combine them with the model, students might be more willing to read a paragraph or page in the textbook, and that could help clarify something for them,” she said.
Running the model locally is more cost-effective and helps preserve the user’s privacy. But running the new tool locally comes with technical challenges.
One challenge with creating the model is speed. Since it is a locally based model, TokenSmith depends solely on the user’s computer memory. Tests have also shown that the tutor currently struggles to answer more complex questions.
“We are interested in pushing the boundaries of these local models so that they give students good answers and also run fast enough to keep students engaged,” Arulraj said.
]]>Associate Professor Joy Arulraj began the project with support from the Bill Kent Family Foundation AI in Higher Education Faculty Fellowship last year. The fellowship, led by Georgia Tech’s Center for 21st Century Universities, supports faculty projects exploring innovative and ethical uses of AI in teaching.
]]>Georgia Tech researchers are making AI easier to understand through their work on Transformer Explainer. The free, online tool shows non-experts how ChatGPT, Claude, and other large language models (LLMs) process language.
Transformer Explainer is easy to use and runs on any web browser. It quickly went viral after its debut, reaching 150,000 users in its first three months. More than 563,000 people worldwide have used the tool so far.
Global interest in Transformer Explainer continues when the team presents the tool at the 2026 Conference on Human Factors in Computing Systems (CHI 2026). CHI, the world’s most prestigious conference on human-computer interaction, will take place in Barcelona, April 13-17.
“There are moments when LLMs can seem almost like a person with their own will and personality, and that misperception has real consequences. For example, there have been cases where teenagers have made poor decisions based on conversations with LLMs,” said Ph.D. student Aeree Cho.
“Understanding that an LLM is fundamentally a model that predicts the probability distribution of the next token helps users avoid taking its outputs as absolute. What you put in shapes what comes out, and that understanding helps people engage with AI more carefully and critically.”
A transformer is a neural network architecture that changes data input sequence into an output. Text, audio, and images are forms of processed data, which is why transformers are common in generative AI models. They do this by learning context and tracking mathematical relationships between sequence components.
Transformer Explainer demystifies how transformers work. The platform uses visualization and interaction to show, step by step, how text flows through a model and produces predictions.
Using this approach, Transformer Explainer impacts the AI landscape in four main ways:
“When I first learned about transformers, I felt overwhelmed. A transformer model has many parts, each with its own complex math. Existing resources typically present all this information at once, making it difficult to see how everything fits together,” said Grace Kim, a dual B.S./M.S. computer science student.
“By leveraging interactive visualization, we use levels of abstraction to first show the big picture of the entire model. Then users click into individual parts to reveal the underlying details and math. This way, Transformer Explainer makes learning far less intimidating.”
Many users don’t know what transformers are or how they work. The Georgia Tech team found that people often misunderstand AI. Some label AI with human-like characteristics, such as creativity. Others even describe it as working like magic.
Furthermore, barriers make it hard for students interested in transformers to start learning. Tutorials tend to be too technical and overwhelm beginners with math and code. While visualization tools exist, these often target more advanced AI experts.
Transformer Explainer overcomes these obstacles through its interactive, user-focused platform. It runs a familiar GPT model directly in any web browser, requiring no installation or special hardware.
Users can enter their own text and watch the model predict the next word in real time. Sankey-style diagrams show how information moves through embeddings, attention heads, and transformer blocks.
The platform also lets users switch between high-level concepts and detailed math. By adjusting temperature settings, users can see how randomness affects predictions. This reveals how probabilities drive AI outputs, rather than creativity.
“Millions of people around the world interact with transformer-driven AI. We believe that it is crucial to bridge the gap between day-to-day user experience and the models' technical reality, ensuring these tools are not misinterpreted as human-like or seen as sentient,” said Ph.D. student Alex Karpekov.
“Explaining the architecture helps users recognize that language generated by models is a product of computation, leading to a more grounded engagement with the technology.”
Cho, Karpekov, and Kim led the development of Transformer Explainer. Ph.D. students Alex Helbling, Seongmin Lee, Ben Hoover, and alumnus Zijie (Jay) Wang assisted on the project.
Professor Polo Chau supervised the group and their work. His lab focuses on data science, human-centered AI, and visualization for social good.
Acceptance at CHI 2026 stems from the team winning the best poster award at the 2024 IEEE Visualization Conference. This recognition from one of the top venues in visualization research highlights Transformer Explainer’s effectiveness in teaching how transformers work.
“Transformer Explainer has reached over half a million learners worldwide,” said Chau, a faculty member in the School of Computational Science and Engineering.
“I'm thrilled to see it extend Georgia Tech's mission of expanding access to higher education, now to anyone with a web browser.”
]]>Georgia Tech researchers are making AI easier to understand through their work on Transformer Explainer. The free, online tool shows non-experts how ChatGPT, Claude, and other large language models (LLMs) process language.
Transformer Explainer is easy to use and runs on any web browser. It quickly went viral after its debut, reaching 150,000 users in its first three months. More than 563,000 people worldwide have used the tool so far.
Global interest in Transformer Explainer continues when the team presents the tool at the 2026 Conference on Human Factors in Computing Systems (CHI 2026). CHI, the world’s most prestigious conference on human-computer interaction, will take place in Barcelona, April 13-17.
]]>That’s one of the main findings from a study by AI Caring on what older adults expect from explainable AI (XAI).
AI Caring is one of three AI Institutions led by Georgia Tech and funded by the National Science Foundation (NSF). The institution supports AI research that benefits older adults and their caregivers.
Niharika Mathur, a Ph.D. candidate in the School of Interactive Computing, was the lead author of a paper based on the study. The paper will be presented in April at the 2026 ACM Conference on Human Factors in Computing Systems (CHI) in Barcelona.
Mathur worked with the Cognitive Empowerment Program at Emory University to interview 23 older adults who live alone and use voice-activated AI assistants like Amazon’s Alexa and Google Home.
Many of them told her they feel excluded from the design of these products.
“The assumption is that all people want interactions the same way and across all kinds of situations, but that isn’t true,” Mathur said. “How older people use AI and what they want from it are different from what younger people prefer.”
One example she gave is that young people tend to be informal when talking with AI. Older people, on the other hand, talk to the agent like they would a person.
“If Older adults are talking to their family members about Alexa, they usually refer to Alexa as ‘she’ instead of ‘it,’” Mathur said. “They tend to humanize these systems a lot more than young people.”
The study evaluated AI explanations that drew information from four sources of data:
Mathur said older users trust the agent more when it bases its explanations on data from the first three sources. However, internal reasoning creates skepticism.
Internal reasoning means the AI doesn’t have enough data from the other sources to give an explanation. It provides a percentage to reflect its confidence based on what it knows.
“The overwhelming response was negative toward confidence scores,” Mathur said. “If the AI says it’s 92% confident, older adults want to know what that’s based on.”
This is another example that Mathur said points to generational preferences.
“There’s a lot of explainable AI research that shows younger people like to see numbers in explanations, and they also tend to rely too much on explanations that contain numerical confidence. Older adults are the opposite. It makes them trust it less.”
Mathur said that AI agents interacting with older adults should serve a dual purpose. They should provide users with companionship and support independence while reducing the caretaking burden often placed on family members.
Some studies have shown that engineers have tended to favor caretakers in the design of these tools. They prioritize daily tasks and routines, leaving some older adults to feel like they are merely a box to be checked.
She discovered that in urgent situations, older users prefer the AI to be straightforward, while in casual settings, they desire more conversation.
“How people interact with technological systems is grounded in what the stakes of the situation are,” she said. “If it had anything to do with their immediate sense of safety, they did not want conversational elaboration. They want the AI to be very direct and factual.”
Mathur said AI agents that interact with older adults are ideally constructed with a dual purpose. They should provide companionship and autonomy for the users while alleviating the burden of caretaking that is often placed on their family members.
Some studies have shown that engineers have strayed toward favoring caretakers in the design of these tools. They prioritize daily tasks and routines, leaving some older adults to feel like they are a box to be checked.
“They’re not being thought of as consumers,” Mathur said. “A lot of products are being made for them but not with them.”
She also said psychological well-being is one of the most important outcomes these tools should produce.
Showing older adults that they are listened to can significantly help in gaining their trust. Some interviewees told Mathur they want agents who are deliberate about understanding their preferences and don’t dismiss their questions.
Meeting these needs reduces the likelihood of protesting and creating conflict with family members.
“It highlights just how important well-designed explanations are,” she said. “We must go beyond a transparency checklist.”
]]>That support, however, begins to disappear in these restrictive cultures once women reach menopause, according to new research from Georgia Tech
Naveena Karusala, an assistant professor in Georgia Tech’s School of Interactive Computing, and master’s student Umme Ammara are working toward improving existing technologies and designing new ones for a demographic they believe has been neglected.
Karusala and Ammara co-authored a paper based on a study they conducted with women in urban Pakistan experiencing menopause.
“Women’s health is understudied in general, but menopause is more neglected than other women’s health issues,” Karusala said. “Our choice to focus on menopause is motivated by expanding how we holistically think about women’s well-being across their lifespan.”
Karusala and Ammara will present their paper in April at the 2026 ACM Conference on Human Factors in Computing Systems (CHI) in Barcelona.
Menopause is diagnosed after 12 consecutive months without a period, vaginal bleeding, or spotting. The transition to menopause, called perimenopause, usually happens over two to eight years.
Hormone changes may cause symptoms such as irregular periods, vaginal dryness, hot flashes, night sweats, trouble sleeping, mood swings, and brain fog.
These symptoms can be debilitating in some cases and affect daily life. However, Ammara said women are pressured to remain silent, maintain appearances, and regulate their emotions to meet social expectations.
“Understanding menopause is important because a woman would be experiencing all these symptoms, and people will not understand those as actual symptoms,” Ammara said. “There’s been resistance to the idea of the medicalization of menopause. People don’t view it as an illness, but as a life transition and something that happens naturally.”
The women interviewed by Karusala and Ammara either stayed at home full-time or were part of the workforce.
The researchers discovered that trusted family members might be the only sources women who stay at home and do not work turn to for disclosure.
“Women at home have the flexibility to take breaks or work at their own pace, so a lot of their experience is shaped by the emotional barriers they face,” Ammara said.
“That could come from their husbands and family members. Some are supportive and some are not. They might weaponize it and use that term against them, or they might dismiss what they’re going through.”
Ammara said it might be easier for women in the workforce to confide in their coworkers, but explaining to an employer that they need sick leave for menopause symptoms can be intimidating.
Even in online communities that have enabled women to anonymously share their health experiences, menopause is seldom discussed.
Karusala and Ammara argue in their paper that a public health approach could be the most effective way to spark conversation about menopause in a patriarchal culture in which technology use varies.
They said the challenge in implementing technologies geared toward menopause support is that the condition isn’t well understood in public. Improving maternal health, for example, is easier to promote within these societies because of the general understanding that motherhood is important.
“There must be an existing infrastructure to build on,” Karusala said. “For example, menstrual and maternal health are taught in schools and regularly discussed in primary care. Cultural and social meaning and importance are placed on motherhood.
“A lot of that doesn’t exist for menopause. Primary care doctors are unprepared to talk about menopause compared to other health issues.”
Ammara said that the most effective way for technologies to make an impact on women going through menopause is to directly address systemic power structures around women’s health within Pakistani culture.
It can start with the husbands.
“Framing the issue for husbands to understand menopause should be at the forefront of designing technology solutions,” she said.
“In Islamic contexts, we suggest using faith-based framings. This has been proposed for maternal health in prior works that draw on Islamic principles to engage expectant fathers in providing care and support. Framing it around religious responsibility to involve men in the journey can also be done for menopause.”
]]>“I was placing an order from a food truck outside the College building when a student approached and asked if I remembered him,” Briana Lampert said. “It was Hoc! It took me a few moments to realize.”
Years earlier, Lampert taught Hoc Nguyen and Cardin Ho in fourth-grade language arts and reading at Hambrick Elementary School in Stone Mountain, Georgia. Today, both are computer science (CS) majors at Georgia Tech.
Nguyen first recognized Lampert’s name while searching for his academic advisor during registration. “I thought her name was familiar, but only when I met her in person did I recall she was my teacher,” he said.
Although he doesn’t remember many details from elementary school, Lampert left a lasting impression. “I remember that she was a very kind teacher and that the class liked her because of how nice she was,” he said.
After their initial meeting, Nguyen shared that Ho was also a Georgia Tech student. Lampert later ran into both students on campus while attending an event, and the three spent nearly an hour catching up.
“They were both lovely and full of personality, just as they are now. I remember how sweet and intelligent they were,” Lampert said.
“They were very close, even then, and part of a crew that included a group of smart and talented kids. I knew they would go on to do great things, but I had no idea that any of us would end up at Tech.”
Ho also remembers Lampert’s approach in the classroom. “I remember Ms. Lampert had lots of patience,” he said. “Our class, me included, really tested her every day, yet she always maintained it to keep us on track.”
After teaching for five years, Lampert transitioned into academic advising. She started at Georgia State University in 2017 and moved to Georgia Tech in 2022. She said the move allowed her to focus on the part of education she enjoyed most.
“The part of the job that I loved the most was one-on-one interactions with students,” Lampert said. “With advising, I can provide the targeted support to students that I enjoy, but on a broad scale.”
In her current role, Lampert works closely with students as they navigate their academic journeys, while focusing on empathy and connection. She is especially passionate about supporting underrepresented student groups and helping students access campus resources.
Her experience as a teacher continues to shape her approach.
“It is important when working in higher education to remember that while Tech students are academically gifted, K-12 education does not teach a person how to ‘be a college student,’” she said. “Those skills are not inherent.”
For Nguyen, having a former teacher as an advisor has made a difference. He also enjoys reflecting on other classmates and teachers he keeps in touch with, who were part of his early academic journey.
“Having Ms. Lampert as an advisor is honestly quite nice,” he said. “It makes talking about your goals and classes a lot easier if your advisor is someone you knew from your childhood.”
Now studying CS, Nguyen discovered his interest in STEM in middle school, when he had more hands-on opportunities in science and technology.
For students considering the field, he recommends starting with personal interests.
“CS is such a broad field that there can be some parts you don’t find interesting and others you do,” he said. “By just starting with something you like, you can enjoy the learning process more and get the skills needed.”
For Lampert, the experience highlighted the lasting impact of education across different stages of students’ journeys.
“Hoc reminded me that, all things considered, there is a short span of time between elementary school and college,” she said. “He reaffirmed that educators are crucial at every stage of a student’s life.”
]]>Years earlier, Lampert taught Hoc Nguyen and Cardin Ho in fourth-grade language arts and reading at Hambrick Elementary School in Stone Mountain, Georgia. Today, both are computer science (CS) majors at Georgia Tech.
]]>The Georgia Scientific Computing Symposium (GSCS) held its annual meeting on February 21 in Athens. Since 2009, the event has hosted researchers from across the Peach State to showcase homegrown advances in scientific computing.
The symposium highlighted Georgia’s reputation as a computing innovation hub. People from around the world come to Georgia universities to lead computing research. By advancing science, engineering, medicine, and technology, their work improves communities at home and abroad.
Faculty and students from Georgia Tech, UGA, Georgia State University, and Emory University presented at the symposium. Georgia Tech participants came from the colleges of Computing, Engineering, and Sciences.
This year’s organizers agreed to meet in Atlanta for the 2027 symposium. Georgia Tech’s School of Computational Science and Engineering (CSE) will host the 19th GSCS.
“From healthcare to computer chip design, scientific computing underpins many of the technological advances we see in our lives,” said Professor Edmond Chow, associate chair of the School of CSE.
“Scientific computing provides the mathematical models, simulations, and data‑driven tools that make modern innovation possible. It allows people to analyze complex systems, test ideas virtually before building them, and make faster, more accurate decisions across nearly every sector of society.”
Professor Haomin Zhou and Assistant Professor Helen Xu delivered two of the symposium’s five plenary talks.
Zhou presented a new method for solving the Schrödinger equation, a landmark equation in quantum mechanics. Drawing inspiration from the mathematics used in generative artificial intelligence models, his approach develops an algorithm that more effectively simulates waves, particle motion, and other physical systems.
Xu focused on improving how computers move and organize data during complex calculations. Her work uses “cache-friendly” layouts that help computers access data more efficiently, boosting performance for scientific and engineering applications.
“Speaking at GSCS was a great opportunity,” Xu said. “The symposium fostered connections within the scientific computing community and gave us a chance to share exciting research.”
The symposium showcased student work through a poster blitz and a poster session. During the blitz, 36 students each had one minute to introduce their research to the full audience. They then shared more details about their research during the poster session.
The student projects showed the range of fields supported by scientific computing. The session also provided attendees with an opportunity to connect and expand their professional networks, helping grow the field’s future impact.
“As an aerospace engineer by training and aspiring computational scientist, GSCS gave me the platform to network with other researchers in the field while showcasing my own research,” said M.S. student Kashvi Mundra.
“I was able to connect with scientists across different disciplines whose work intersects with my own in unexpected ways. Those conversations pushed my thinking beyond my own lab's perspective, helping me see my work on physics-informed machine learning for inverse problems in a broader scientific computing context.”
Georgia Tech students who presented posters included:
Abir Haque (CSE), Massively Parallel Random Phase Approximation Correlation Energy via Lanczos Quadrature
Antonio Varagnolo (CSE), Physics-Enhanced Deep Surrogates for the Phonon Boltzmann Transport Equation
Ben Burns (CSE), Infinite-Dimensional Stein Variational Inference with Derivative-Informed Neural Operators
Ben Wilfong (CSE), Shocks without Shock Capturing; Compressible Flow at 1 quadrillion Degrees of Freedom without Loss of Accuracy
Daniel Vickers (CSE), Highly-Parallel Fluid-Solid Interactions for Compressible Flows
Eric Fowler (CSE), High-Performance Tensor Contractions in Computational Chemistry
Haoran Yan (Math), Understanding Denoising Autoencoders through the Manifold Hypothesis: A Geometric Perspective
Kashvi Mundra (CSE), Autoregressive Multifidelity Neural Surrogate Modeling under Scarce Data Regimes
Sebastián Gutiérrez Hernández (Math/CSE), PDPO: Parametric Density Path Optimization
Vivian Zhang (AE), Multifidelity Operator Inference: Non-Intrusive Reduced Order Modeling from Scarce Data
Xian Mae Hadia (CSE), Data Efficiency of Surrogate Models: Learning Physics Data from Full Field Data vs. Inductive Bias from Approximate PDE Solvers
Xiangming Huang (CSE), Neural Operator Accelerated Evolutionary Strategies for PDE-Constraint Optimization
Zhaiming Shen (Math), Understanding In-Context Learning on Structured Manifolds: Bridging Attention to Kernel Methods
Zhongjie Shi (Math), Towards Understanding Generalization in DP-GD: A Case Study in Training Two-Layer CNNs
]]>The Georgia Scientific Computing Symposium (GSCS) held its annual meeting on February 21 in Athens. Since 2009, the event has hosted researchers from across the Peach State to showcase homegrown advances in scientific computing.
The symposium highlighted Georgia’s reputation as a computing innovation hub. People from around the world come to Georgia universities to lead computing research. By advancing science, engineering, medicine, and technology, their work improves communities at home and abroad.
]]>New cybersecurity research from the Georgia Institute of Technology, however, revealed that crews aboard commercial vessels were often not adequately prepared to manage cyberattacks effectively due to systemic training gaps.
The findings are based on interviews conducted by researchers with more than 20 officer-level mariners to assess the maritime industry’s readiness to handle cybersecurity attacks at sea.
"Historically, cybersecurity research has focused heavily on cyber-physical systems like cars, factories, and industrial plants, but ships have largely been overlooked,” said Anna Raymaker, Ph.D. student and lead researcher.
“That gap is concerning when more than 90% of the world’s goods travel by sea. Recent incidents, from GPS spoofing to ships linked to subsea cable disruptions, show that maritime systems are increasingly part of the global cyber threat landscape.”
The researchers proposed four practical strategies to strengthen maritime cyber defenses and close the training gaps. Their findings were presented recently at the ACM SIGSAC Conference on Computer and Communications Security (CCS).
Many of those interviewed for the study described current cybersecurity training as “boilerplate” — generic modules that don’t reflect real shipboard risks.
Researchers recommend:
At sea, crews can’t simply escalate a cyber incident to a shore-based IT department and wait. Operational resilience requires onboard readiness.
Researchers recommend:
Related Article: When GPS lies at sea: How electronic warfare is threatening ships and their crews by Anna Raymaker
Maritime cybersecurity regulations are often reactive and fragmented. Researchers argue the industry needs a cohesive, domain-specific framework.
Key recommendations include:
Finally, the researchers stress that long-term resilience requires deeper technical research focused on maritime systems.
Priority areas include:
Cyber threats at sea are no longer hypothetical. Mariners report real-world incidents ranging from GPS spoofing to ransomware that disrupts global trade.
“Through our interviews with mariners, I saw firsthand how much dedication and pride they take in their work,” said Raymaker. “Our goal is for this research to serve as a call to action for researchers, policymakers, and industry to invest more attention in maritime cybersecurity and support the people who risk their lives every day to keep global trade, food, and energy moving."
A Sea of Cyber Threats: Maritime Cybersecurity from the Perspective of Mariners was presented at CCS 2025. It was written by Raymaker and her colleagues, Ph.D. students Akshaya Kumar, Miuyin Yong Wong, and Ryan Pickren; Research Scientist Animesh Chhotaray, Associate Professor Frank Li, Associate Professor Saman Zonouz, and Georgia Tech Provost and Executive Vice President for Academic Affairs Raheem Beyah.
]]>Communications Officer II School of Cybersecurity and Privacy
]]>Li, an accomplished computer security and privacy researcher, joined Georgia Tech in 2020 as the Institute was launching the School of Cybersecurity and Privacy (SCP). He holds a joint appointment with the School of Electrical and Computer Engineering (ECE).
“While tenure may be an individual's milestone, in reality, it reflects the help, support, and hard work of countless others,” Li said.
He credits his accomplishments to the ongoing mentorship and support he has received from faculty and staff at SCP, ECE, and Georgia Tech.
“I'm also extremely thankful to work with such amazing students at Georgia Tech, especially the Ph.D. students in my research lab, and the BS and MS students in my classes, who help our research efforts. Georgia Tech has been an amazing place to start my faculty career,” said Li.
Li advises five Ph.D. students at his Better Empirically Established Security (BEES) lab in SCP. They take a data-driven approach to understanding how security and privacy concerns manifest in practice, and use the insights gained to drive improvements in real-world security.
Their research examines how users, security operators, and attackers behave in various security and privacy-sensitive situations, often using internet-wide measurements, network traffic analysis, user studies and experiments, and large-scale data mining.
“The tenure and promotion to associate professor rank is in recognition of the outstanding research program Frank has developed at SCP,” said Mustaque Ahamad, interim chair and Regents’ Entrepreneur.
“He is an award-winning educator. We look forward to his continued leadership in the important areas of usable security and network security in the future.”
Li was among nine College of Computing faculty members who received promotion and tenure this year.
John P. Imlay Jr. Dean of Computing Vivek Sarkar emailed the College community with the good news.
“We are truly thrilled to celebrate this moment with you, as we recognize your contributions to our students and to the advancement of our College and Institute in so many ways,” he said.
In 2025, Li received the prestigious CAREER Award from the National Science Foundation (NSF). His CAREER project will investigate real-world uses of FIDO2/passkeys and address security and usability issues that can arise. A goal of his research is to identify and resolve problems before they become widespread and more difficult to solve.
]]>Communications Officer II School of Cybersecurity and Privacy
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