The competition to win one of four $150,000 startup investments began in February and ended in April when 17 teams pitched their startup concepts to judges at a live Demo Day event held on April 22.
“The Klaus Startup Challenge was a huge success, and we were thrilled with the level of participation and energy in the room,” said Tamar Wilkins, event organizer and GT Computing academic program manager.
She added that the event showcases the innovation and entrepreneurial spirit within the College of Computing community, and provides students with access to workshops, mentors, and networking opportunities with alumni, founders, and industry leaders.
“The startup challenge is designed to help students move beyond the classroom to begin building real-world solutions through customer discovery, mentorship, pitch development, and startup storytelling.”
From the arts to healthcare, this year’s startup challenge highlighted a range of innovative ideas and technologies from student founders. The winning teams were:
Each winning team received $150,000 in funding support from Fusen World, a platform founded in 2022 by Christopher Klaus, Fusen World CEO, GT alumnus, technology entrepreneur, and philanthropist. Fusen was launched to empower student founders worldwide to successfully launch and grow their startups.
Along with Klaus, the judges for this year’s startup challenge were:
To be eligible for the Klaus Startup Challenge, at least one co-founder for each team must be a current GT Computing student.
]]>Georgia Tech College of Computing
albert.snedeker@cc.gatech.edu
]]>The new technology is also set to revolutionize the scale of policy training data collection, which is essential to advancing robotic capabilities and meeting growing production demand.
COBALT is a mobile app that turns smartphones into controllers for robot arms. With a secure Wi-Fi connection to a server, users can move their phones in any direction, and the robot arm will mirror the motion — from anywhere in the world.
Ayush Agarwal, a Ph.D. student in Georgia Tech’s School of Interactive Computing who leads a research team developing COBALT, said it works like the games people play on smartphones. Users can press a button to have the arm grasp an object, move it, and release it with another button.
Agarwal conducted several user studies with participants in nine countries who remotely operated robot arms inside Georgia Tech’s People, AI & Robotics (PAIR) Lab. The lab is directed by Assistant Professor Animesh Garg, who advises Agarwal.
“We built an entire distribution system for remote teleoperation scaled to where we had people from Indonesia, India, and Pakistan operating for us,” Agarwal said. “They were novice operators who had never done it before. By collecting data from these new users, we showed that we can train policies to automate certain tasks.”
Garg envisions a world where data collection for policy training is done through crowdsourcing. He began working toward this goal 10 years ago as a postdoc at Stanford University, when he developed RoboTurk, an earlier version of COBALT.
“There is a large-scale data collection requirement for mass robot production to be possible, and it will not be solved purely through simulation,” Garg said.
“Our idea was, what if we could get almost every person on the planet to be a passive source for data collection? There are almost five billion people who have smartphones and know how to use them.”
Another major implication of COBALT could be expanded access to CS and robotics education.
Students can learn to operate a robot remotely in any classroom. In fact, Garg and his lab recently hosted students from Midtown High School in Atlanta to demonstrate COBALT and let them control robot arms from a phone.
Garg also sees the possibility of a “gig economy” in which people pay remote operators to control assistive robots in their homes and complete household chores for them.
“It could be Uber for robots,” he said. “People who want to log onto the platform can do so at their convenience and for as long as they want.”
Companies with robot-dependent labor tasks could also use the platform to enable human oversight.
“If I deploy a robot in a factory that achieves high autonomy for most tasks, but there are still times it needs help, a human could operate the robot from anywhere in the world,” Garg said.
Agarwal’s studies showed that people prefer to interact with and control a robot using a smartphone rather than virtual reality (VR) headsets, controllers, keyboards, mice, or other devices.
“The phone is a more intuitive interface and can provide data quality that’s on par with other commonly used devices,” he said.
Agarwal also said there is minimal latency in the video feed sent back to operators on the other side of the world. That’s because the amount of data being processed is small.
The data is carried over Web Real-Time Communication (WebRTC), the same technology used by many streaming services and web conferencing platforms such as Zoom and Google Meet.
“There’s a connection from your phone to the teleoperation server, which is connected to the robots,” Agarwal said.
“Then there’s another connection from the teleoperation server back to the user, which allows for a video stream. We need low latency on both because you don’t want the user to move their phone and wait 10 seconds to see the visual feed.”
Agarwal is the co-lead author of a paper on COBALT that is being presented at the IEEE International Conference on Robotics and Automation this week in Vienna. He said the paper stands out because it has moved from theory to the implementation of an entire distribution network.
“The real novelty of our paper is the systems that we build around it to actually support the scaling of remote operation and data collection at a global level,” he said.
]]>Georgia Tech’s competitive programming team placed seventh at the International Collegiate Programming Contest (ICPC) North America Championship (NAC), earning a bronze medal and further cementing its standing among the continent’s elite collegiate teams.
The NAC is the highest level of regional competition in the ICPC.
For the team, the achievement was the product of months of deliberate preparation and a carefully balanced roster.
“We’ve been practicing consistently since September,” said Kevin Shan, a third-year computer science (CS) student and three-year team member. “As a result, we’ve developed pretty strong team chemistry as well as a good understanding of what each person’s strengths are.”
That chemistry proved critical in a contest format that demands technical mastery and coordination under pressure. ICPC competitions require teams to collaboratively solve complex algorithmic problems within a fixed time limit, often forcing quick decisions about strategy, debugging, and division of labor.
The team reflects a blend of experience across multiple levels of competitive programming. Shan earned his second NAC medal this year, while first-year CS student Zachary Chao entered with adistinguished background, including a bronze medal at the International Olympiad in Informatics (IOI) representing Taiwan. Zejia Chen, a PhD student, added further depth as a former ICPC World Finals competitor.
Despite differences in format, Chao said the transition from individual to team competition was natural.
“Although IOI and ICPC have very different contest formats, the skills required to excel in both competitions are very similar,” he said. “I had to adapt to the team environment, but in terms of problem solving, my experience definitely translated.”
He also emphasized that success in competitive programming is less about seniority and more about skill and practice.
“I feel like grade level isn’t too relevant to ICPC,” he said. “As long as a contestant is able to compete at a certain level, it doesn’t really matter what grade they are.”
For Shan, competing at multiple levels over three years has sharpened his understanding of how each stage differs. “The contests at different levels—regionals, NAC, and World Finals—all have unique characteristics,” he said. “It’s important not only to practice on different sets for these contests but also to approach them differently.”
The emotional turning point came at the very end of the competition. After struggling to debug the final solution, the team members were unsure of how they had performed. “We were all pretty bummed,” Shan said. “So the best part was definitely finding out at the award ceremony that we were awarded a medal.”
Beyond the results, Georgia Tech’s reputation was evident throughout the competition. According to School of Computing Instruction faculty member and ICPC advisor Abrahim Ladha, competitors from other universities recognized the team.
“Walking around with them, they were treated like celebrities. Competitors from other schools knew of them, the way people talk about Haynes King or something,” Ladha said.
“Getting a bronze at NAC is a huge deal, and they all will have jobs lined up because of this.”
Chen, who has competed internationally, noted that the NAC stands out not just for its difficulty but also for the broader experience it offers. Compared to the competitions he attended during his undergraduate years, he described NAC as “much richer and more engaging,” with opportunities to connect with peers, attend talks, and explore career pathways alongside the contest.
At the same time, the team remains focused on continued growth. “Winning a bronze medal gives us encouragement,” Chen said, noting that the experience will help guide their preparation for future competitions.
Georgia Tech’s competitive programming team placed seventh at the International Collegiate Programming Contest (ICPC) North America Championship (NAC), earning a bronze medal and further cementing its standing among the continent’s elite collegiate teams.
]]>Fiona Ryan, a Ph.D. student in Georgia Tech’s School of Interactive Computing, is pioneering research that tracks and predicts user gaze from a first-person perspective in 3D environments.
Currently, most AR devices react to where users look, playing catch-up. Ryan’s method could give these devices a heads-up and make the user experience more seamless.
“It allows an AR system to anticipate what the person will interact with next and where they’re going to look next so it can proactively render the experience,” she said.
Ryan is the lead author of the paper Forecasting 3D Scanpaths in Egocentric Video, which she will present next week at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) in Denver.
While there is existing research on predicting user gaze from 2D still images, her work is the first to address the issue through a 3D framework.
“Because we live in a 3D world and people are dynamically moving around from multiple points of view, we need to predict gaze in 3D rather than 2D,” she said. “What we’re seeing is a path of the person’s attention in 3D through space. Our paper is the first to attempt to model this.”
Ryan conducted most of the research while interning at Meta, where she used data from Meta’s Aria Digital Twin dataset. The dataset contains first-person video footage of users interacting with objects in an apartment.
“We chose that dataset because it has a high-fidelity 3D reconstruction of a full environment, which helps us get a ground-truth 3D gaze,” she said. “We can trace eye movement and see how it intersects with the environment.”
A video demonstration of Ryan’s work shows her software tracking a user’s path toward a table with a cup on it. Once the user picks up the cup, the software correctly predicts the direction the user will turn next.
“When we look at a scene, we don’t take in everything in full detail all at once,” she said. “We fixate on certain areas, and our gaze is a sequence of fixations, which might depend on what we’re trying to do. If we want to pick up a cup, we might look toward that and then the next step would be looking at where we’re going to put it down.”
Ryan said the software can predict, on average, up to three seconds into the future — and as far as 10 seconds in some cases. That’s enough time for the AR system to proactively render a more enhanced environment.
“We’re not looking that far into the future right now, but it would be interesting to explore longer forecasting windows,” she said. “I think potential futures would diverge pretty quickly, so we’re trying to explore what can reasonably be predicted from a short segment of a person looking and moving through space.”
Ryan said her paper served as a proof-of-concept, and that there is still much future work to be done. She already has some ideas.
“I think future models can include different scenarios to help narrow down possibilities. Sometimes a person’s gaze stays on one thing for a long time. If we know what someone is trying to do, we’ll have a better idea of the likely path their attention might go.”
There could also be future implications for her work in robotics research.
“It could potentially be used for training algorithms for robots to emulate active human perception. If we can understand what a person looks at as they perform a task, we could use that to facilitate a robot learning to do that same task.”
]]>Fiona Ryan, a Ph.D. student in Georgia Tech’s School of Interactive Computing, is pioneering research that tracks and predicts user gaze from a first-person perspective in 3D environments.
Currently, most AR devices react to where users look, playing catch-up. Ryan’s method could give these devices a heads-up and make the user experience more seamless.
“It allows an AR system to anticipate what the person will interact with next and where they’re going to look next so it can proactively render the experience,” she said.
Ryan is the lead author of the paper Forecasting 3D Scanpaths in Egocentric Video, which she will present next week at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) in Denver.
While there is existing research on predicting user gaze from 2D still images, her work is the first to address the issue through a 3D framework.
“Because we live in a 3D world and people are dynamically moving around from multiple points of view, we need to predict gaze in 3D rather than 2D,” she said. “What we’re seeing is a path of the person’s attention in 3D through space. Our paper is the first to attempt to model this.”
Ryan conducted most of the research while interning at Meta, where she used data from Meta’s Aria Digital Twin dataset. The dataset contains first-person video footage of users interacting with objects in an apartment.
“We chose that dataset because it has a high-fidelity 3D reconstruction of a full environment, which helps us get a ground-truth 3D gaze,” she said. “We can trace eye movement and see how it intersects with the environment.”
A video demonstration of Ryan’s work shows her software tracking a user’s path toward a table with a cup on it. Once the user picks up the cup, the software correctly predicts the direction the user will turn next.
“When we look at a scene, we don’t take in everything in full detail all at once,” she said. “We fixate on certain areas, and our gaze is a sequence of fixations, which might depend on what we’re trying to do. If we want to pick up a cup, we might look toward that and then the next step would be looking at where we’re going to put it down.”
Ryan said the software can predict, on average, up to three seconds into the future — and as far as 10 seconds in some cases. That’s enough time for the AR system to proactively render a more enhanced environment.
“We’re not looking that far into the future right now, but it would be interesting to explore longer forecasting windows,” she said. “I think potential futures would diverge pretty quickly, so we’re trying to explore what can reasonably be predicted from a short segment of a person looking and moving through space.”
Ryan said her paper served as a proof-of-concept, and that there is still much future work to be done. She already has some ideas.
“I think future models can include different scenarios to help narrow down possibilities. Sometimes a person’s gaze stays on one thing for a long time. If we know what someone is trying to do, we’ll have a better idea of the likely path their attention might go.”
There could also be future implications for her work in robotics research.
“It could potentially be used for training algorithms for robots to emulate active human perception. If we can understand what a person looks at as they perform a task, we could use that to facilitate a robot learning to do that same task.”
]]>The research also reveals that most websites that require age verification don’t enforce the policy.
The findings come from a new paper that researchers from the Georgia Institute of Technology and the University of California, Irvine (UC Irvine) will present at this week’s IEEE Symposium on Security and Privacy conference in San Francisco.
The research team examined Yoti, a London-based company that provides age-verification services for an estimated 60% of websites that require it. Its client list includes Meta, OnlyFans, Sony PlayStation, and TikTok.
The research team determined that the process Yoti uses to verify a person’s age broadcasts the person’s personal information to third- and fourth-party companies.
When a bartender checks an ID, they quickly verify a customer’s date of birth and identity before serving them. Companies like Yoti that employ digital age verification claim their products function the same way, but in a completely private manner.
That analogy has justified laws passed in 25 U.S. states — comprising more than 40% of Americans — mandating the use of digital age verification to gate access to social media and adult online content.
However, by measuring online age verification, researchers reveal that the reality of these systems is far from ideal. The study found that most sites covered by these laws do not appear to enforce age verification.
When sites comply, they force users to use third-party age-verification services like Yoti, which collect and share highly sensitive data with other third parties.
“There have been laws passed and court cases settled on the promise that these companies are incentivized to keep users’ data private” said Assistant Professor Michael A. Specter at the School of Cybersecurity and Privacy. “We found that reality is starkly different.”
Digital age verification laws are being considered by other legislative bodies to bar minors from social media sites. The problem, Specter and his colleagues argue, is that current methods of age verification are ineffective and create new privacy risks.
“In legal arguments, there have been comparisons to these services acting like a bartender checking IDs,” said Specter. “However, what is really happening is the bartender is making photocopies of the patron’s license and sending it to their food vendors.”
According to the researchers, the data is then sent to credit card companies, IP geolocation services, and data brokers. The researchers found that the information being shared can be used to identify and track devices. For example, a single verification attempt may transmit a user’s facial image, IP address, and device fingerprint to credit card companies.
Aside from privacy concerns, researchers note that differing state policies could lead to what they call the Balkanization of the U.S. web. In other words, users may have access to different parts of the internet depending on the state they are in. This will potentially limit the free exchange of ideas and information.
According to Assistant Professor Harry Oppenheimer of the Jimmy and Rosalynn Carter School of Public Policy, users are already accustomed to experiencing the internet differently across countries. However, this may signal the beginning of similar fragmentation within the United States.
“We are going to start seeing comparable differences between U.S. states,” said Oppenheimer. “Users in some states will now have to go through additional steps to access information. Close your laptop in New York before a flight to Dallas and try to load the same web page—now you see two different results.”
“We also observed age verification deployed on websites accessed from New York, which has no law requiring verification,” said Associate Professor Paul Pearce of UC Irvine’s Department of Computer Science.
“We don’t know why these sites are deploying such verification—it could be a move to limit liability or simplify operations. Regardless, it points to an emerging threat for the open Internet where restrictive laws from some states could impact the entire country and beyond.”
“This is why we can’t have nice things,” Specter added.
The study, Papers Please: A First Look at Age Verification on the Web, was led by Georgia Tech Ph.D. student Shreyas Minocha, undergraduate Isaac Sheridan, and Oppenheimer, Pearce, and Specter. It is part of the proceedings of the 47th IEEE Symposium on Security and Privacy and will be presented in San Francisco on May 20, and was featured in Arstechnica.
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The research also reveals that most websites that require age verification don’t enforce the policy.
]]>Communications Officer II at the School of Cybersecurity and Privacy
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