A new robot could solve one of the biggest challenges facing indoor farmers: manual pollination.

Indoor farms, also known as vertical farms, are popular among agricultural researchers and are expanding across the agricultural industry. Some benefits they have over outdoor farms include:

• Year-round production of food crops
• Less water and land requirements
• Not needing pesticides
• Reducing carbon emissions from shipping
• Reducing food waste

Additionally, some studies indicate that indoor farms produce more nutritious food for urban communities. 

However, these farms are often inaccessible to birds, bees, and other natural pollinators, leaving the pollination process to humans. The tedious process must be completed by hand for each flower to ensure the indoor crop flourishes.

Ai-Ping Hu, a principal research engineer at the Georgia Tech Research Institute (GTRI), has spent years exploring methods to efficiently pollinate flowering plants and food crops in indoor farms to find a way to efficiently pollinate flower plants and food crops in indoor farms.

Hu, Assistant Professor Shreyas Kousik of the George W. Woodruff School of Mechanical Engineering, and a rotating group of student interns have developed a robot prototype that may be up to the task.

The robot can efficiently pollinate plants that have both male and female reproductive parts. These plants only require pollen to be transferred from one part to the other rather than externally from another flower.

Natural pollinators perform this task outdoors, but Hu said indoor farmers often use a paintbrush or electric tootbrush to ensure these flowers are pollinated. 

Knowing the Pose

An early challenge the research team addressed was teaching the robot to identify the “pose” of each flower. Pose refers to a flower’s orientation, shape, and symmetry. Knowing these details ensures precise delivery of the pollen to maximize reproductive success. 

“It’s crucial to know exactly which way the flowers are facing,” Hu said.

“You want to approach the flower from the front because that’s where all the biological structures are. Knowing the pose tells you where the stem is. Our device grasps the stem and shakes it to dislodge the pollen.

“Every flower is going to have its own pose, and you need to know what that is within at least 10 degrees.”

Computer Vision Breakthrough

Harsh Muriki is a robotics master’s student at Georgia Tech’s School of Interactive Computing, who used computer vision to solve the pose problem while interning for Hu and GTRI.

Muriki attached a camera to a FarmBot to capture images of strawberry plants from dozens of angles in a small garden in front of Georgia Tech’s Food Processing Technology Building. The FarmBot is an XYZ-axis robot that waters and sprays pesticides on outdoor gardens, though it is not capable of pollination.

“We reconstruct the images of the flower into a 3D model and use a technique that converts the 3D model into multiple 2D images with depth information,” Muriki said. “This enables us to send them to object detectors.”

Muriki said he used a real-time object detection system called YOLO (You Only Look Once) to classify objects. YOLO is known for identifying and classifying objects in a single pass.

Ved Sengupta, a computer engineering major who interned with Muriki, fine-tuned the algorithms that converted 3D images into 2D.

“This was a crucial part of making robot pollination possible,” Sengupta said. “There is a big gap between 3D and 2D image processing.

“There’s not a lot of data on the internet for 3D object detection, but there’s a ton for 2D. We were able to get great results from the converted images, and I think any sector of technology can take advantage of that.”

Sengupta, Muriki, and Hu co-authored a paper about their work that was accepted to the 2025 International Conference on Robotics and Automation (ICRA) in Atlanta.

Measuring Success

The pollination robot, built in Kousik’s Safe Robotics Lab, is now in the prototype phase. 

Hu said the robot can do more than pollinate. It can also analyze each flower to determine how well it was pollinated and whether the chances for reproduction are high.

“It has an additional capability of microscopic inspection,” Hu said. “It’s the first device we know of that provides visual feedback on how well a flower was pollinated.”

For more information about the robot, visit the Safe Robotics Lab project page.

News Contact

ATLANTA — Georgia Tech Arts has announced the recipients of its Spring 2026 Microgrants, supporting student-led, cross-disciplinary artistic projects that enliven Georgia Tech’s campus with creativity.

These grants of up to $1,000 provide undergraduate and graduate students, as well as postdoctoral researchers, support for individual and collaborative projects. All six colleges with on-campus students are represented among the primary proposers, with collaborators ranging from registered student organizations and faculty mentors to Atlanta-based artists.

College of Design

Anthony Cammarota, a musician and Ph.D. candidate in music technology (School of Music), received funding for Guitar Picking Device: Technique as Embodiment of Performance Practice. The project designs a musician-focused guitar performance technology to improve technique through techno-mediated learning, reducing physical strain and inefficient gestural habits.

Rafael Collado, a graduate student in music technology (School of Music), received funding for Bravo, Director. This staged one-man musical showcase uses generative AI to satirically comment on the role of AI in music creation and contemporary creative expression. The performance will take place April 20 in the Black Box Theatre.

Aleksandra Ma, a graduate student in music technology (School of Music), in collaboration with Anthony Cammarota and Jeff Albert, received funding for Human to Human Jazz Improv. The project explores how musicians communicate during improvisation and how those insights can inform new forms of artistic collaboration between human performers and AI.

TeAiris Majors, a Ph.D. candidate in music technology (School of Music), in collaboration with Thais Alvarenga, will create Just Chill, a portable interactive installation inviting students to explore emotional well-being through sound and visual design.

John Parrack, a third-year architecture student (School of Architecture), in collaboration with Molly Pentecost and Nour Khalifa, received funding to support Sandbox, an emerging student-run publication. Exhibitions are scheduled for late April and early May.

Ryan Yin, a third-year architecture student (School of Architecture), will produce two installations: What Makes Something Home and Informality, both designed for high-traffic campus spaces to encourage interaction and reflection on housing disparity and community-driven architecture.

Peyman Salimi, a graduate student in music technology (School of Music), will present Self + Apolide: A Multilingual Spatial Audio Performance, an immersive show using a 12-speaker ambisonics setup.

Ivan Allen College of Liberal Arts

Inha Cha, a Ph.D. candidate in digital media (School of Literature, Media, and Communication), will lead AI-Non Use Tool Kit, a tangible resource for creative professionals exploring the social and ethical implications of AI usage and non-usage.

Chelsi Cocking, a Ph.D. candidate in digital media (School of Literature, Media, and Communication), in collaboration with Raianna Brown, Ta Nycia Wooden and Okorie Johnson, will create Everything Sings, an audio-reactive sculpture visualizing ambient vibrations in performance space.

Olamma Oparah, a Ph.D. candidate in digital media (School of Literature, Media, and Communication), received support for Anyanwu Patterns. The film and textile installation adapts Octavia E. Butler’s Wild Seed and will be showcased at the Butler Symposium at Atlanta Contemporary on Feb. 26.

Allie Riggs, a Ph.D. candidate in digital media (School of Literature, Media, and Communication), in collaboration with Shelly Boehm, received funding for Lichen Meditations: Materializing Queer Entanglements in Sonic Environments. Riggs will present the work at the Atlanta Science Festival on March 14 and Georgia Tech’s Digital Media Demo Day.

Cecile Zhang, a Ph.D. candidate in digital media (School of Literature, Media, and Communication), leads Feminist Mixed Media Photography: Counter Archive x Algorithm, examining the patriarchal history of photography and how emerging technologies can challenge established norms.

College of Computing

Sylvia Janicki, a postdoctoral researcher in interactive computing, will produce Rest Against the Machine, a sonic-textile installation examining AI data centers through a critical disability lens. The work will be featured June 5 and 6 at the Atlanta Public Art Futures Lab.

Catherine Wieczorek-Berkes, a Ph.D. candidate in human-centered computing, leads Materializing Critical Temporalities, which will be presented at the SPARK Lab in TSRB in April.

Ethan Zhao, a graduate student in human-computer interaction, in collaboration with Allen Cai and Emily Zhou, received funding for Sustainability in the DIY Music Community, a community-engaged research initiative supporting Atlanta’s DIY music spaces.

College of Sciences

Ryan Clark, a third-year neuroscience student, received support for Collective Effervescence, an interactive light installation using DMX and motion capture equipment. Clark plans to showcase the work at the Atlanta Science Festival and ImmerseGT.

Scheller College of Business

Srihitha Joginapally, a third-year business administration student, received support for GT AfroDance’s Unity Dey. The grant will fund materials for a tie-dye workshop allowing dancers to design their own costumes.

College of Engineering

Lukas Kassatly, a mechanical engineering student and vice president of DramaTech Theatre (School of Mechanical Engineering), will use funds to support DramaTech’s production of Everybody by Branden Jacobs-Jenkins. The performance runs Feb. 20–28 in the Black Box Theatre.

Alexandra Wnuk, a Ph.D. candidate in materials science and engineering (School of Materials Science and Engineering), in collaboration with Ashley Burton and Lucia Lammers, received support for the Textiles Team’s Fashion of the Future on April 17 in the Marcus Nanotechnology Building.

Naugle Writing and Communication Center

Jenessa Kenway, a Marion L. Brittain Postdoctoral Teaching Fellow, in collaboration with Jacqueline Kari, will lead Tender Buttons, Moving Pictures, a course integrating modernism, visual literacy and experimental filmmaking.

For more information about these programs, contact Kailey Albus, student support specialist for Georgia Tech Arts.

News Contact

The future of clean energy depends on algorithms as much as it does atoms.

Georgia Tech’s Qi Tang is building machine learning (ML) models to accelerate nuclear fusion research, making it more affordable and more accurate. Backed by a grant from the U.S. Department of Energy (DOE), Tang’s work brings clean, sustainable energy closer to reality.

Tang has received an Early Career Research Program (ECRP) award from the DOE Office of Science. The grant supports Tang with $875,000 disbursed over five years to craft ML and data processing tools that help scientists analyze massive datasets from nuclear experiments and simulations.

Tang is the first faculty member from Georgia Tech’s College of Computing and School of Computational Science and Engineering (CSE) to receive the ECRP. He is the seventh Georgia Tech researcher to earn the award and the only GT awardee among this year’s 99 recipients.

More than a milestone, the award reflects a shift in how nuclear research is done. Today, progress depends on computing and data science as much as on physics and engineering.

“I am honored and excited to receive the ECRP award through DOE’s Advanced Scientific Computing Research program, an organization I care about deeply,” said Tang, an assistant professor in the School of CSE. 

“I am grateful to my former colleagues at Los Alamos National Laboratory and collaborators at other national laboratories, including Lawrence Livermore, Sandia, and Argonne. I am also thankful for my Ph.D. students at Georgia Tech, whose dedication and creativity make this award possible.”

[Related: New Faculty Applies High-Performance Computing, Scientific Machine Learning Interests to Studies in Plasma Physics]

A problem in nuclear research is that fusion simulations are challenging to understand and use. These simulations generate enormous datasets that are too large to store, move, and analyze efficiently.

In his ECRP proposal to DOE, Tang introduced new ML methods to improve the analysis and storage of particle data.

Tang’s approach balances shrinking data so it is easier to store and transfer while preserving the most important scientific features. His multiscale ML models are informed by physics, so the reduced data still reflects how fusion systems really behave.

With Tang’s research, scientists can run larger, more realistic fusion models and analyze results more quickly. This accelerates progress toward practical fusion energy.

“In contrast to generic black-box-type compression tools, we aim at preserving the intrinsic structures of the particle dataset during the data reduction processes,” Tang said. 

“Taking this approach, we can meet our goal of achieving high-fidelity preservation of critical physics with minimum loss of information.”

Computing is essential in modern research because of the amount of data produced and captured from experiments and simulations. In the era of exascale supercomputers, data movement is a greater bottleneck than actual computation.

DOE operates three of the world’s four exascale supercomputers. These machines can calculate one quintillion (a billion billion) operations per second.

The exascale era began in 2022 with the launch of Frontier at Oak Ridge National Laboratory. Aurora followed in 2023 at Argonne National Laboratory. El Capitan arrived in 2024 at Lawrence Livermore National Laboratory.

With Tang’s data reduction approaches, all of DOE’s supercomputers spend more time on science and less time waiting for data transfers.

“Qi’s work in computational plasma physics and nuclear fusion modeling has been groundbreaking,” said Haesun Park, Regents’ Professor and Chair of the School of CSE. 

“We are proud of Qi and what this award means for him, Georgia Tech, and the Department of Energy toward leveraging computation to solve challenges in science and engineering, such as sustainable energy."

Previous Georgia Tech recipients of DOE Early Career Research Program awards include:

Itamar Kimchi, assistant professor, School of Physics

Sourabh Saha, assistant professor, George W. Woodruff School of Mechanical Engineering

Wenjing Lao, associate professor, School of Mathematics

Ryan Lively, Thomas C. DeLoach Professor, School of Chemical & Biomolecular Engineering

Josh Kacher, associate professor, School of Materials Science and Engineering

Devesh Ranjan, Eugene C. Gwaltney Jr. School Chair and professor, Woodruff School of Mechanical Engineering

News Contact

The College of Computing is forging new relationships with Atlanta’s venture capital community to advance entrepreneurial opportunities for students.

Nearly two dozen venture capital (VC) leaders based in Atlanta and the Southeast participated in a half-day summit at the College on Jan. 21.

Co-hosts Dean of Computing Vivek Sarkar and Noro-Moseley Partners General Partner Alan Taetle organized the invitation-only summit. Their goals were to:

• Showcase the College’s research strengths and entrepreneurial culture
• Deepen connections between academic innovation and startups
• Explore opportunities for collaboration, commercialization, and startup growth

The summit’s guest list included founders, partners, and leaders from VC firms. Many of these firms focus on early-stage startups in SaaS, fintech, cybersecurity, and other emerging technology markets.

Research With Commercial Impact

Sarkar outlined the College of Computing’s academic mission and research priorities during his opening remarks. He emphasized the College’s role in advancing innovation in cybersecurity, artificial intelligence (AI), and other emerging research areas.

“One of the College’s strategic pillars is what I call ‘X to the power of Computing’,” Sarkar said. “Look at any discipline or industry X to see where they're innovating and where their advances are being made, and that’s where Computing meets that discipline.”

Along with remarks from the dean, the summit featured presentations highlighting Georgia Tech’s entrepreneurial ecosystem and College-led research initiatives with strong commercialization potential.

Expanding Support for Student Founders

Jen Whitlow leads Community Partnerships at Fusen, a global platform for student founders created by Atlanta philanthropist Christopher W. Klaus. She described Klaus’s support for student entrepreneurship, including GT Computing’s annual Klaus Startup Challenge. In 2025, Klaus awarded five winning teams $150,000 each to cover startup costs.

Whitlow also updated guests on Klaus’s commitment, announced in May 2025, to covering the incorporation costs for any graduating student who aspires to launch a startup.

“More than 600 graduates from last year’s Spring and Fall Commencements have accepted the gift, and more than 225 recent graduates have completed their incorporation to date,” Whitlow said. She added that a second cohort of Fall 2025 graduates is being processed over the next few weeks.

Offering an enterprise-level view, CREATE-X Rahul Saxena presented recent updates to commercialization at Georgia Tech and efforts to streamline entrepreneurial processes.

Saxena emphasized the launch of Velocity Startups, an accelerator that provides the resources and infrastructure student startups need to bring their innovations to market.

Building the Pipeline From Research to Startup

Following these updates, GT Computing faculty delivered lightning-round presentations highlighting the College’s research strengths in AI, cybersecurity, and high-performance computing.

“The tighter the local investing community is with Georgia Tech, the better off both are,” said Taetle, who has been a member of the College’s Advisory Board for more than 20 years.

“It’s critical in this super-competitive world that we do everything that we can to support this fantastic university.”

Taetle added that the summit was part of a broader effort to strengthen the College’s entrepreneurial pipeline.

“There are some really big ideas here, which could turn into really big companies,” he said. “We’ve made some great strides on the commercialization front, but we still have that opportunity and challenge in front of us.”

The afternoon concluded with a discussion of next steps and engagement opportunities, led by Sarkar and Jason Zwang, GT Computing’s senior director of development. The discussion focused on research partnership opportunities, startup formation, and student involvement.

Zwang emphasized the importance of investing in Atlanta’s innovation ecosystem, citing the city’s strong fundamentals and pro-growth climate for entrepreneurship.

“This gives us a unique opportunity to start working more closely with the local VC community, and it’s also great for our students,” Zwang said.

Sarkar agreed, saying, “There’s no downside for students to get involved in a startup. It might take off and be a bonanza. If not, the experience makes you a more competitive hire because of the breadth of experience you gain at a startup.”

To foster these opportunities for students, Zwang said that a key priority is to establish earlier, more intentional connections among students, startups, and investors.

“This is a pivotal moment,” he said. “We can determine how to connect students with the VC and startup community earlier and ensure these investors remain involved with the College.”

College leaders said the summit underscored Computing’s commitment to fostering an entrepreneurial culture and to building lasting relationships that can help accelerate the real-world impact of its research beyond the Institute.

“Georgia Tech is a force multiplier for entrepreneurship,” said Sarkar. “We’re here to change the world. We want to inspire a culture of bold, big entrepreneurial thinking, and look forward to the next steps that will follow this VC summit.”

News Contact

While not as highlight-reel worthy as the Winter Olympics and the World Cup, experts expect high-performance computing (HPC) to have an even bigger impact on daily life in 2026.

Georgia Tech researchers say HPC and artificial intelligence (AI) advances this year are poised to improve how people power their homes, design safer buildings, and travel through cities.

According to Qi Tang, scientists will take progressive steps toward cleaner, sustainable energy through nuclear fusion in 2026. 

“I am very hopeful about the role of advanced computing and AI in making fusion a clean energy source,” said Tang, an assistant professor in the School of Computational Science and Engineering (CSE). 

“Fusion systems involve many interconnected processes happening across different scales. Modern simulations, combined with data-driven methods, allow us to bring these pieces together into a unified picture.”

Tang’s research connects HPC and machine learning with fusion energy and plasma physics. This year, Tang is continuing work on large-scale nuclear fusion models.

Only a few experimental fusion reactors exist worldwide compared to more than 400 nuclear fission reactors. Tang’s work supports a broader effort to turn fusion from a promising idea into a practical energy source.

Nuclear fusion occurs in plasma, the fourth state of matter, where gas is heated to millions of degrees. In this extreme state, electrons are stripped from atoms, creating a hot soup of fast-moving ions and free electrons. In plasma, hydrogen atoms overcome their natural electrical repulsion, collide, and fuse together. This releases energy that can power cities and homes.

Computers interpret extreme temperatures, densities, pressures, and plasma particle motion as massive datasets. Tang works to assimilate these data types from computer models and real-world experiments.

To do this, he and other researchers rely on machine learning approaches to analyze data across models and experiments more quickly and to produce more accurate predictions. Over time, this will allow scientists to test and improve fusion reactor designs toward commercial use. 

Beyond energy and nuclear engineering, Umar Khayaz sees broader impacts for HPC in 2026.

“HPC is the need of the day in every field of engineering sciences, physics, biology, and economics,” said Khayaz, a CSE Ph.D. student in the School of Civil and Environmental Engineering. 

“HPC is important enough to say that we need to employ resources to also solve social problems.”

Khayaz studies dynamic fracture and phase-field modeling. These areas explore how materials break under sudden, rapid loads. 

Like nuclear fusion, Khayaz says dynamic fracture problems are complex and data-intensive. In 2026, he expects to see more computing resources and computational capabilities devoted to understanding these problems and other emerging civil engineering challenges.

CSE Ph.D. student Yiqiao (Ahren) Jin sees a similar relationship between infrastructure and self-driving vehicles. He believes AI will innovate this area in 2026.

At Georgia Tech, Jin develops efficient multimodal AI systems. An autonomous vehicle is a multimodal system that uses camera video, laser sensors, language instructions, and other inputs to navigate city streets under changing scenarios like traffic and weather patterns.

Jin says multimodal research will move beyond performance benchmarks this year. This shift will lead to computer systems that can reason despite uncertainty and explain their decisions. In result, engineers will redefine how they evaluate and deploy autonomous systems in safety-critical settings.

“Many foundational problems in perception, multimodal reasoning, and agent coordination are being actively addressed in 2026. These advances enable a transition from isolated autonomous systems to safer, coordinated autonomous vehicle fleets,” Jin said. 

“As these systems scale, they have the potential to fundamentally improve transportation safety and efficiency.”

News Contact

An AI-powered tool is changing how researchers study disasters and how students learn from them. 

In the International Disaster Reconnaissance (IDR) course, students now use Filio, a platform built by School of Computing Instruction Senior Lecturer Max Mahdi Roozbahani, to capture immersive 360° media, photos, and video that transform real disaster sites in India and Nepal into living digital classrooms. 

Offered by the School of Civil and Environmental Engineering and taught by IDR director and Regents’ Professor David Frost, the course pairs traditional fieldwork with Roozbahani’s expertise in immersive technology and data-driven learning, transforming on-the-ground observations into reusable, interactive educational resources. 

How Computing Can Capture Data 

Disasters are not only physical events; they are also information events, Roozbahani says. Effective response and long-term resilience depend on the ability to observe, record, and communicate critical data under pressure. Georgia Tech’s IDR course pairs structured on-campus preparation with international field experiences, enabling students to study the cascading effects of major disasters, including how local building practices, governance, and culture shape damage and recovery. 

“When students step into a disaster zone, they learn quickly that resilience is a systems problem: physical, social, and informational. Our job in computing is to help them capture and reason about that system responsibly,” Roozbahani said. 

Learning from the 2025 Himalayas Expedition 

During spring break last year, the cohort traveled along the Teesta River corridor in Sikkim, India. The region is shaped by steep terrain, fast-moving water, and critical infrastructure in narrow valleys. 

The visit followed the October 2023 glacial lake outburst flood from South Lhonak Lake, which destroyed the Teesta III hydropower dam and impacted downstream towns, including Dikchu and Rangpo. Field stops across India included Lachung, Chungthang, Dikchu, Rangpo, Gangtok, and New Delhi. 

Students explored both upstream and downstream consequences. 

Upstream, the team examined how steep terrain and river confinement amplify flood forces, creating cascading risks for infrastructure. Using Filio’s interactive 360° media, students captured conditions in Lachung and Chungthang, allowing viewers to explore the landscape through a 360° photo and 360° video that reveal how topography and river dynamics intensify disaster impacts. 

They studied community-scale effects downstream, including damaged buildings, disrupted access, and prolonged recovery timelines. 

Rangpo offered a glimpse of recovery in motion, with materials staged for rebuilding bridges and roads essential to commerce and emergency response.

News Contact

Ever since ChatGPT’s debut in 2023, concerns about artificial intelligence (AI) potentially wiping out humanity have dominated headlines. New research from Georgia Tech suggests that those anxieties are misplaced.

“Computer scientists often aren’t good judges of the social and political implications of technology,” said Milton Mueller, a professor in the Jimmy and Rosalynn Carter School of Public Policy. “They are so focused on the AI’s mechanisms and are overwhelmed by its success, but they are not very good at placing it into a social and historical context.”

In the four decades Mueller has studied information technology policy, he has never seen any technology hailed as a harbinger of doom — until now. So, in a Journal of Cyber Policy paper published late last year, he researched whether the existential AI threat was a real possibility. 

What Mueller found is that deciding how far AI can go, and its limitations, is something society shapes. How policymakers get involved depends on the specific AI application. 

Defining Intelligence

The AI sparking all this alarm is called artificial general intelligence (AGI) — a “superintelligence” that would be all-powerful and fully autonomous. Part of the debate, Mueller realized, is that no one could agree on the definition of what artificial general intelligence is. 

Some computer scientists claim AGI would match human intelligence, while others argue it could surpass it. Both assumptions hinge on what “human intelligence” really means. Today’s AI is already better than humans at performing thousands of calculations in an instant, but that doesn’t make it creative or capable of complex problem-solving. 

Understanding Independence 

Deciding on the definition isn’t the only issue. Many computer scientists assume that as computing power grows, AI could eventually overtake humans and act autonomously.

Mueller argued that this assumption is misguided. AI is always directed or trained toward a goal and doesn’t act autonomously right now. Think of the prompt you type into ChatGPT to start a conversation. 

When AI seems to disregard instructions, it’s caused by inconsistencies in its instructions, not by the machine coming alive. For example, in a boat race video game Mueller studied, the AI discovered it could get more points by circling the course instead of winning the race against other challengers. This was a glitch in the system’s reward structure, not AGI autonomy.

“Alignment gaps happen in all kinds of contexts, not just AI,” Mueller said. “I've studied so many regulatory systems where we try to regulate an industry, and some clever people discover ways that they can fulfill the rules but also do bad things. But if the machine is doing something wrong, computer scientists can reprogram it to fix the problem.”

Relying on Regulation

In its current form, even misaligned AI can be corrected. Misalignment also doesn’t mean the AI would snowball past the point where humans lose control of its outcomes. To do that, AI would need to have a physical capability, like robots, to do its bidding, and the power source and infrastructure to maintain itself. A mere data center couldn’t do that and would need human intervention to become omnipotent. Basic laws of physics — how big a machine can be, how much it can compute — would also prevent a super AI. 

More importantly, AI is not one homogenous being. Mueller argued that different applications involve different laws, regulations, and social institutions. For example, the data scraping AI does is a copyright issue subject to copyright laws. AI used in medicine can be overseen by the Food and Drug Administration, regulated drug companies, and medical professionals. These are just a few areas where policymakers could intervene from a specific expertise level instead of trying to create universal AI regulations. 

The real challenge isn’t stopping an AI apocalypse — it’s crafting smart, sector-specific policies that keep technology aligned with human values. To avoid being a victim of AI, humans can, and should, put up focused guardrails. 

News Contact

People with autism seeking employment may soon have access to a new AI-based job-coaching tool thanks to a six-figure grant from the National Science Foundation (NSF).

Jennifer Kim and Mark Riedl recently received a $500,000 NSF grant to develop large language models (LLMs) that provide strength-based job coaching for autistic job seekers. 

The two Georgia Tech researchers work with Heather Dicks, a career development advisor in Georgia Tech’s EXCEL program, and other nonprofit organizations to provide job-seeking resources to autistic people.

Dicks said the average job search for people with autism can take three to six months in a good economy. It can take up to 18 months in a bad one. However, the new LLMs from Georgia Tech could help to reduce stress and fast-track these job seekers into employment.

Kim is an assistant professor who specializes in human-computer interaction technology that benefits neurodivergent people. Riedl is a professor and an expert in the development of artificial intelligence (AI) and machine learning technologies.

The team’s goal is to identify job-search pain points and understand how job coaches create better employment prospects for their autistic clients.

“Large-language models have an opportunity to support this kind of work if we can have more data about each different individual strength,” Kim said.

“We want to know what worked for them in specific settings at work, what didn’t work, and what kind of accommodations can better help them. That includes how they should prepare for interviews, how they can better represent their skills, how they can address accommodations they need, and how to write a cover letter. It’s a broad range.”

Dicks has advocated for neurodivergent people and helped them find employment for 20 years. She worked at the Center for the Visually Impaired in Atlanta before coming to Georgia Tech in 2017.

She said most nonprofits that support neurodivergent people offer career development programs and many contract job coaches, but limited coach availability often leads to long waitlists. However, LLMs could fill this availability gap to address the immediate needs of job seekers who may not have access to a job coach.

“These organizations often run at a slow pace, and there’s high turnover,” Dicks said. “An AI tool could get the job seeker quicker support. Maybe they don’t even need to wait on the government system.

“If they’re on a waitlist, it can help the user put together a resume and practice general interview questions. When the job coach is ready to work with them, they’re able to hit the ground running.”

Nailing the Interview

Dicks said the job interview is one of the biggest challenges for people with autism.

“They have trouble picking up on visual and nonverbal cues — the tone of the interview, figuring out the nuances that a question is hinting at,” she said. “They’re not giving the warm and fuzzy vibes that allow them to connect on a personal level.”

That’s why Kim wants the models to reflect a strength-based coaching approach. Strength-based coaching is particularly effective for individuals with autism. Many possess traits that employers value. These include:

• Close attention to detail
• Strong technical proficiency
• Unique problem-solving perspectives

“The issue is that they don’t know how these strengths can be applied in the workplace,” Kim said. “Once they understand this, they can communicate with employers about their strengths and the accommodations employers should provide to the job seeker so they can successfully apply their skills at work.”

Handling Rejection

Still, Kim understands that candidates will need to handle rejection to make it through the search process. She envisions LLMs that help them refocus their energy and regain their confidence after being turned down.

“When you get a lot of rejection emails, it’s easy to feel you’re not good enough,” she said. “Being constantly reminded about your strengths and their prior successes can get them through the stressful job-seeking process.”

Dicks said the models should also be able to provide feedback so that candidates don’t repeat mistakes.

“It can tell them what would’ve been a better answer or a better way to say it,” Dicks said. “It can also encourage them with reminders that you get 100 noes before you get a yes.”

You’re Hired, Now What?

Dicks said the role of a job coach doesn’t end the moment a client is hired. Government-contracted job coaches may work with their clients for up to 90 days after they start a new job to support their transition.

However, she said, sometimes that isn’t enough. Many companies have probationary periods exceeding three months. Autistic individuals may struggle with on-the-job training or communicating what accommodations they need from their new employer. 

These are just a few gaps an AI tool can fill for these individuals after they’re hired.

“I could see these models evolving to being supportive at those critical junctures of the probationary period being over or the one-year job review or the annual evaluation that everyone dreads,” she said.

Dicks has an average caseload of 15 students, whom she assists in landing jobs and internships through the EXCEL program.

EXCEL provides a mentorship program for students with intellectual and developmental disabilities from the time they set foot on campus through graduation and beyond.

For more information and to apply, visit EXCEL’s website.

News Contact

The AI4Science Center has announced the first recipients of its semiannual seed grant competition. Supported by the Schools of Chemistry and Biochemistry, Physics, and Psychology, the seed grant aims to support the development of research projects centered on innovation and collaboration. 

“The selection committee received more than a dozen proposals that push the boundaries of AI-enabled science and encourage collaboration across units. I look forward to seeing the great science, strong results, and successful future external funding enabled by these seed grants,” says Dimitrios Psaltis, professor in the School of Physics and director of the AI4Science Center. 

Launched earlier this semester, the center promotes cross-disciplinary research on AI tools that address scientific challenges. The following three proposals were selected by the center based on their scientific goals, extent of interdisciplinary collaboration, and potential for outside funding: 

Spring 2026 AI4Science Center Seed Grant Recipients  

Graph Foundation Models for Protein Conformational Dynamics | School of Chemistry and Biochemistry 

• PIs: Professor Peter Kasson, School of Chemistry and Biochemistry; Professor JC Gumbard, School of Physics; Assistant Professor Amirali Aghazadeh, School of Electrical and Computer Engineering
• Graduate student: Jeffy Jeffy
• Team statement: “The AI4Science Center’s seed funding will allow us to complete and test a prototype of our new deep learning architecture for protein dynamics. We're super excited about the project and happy that this gives us support to pursue our new idea.”

Combinations of Verified AI and Domain Knowledge for New Insights in Theoretical Physics | School of Physics

• PIs: Assistant Professor Aishik Ghosh, School of Physics; Professor Vijay Ganesh, School of Computer Science
• Graduate student: Piyush Jha
• Team statement: “This seed funding gives us an opportunity to connect two fields in a way that could transform our approach to certain problems in theoretical physics.”

Harnessing the Manifold Geometry of Neural Representations for Robust LLM Safety | School of Psychology 

• PIs: Assistant Professor Audrey Sederberg, School of Psychology; Assistant Professor Pan Li, School of Electrical and Computer Engineering
• Graduate student: Ruixuan Deng
• Team statement: “Our project injects insights from human neuroscience directly into AI safety algorithm design, allowing us to move beyond black-box approaches toward more interpretable and principled safety mechanisms. By closing the loop, these computational models will also provide new feedback and insights for neuroscience.”

News Contact