Georgia Tech researchers applied their expertise to a national research program that will shape the future of computing. Their work may yield more energy-efficient computers and better predictions for environmental challenges like carbon storage, tsunamis, wildfires, and sustainable energy.
The Department of Energy Office of Science recently released two reports through its Advanced Scientific Computing Research (ASCR) program. The reports were produced by workshops that brought together researchers from universities, national labs, government, and industry to set priorities for scientific computing.
Professor Felix Herrmann served on the organizing committee for the Workshop on Inverse Methods for Complex Systems under Uncertainty. Assistant Professor Peng Chen joined Herrmann as a workshop participant, contributing expertise in data science and machine learning.
Inverse methods work backward from outcomes to find their causes. Scientists use these tools to study complex systems, like designing new materials with targeted properties and using past wildfires to map vulnerable areas and behavior of future fires.
The ASCR report highlighted Herrmann’s work on seismic exploration and monitoring through digital twins. Founded on inverse methods, digital twins upgrade from static models to virtual systems that accurately mirror their physical counterparts.
Digital twins integrate real-time data sources, including fluid flows, monitoring and control systems, risk assessments, and human decisions. These models also account for uncertainty and address data gaps or limitations.
The DOE organized the workshop to support the growing role of inverse modeling. The group identified four priority research directions (PRDs) to guide future work. The PRDs are:
“A digital twin is a system you can control, like to optimize operations or to minimize risk,” said Herrmann, who holds joint appointments in the Schools of Earth and Atmospheric Sciences, Electrical and Computer Engineering, and Computational Science and Engineering.
“Digital twins give you a principled way to consider uncertainties, which there are a lot in subsurface monitoring. If you inject carbon dioxide too fast, you will will increase the pressure and may fracture the rock. If you inject too slow, then the process may become too costly. Digital twins help us make balanced decisions under uncertainty.”
Supercomputers, algorithms, and artificial intelligence now power modern science. However, these tools consume enormous amounts of energy. This raises concerns about how to sustain computing and scientific research as we know them in the decades ahead.
Professors Rich Vuduc and Hyesoon Kim co-authored the report from the Workshop on Energy-Efficient Computing for Science. At the three-day ASCR workshop, participants identified five key research directions:
“I’m cautiously optimistic about the future of energy-efficient computing. The ASCR report says, from a technological point of view, there are things we can do,” said Vuduc.
“The report lays out paths for how we might design better apps, hardware systems, and algorithms that will use less energy. This is recognition that we should think about how architectures and software work together to drive down energy usage for systems.”
Bryant Wine, Communications Officer
bryant.wine@cc.gatech.edu
Photo courtesy of NASA
Georgia Tech’s faculty startup engine Quadrant-i, together with the Space Research Institute (SRI), launched the first cohort of the CreationsVC Space Fellows Program. Funded by space technology venture capital firm CreationsVC, the program enables faculty to explore promising early-stage innovations and their potential for future commercial impact.
“This first set of CreationsVC Fellows offers an exciting cross-section of innovative hardware and software technologies built on Georgia Tech’s legacy of space exploration, hardware development, and product commercialization,” said Jud Ready, SRI executive director.
In the first year of the three-year program, CreationsVC provides $125,000 to promote and accelerate innovations that have both space and terrestrial applications. The series offers participants training focused on customer discovery, engaging and compelling storytelling, value proposition design and quantification, and lean/agile project/product management.
“CreationsVC is centered on a deep appreciation for innovation and big thinking,” said Steve Braverman, co-founder and managing partner of CreationsVC. “We felt this was the right time to align our efforts in sourcing and supporting dual-value technologies that will have an impact on both Earth and space.”
The six startups tackle real-world space research problems like supply chain management, how artificial intelligence works in space, and navigation.
“We are excited CreationsVC is providing us with an opportunity to try new approaches to accelerate deep tech development,” said Jonathan Goldman, Quadrant-i’s director. “These are the toughest kinds of startups to build, and we look forward to the learning we will gain from forcing our innovators out of their comfort zones to embrace some new and valuable skills.”
Founders: Shimeng Yu, James Read
School: School of Electrical and Computer Engineering (ECE)
Objective: To develop energy-efficient, radiation-tolerant artificial intelligence processors using a persistent type of ferroelectric memory. The startup aims to improve applications requiring high power efficiency, such as battery-powered devices and space-based systems.
Why Q-i: “The advantage of Q-i is in helping technical founders turn their research into products that solve customers’ problems,” noted James Read. “For us, that means talking with potential customers and hearing their pain points directly from the source. Now we’re use that information to build a convincing narrative around our startup’s value for stakeholders and investors.”
Founders: Morris Cohen, Matthew Strong
School: ECE
Objective: To provide up-to-date mapping of the electrical properties of the upper atmosphere, with applications to GPS-free navigation, long-range communication, and satellite and launch vehicle viability. The startup uses the radio energy released by lightning strikes to create this map.
Why Q-i: “This weird region about 50 miles up from Earth’s surface is both really hard to track and measure, and also impacts a surprising array of applications,” said Cohen. “It’s sometimes called the `ignorosphere’ because of how difficult it is to measure, and it’s time we change that.”
Founders: Panagiotis Tsiotras, Juan Diego Florez-Castillo, Iason Velentzas
School: Daniel Guggenheim School of Aerospace Engineering (AE)
Objective: To commercialize algorithms that help spacecraft maneuver when they have limited information on their environment. The algorithms use state-of-the-art computer vision and localization techniques. This could benefit manufacturing, assembly, and refueling in orbit, as well as enable monitoring, situational awareness, and debris removal.
Why Q-i: “The program offers a conduit to entrepreneurship opportunities and spinoff companies in the space domain by providing guidance and commercialization ‘know-how,’” said Panagiotis Tsiotras.
Founders: Yashwanth Kumar Nakka, Sadhana Kumar, Vincent Griffo, Sachin Kelkar
School: AE
Objective: To create an autonomous rover platform with adaptive, reconfigurable mobility. The rover will implement software and sensing algorithms to automatically detect terrain type and improve traction and energy usage. This could be used on the moon or Mars, or even terrestrial search and rescue.
Why Q-i: “TerraMorph was developed to address fundamental challenges in mobility and autonomy across uncertain terrain, but successfully translating that work into impact requires creative guidance, critical feedback, and experienced perspectives beyond the lab,” said Yashwanth Kumar Nakka. “Q-i’s culture of leading by example and fostering strong, ethical teams aligns closely with how we want to build TerraMorph: iteratively, thoughtfully, and with a focus on real-world deployment.”
Founders: Shreyes Melkote, Mike Yan
School: George W. Woodruff School of Mechanical Engineering
Objective: To deliver real-time manufacturing supply chain visibility for the space and national security industries. OpenWerks technology aims to dramatically reduce current sourcing cycles from eight months down to weeks by connecting corporate buyers directly with verified supplier manufacturing capability and capacity data.
Why Q-i: “From the very beginning, principals at VentureLab and Q-i offered a clear pathway to translate academic research into a viable business,” said Mike Yan. “Their reputation for guiding Georgia Tech startups through both business and technology derisking, combined with their comprehensive ecosystem of programs and coaches, made them the natural partner for our entrepreneurial journey.”
Founders: Chandra Raman
School: School of Physics
Objective: To manufacture quantum hardware in Georgia. 8Seven8 aims to put high-precision atomic clocks and gyroscopes on a chip for applications ranging from aircraft navigation to industrial automation.
Why Q-i: “They have mentored me and my students through the commercialization process, providing opportunities such as the Space Fellows Cohort,” Chandra Raman said. “One of my former students, Alexandra Crawford, gained valuable business experience through a Q-i entrepreneur’s assistantship, and is now working at 8Seven8 full-time. They have also guided me through the process of obtaining funding through the Georgia Research Alliance for our commercialization effort.”
Tess Malone, Senior Research Writer/Editor
tess.malone@gatech.edu
Georgia Tech has appointed David Sherrill as executive director of the Institute for Data Engineering and Science (IDEaS), effective March 1. Sherrill is a Regents' Professor in the School of Chemistry and Biochemistry with a joint appointment in the School of Computational Science & Engineering. Sherrill has served as associate director for IDEaS since its founding in 2016 and as interim director since January 1, 2025.
“I’m thrilled to see Professor Sherrill tackle this role for the coming 5 years. He understands the rapidly evolving opportunities to apply AI and data science approaches to the diversity of research conducted by Georgia Tech faculty and students, and has a strong agenda to help our researchers make the most of this explosive change in the research landscape.” Said V.P. of Interdisciplinary Research, Julia Kubanek. “He also has deep experience with team building and management which will position IDEaS favorably.”
As executive director, Sherrill will guide IDEaS’ current initiatives, which include the Microsoft CloudHub program that supports innovative applications in Generative Artificial Intelligence, and provide oversight and support for the joint College of Computing / IDEaS Center for Artificial Intelligence in Science and Engineering (ARTISAN), which provides Georgia Tech faculty and research engineers expert support staff, needed cyberinfrastructure, software resources, and advice to assist faculty with projects using large data sets or using AI and machine learning to drive discovery.
Sherrill will also the lead the launch of a new strategic vision, emphasizing the Georgia Tech research community’s expertise in the development of AI and ML techniques and their application to problems in science and engineering, high performance computing, and academic software. Sherrill will focus on internal and external partnerships at IDEaS, creating new collaborative efforts in areas such as economics, policy, and the arts and humanities. He will also work to strengthen current connections across Georgia Tech’s Colleges, Interdisciplinary Research Institutes (IRIs), and the Georgia Tech Research Institute (GTRI).
“It’s a great honor to be named the next executive director of IDEaS,” said Sherrill. “Georgia Tech has world-class faculty and students, and an unparalleled spirit of collaboration. By bringing together faculty from across campus and working together with some of the amazing student groups, we can leverage the power of AI to accelerate our research and maximize our impact. IDEaS will continue to run upskilling workshops to help our campus keep pace with the rapid changes in AI.”
Sherrill is an active promoter of education in computational quantum chemistry, as well as a strong voice for the benefits of open-source software for research acceleration. He was named Outreach Volunteer of the Year by the Georgia Section of the American Chemical Society in 2017, and he is the lead principal investigator of the Psi open-source quantum chemistry program.
Sherrill earned a B.S. in chemistry from MIT in 1992 and a Ph.D. in chemistry from the University of Georgia in 1996. From 1996-1999 Sherril was an NSF Postdoctoral Fellow at the University of California, Berkeley.
Sherrill is Fellow of the American Association for the Advancement of Science (AAAS), the American Chemical Society, and the American Physical Society, and he has been Associate Editor of the Journal of Chemical Physics since 2009. Sherrill has received a Camille and Henry Dreyfus New Faculty Award, the International Journal of Quantum Chemistry Young Investigator Award, an NSF CAREER Award, and Georgia Tech's W. Howard Ector Outstanding Teacher Award. In 2023, he received the Herty Medal from the Georgia Section of the American Chemical Society, and in 2024, he was elected to the International Academy of Quantum Molecular Science.
- Christa M. Ernst
Five faculty members from Georgia Tech have been elected as senior members of the National Academy of Inventors (NAI). As members, they are recognized as distinguished academic inventors with a strong record of patenting technologies, licensing IP, and commercializing their research. Their innovations have made, or have the potential to make, meaningful impacts on society.
“The election of our faculty members to this prestigious association is a powerful affirmation of the innovative research happening at Georgia Tech,” said Raghupathy “Siva” Sivakumar, chief commercialization officer at Georgia Tech. “Their work to take research to market reflects the growing importance of invention in addressing society’s most complex challenges. This recognition signals the strength of the commercialization ecosystem at Georgia Tech to advance impactful research, encourage innovation, and prepare the next generation of inventors.”
The 2026 Georgia Tech NAI senior members are:
Azoulay is recognized for pioneering new classes of functional materials through innovative polymer synthesis, heterocycle chemistry, and polymerization reactions. His work spans electronic, photonic, and quantum materials, device fabrication, and chemical sensing for environmental monitoring. He has demonstrated new classes of organic semiconductors with infrared functionality and holds nine issued U.S. patents. Azoulay is the Georgia Research Alliance Vasser-Woolley Distinguished Investigator and holds a joint appointment in the School of Chemistry and Biochemistry.
Desai is recognized for advancing medical robotics and translational biomedical innovation with inventions spanning robotically steerable guidewires for endovascular interventions, minimally invasive surgical tools, MEMS sensors for cancer diagnosis, and rehabilitation robotics for people with motor impairments. He is the founding editor-in-chief of the Journal of Medical Robotics Research, has authored more than 225 peer-reviewed publications, and serves as the Director of Georgia Center for Medical Robotics at Georgia Tech. Desai holds 15 U.S. and International patents.
Frost has built a career at the intersection of civil engineering research and entrepreneurship. A leader in the study of natural and human-made disasters and their impacts on infrastructure, he has founded two Georgia Tech-based software companies: Dataforensics, which offers tools for subsurface data collection and infrastructure project management, and Filio, an AI-powered mobile platform that supports visual asset management in construction and post-disaster reconnaissance. In 2023, Frost was named a Regents’ Entrepreneur by the University System of Georgia’s Board of Regents, a designation reserved for tenured faculty who have successfully taken their research into a commercial setting. He holds four U.S. patents.
Raman is a physicist, inventor, and technology entrepreneur whose research on ultracold atoms is enabling a new generation of ultraprecise quantum sensing devices. He is the co-inventor of chip-scale atomic beam technology — a breakthrough that makes it possible to miniaturize quantum sensors for navigation and timing applications in environments where GPS fails, with uses spanning autonomous vehicles, aerospace, and national security. Raman holds six U.S. patents, three of which have been issued and two licensed. To bring his inventions to market, he founded 8Seven8 Inc., Georgia’s first quantum hardware company. He is a fellow of the American Physical Society and an advisor to national and space-based quantum initiatives.
Young directs the Exoskeleton and Prosthetic Intelligent Controls Lab, where he develops robotic exoskeletons and intelligent control systems to improve walking function and physical capability for people with mobility impairments and industrial safety applications. His research has been supported by major federal grants from the National Institutes of Health, and he holds three U.S. patents. Young works with Georgia Tech’s Office of Technology Licensing and Quadrant-i to advance promising technologies toward real-world adoption.
The Office of Commercialization is the nexus of research commercialization and entrepreneurship at Georgia Tech, bringing leading-edge research and innovation to market. It comprises six key units — ATDC, CREATE-X, VentureLab, Quadrant-i, Technology Licensing, and Velocity Startups — that empower students and faculty to launch startups, manage intellectual property, and transform research ideas into positive societal impact. Learn more at commercialization.gatech.edu.
The National Academy of Inventors is a member organization comprising U.S. and international universities, and governmental and nonprofit research institutes, with over 4,000 individual inventor members and fellows spanning more than 250 institutions worldwide. It was founded in 2010 to recognize and encourage inventors with patents issued from the U.S. Patent and Trademark Office, enhance the visibility of academic technology and innovation, and translate the inventions of its members to benefit society. Learn more at academyofinventors.org.
Tyler Cook is a research affiliate at the Jimmy and Rosalynn Carter School of Public Policy at Georgia Tech and assistant program director of the Center for AI Learning at Emory University.
Artificial intelligence (AI) loves to cheat. When matched against a chess bot, an OpenAI model preferred hacking into its opponent’s system to winning the game fairly, according to a recent study.
While chess doesn’t have moral stakes, more serious ethical issues could arise in everything from medicine to self-driving cars as AI becomes even more pervasive. So, what does it mean for AI to be safe?
“No one is saying developing safe AI will be easy, but we need to make sure we cover as many ethical concerns as possible,” said Tyler Cook, a research affiliate at the Jimmy and Rosalynn Carter School of Public Policy at Georgia Tech and assistant program director of the Center for AI Learning at Emory University. “Humans also care about being treated fairly. We care about not being deceived. We should aim for much more than safety.”
AI is too complex for simple guardrails, Cook argues in a recent Science and Engineering Ethics paper. But AI still needs to be limited and incorporated with human values of fairness, honesty, and transparency so it doesn’t make ethically dubious decisions.
AI is not just a problem to manage. It’s a technology whose impact depends on the values we choose to build in it, Cook claims. Developers must think carefully about the world their systems will shape. AI shouldn’t make our world, but instead integrate into it.
Safe vs. Autonomous AI
Some computer scientists would say “safe” AI, or AI that doesn’t cause harm, is the answer. But AI is not a simple machine like a lawnmower that needs just a blade guard to prevent harm.
Establishing AI safety is more complex than adding protective features. Being prudent with how much autonomy AI gets is also paramount.
“We don't want AI systems deciding that they don't want to pursue fairness anymore,” Cook said. “We don't want AI to be autonomous with respect to its ethical goals or values.”
Such ethical autonomy could lead to unpredictable or undesirable outcomes. Consider algorithmic bias: Human biases, combined with machine automation, can lead to unequal consequences. An AI mortgage lender could favor certain applicant demographics over others, for example.
Cook posits there is a middle ground between merely safe AI and autonomous ethical AI — “end-constrained ethical AI.”
“As designers of AI systems, computer scientists should choose what we want the AI to prioritize: fairness, honesty, transparency,” Cook said. “That's why I use the language of constraint. We're constraining the AI’s values so they can actually benefit society.”
End‑constrained ethical AI asks designers to set those boundaries intentionally, not as an afterthought. And if developers take that responsibility seriously, AI doesn’t have to reinvent our world — it can strengthen the one we already have.
"A Case for End-Constrained Ethical Artificial Intelligence." Science and Engineering Ethics 32.7 (2026).
DOI: 10.1007/s11948-025-00577-6
Tess Malone, Senior Research Writer/Editor
tess.malone@gatech.edu
Artificial intelligence (AI) systems power everything from chatbots to security cameras, yet many of the most advanced models operate as “black boxes.” Companies can use them, but outsiders can’t see how they were built, where they came from, or whether they contain hidden flaws.
This lack of transparency creates real risks. A model could contain security vulnerabilities or hidden backdoors. It could also be a lightly modified version of an open-source system — repackaged in violation of its license — with no easy way to prove it.
Researchers at the Georgia Institute of Technology have developed a new framework, ZEN, to help solve this problem. The tool can recover a model’s unique “fingerprint” directly from its memory, allowing experts to trace its origins and reconstruct how it was assembled.
“Analyzing a proprietary AI model without identifying where it came from and how it is constructed is like trying to fix a car engine with the hood welded shut,” said David Oygenblik, a Ph.D. student at Georgia Tech and the study’s lead author.
“ZEN not only X-rays the engine but also provides the complete wiring diagram.”
ZEN works by taking a snapshot of a running AI system and extracting information about both its mathematical structure and the code that defines it. It compares that fingerprint against a database of known open-source models to determine the system’s origin.
If it finds a match, ZEN identifies the exact changes and generates software patches that allow investigators to recreate a working replica of the proprietary model for testing.
That capability has major implications for both security and intellectual property protection.
“With ZEN, a security analyst can finally test a black-box model for hidden backdoors, and a company can gather concrete evidence to prove its software license was infringed,” Oygenblik said.
To evaluate the system, the research team tested ZEN on 21 state-of-the-art AI models, including Llama 3, YOLOv10, and other well-known systems.
ZEN correctly traced every customized model back to its original open-source foundation — achieving 100% attribution accuracy. Even when models had been heavily modified — differing by more than 83% from their original versions — ZEN successfully identified the changes and enabled full reconstruction for security testing.
The researchers will present their findings at the 2026 Network and Distributed System Security (NDSS) Symposium. The paper, Achieving Zen: Combining Mathematical and Programmatic Deep Learning Model Representations for Attribution and Reuse, was authored by Oygenblik, master’s student Dinko Dermendzhiev, Ph.D. students Filippos Sofias, Mingxuan Yao, Haichuan Xu, and Runze Zhang, post-doctorate scholars Jeman Park, and Amit Kumar Sikder, as well as Associate Professor Brendan Saltaformaggio.
John Popham
Communications Officer II School of Cybersecurity and Privacy
Written by: Anne Wainscott-Sargent
As artificial intelligence (AI) drives explosive growth in data centers, communities across the U.S. are facing rising electricity costs, new industrial development, and mounting strain on an aging power grid.
At Georgia Tech, several faculty members are approaching these sustainability challenges from different but complementary angles: examining how data center policy affects local communities, modeling how AI-driven demand reshapes regional energy systems, and building tools that help the public understand the tradeoffs embedded in grid planning. Together, their work highlights how better data, thoughtful policy, and public engagement can guide more resilient and equitable decisions in an AI-powered future.
AI’s Hidden Footprint: How Data Centers Reshape Communities
Ahmed Saeed studies the infrastructure most people never see. An assistant professor in the School of Computer Science and a Brook Byers Institute for Sustainable Systems (BBISS) Faculty Fellow, Saeed focuses on how data centers — the backbone of modern AI — are built, operated, and regulated, and what their growth means for host communities.
“Data centers are the infrastructure for our digital life, so more of them are necessary to keep doing what we’re doing,” he said.
Data center energy consumption could double or triple by 2028, accounting for up to 12% of U.S. electricity use, according to a report by Lawrence Berkeley National Laboratory. U.S. spending on data center construction jumped nearly 70% between May 2023 and May 2024, according to the American Edge Project.
Georgia is an AI data center hub, ranked fourth globally, with $4.6 billion in AI-related venture capital invested across 368 deals, the American Edge Project reported. At a recent town hall in DeKalb County, Georgia, Saeed helped residents connect AI’s promise to its local consequences. Training large AI models can require tens of thousands of graphics processing units (GPUs) running for days or weeks, driving an unprecedented wave of data center construction. AI-focused chips, he noted, can consume 10 to 14 times more power than traditional processors.
That demand often shows up as pressure on local infrastructure. Communities are increasingly concerned about electricity and water use, grid upgrades, and who ultimately pays. In Virginia, Saeed pointed to a legal dispute in which consumer advocates warned that data centers could raise electricity bills by 5% in the short term and up to 50% over time, while utilities argued those investments were inevitable and could benefit customers in the long run.
Environmental concerns add another layer. Saeed cited controversies over water use and backup diesel generators in states, including Georgia and Tennessee, alongside a recent Environmental Protection Agency (EPA) ruling that tightened generator regulations. While diesel generators are clearly harmful, he cautioned that long-term, rigorous evidence linking data centers to regional health impacts remains limited.
Saeed’s research aims to reduce those impacts directly. By optimizing how workloads are scheduled across large server fleets, his team has demonstrated power savings of 4 – 12%, a meaningful gain if U.S. data centers approach projected levels of up to 12% of national electricity use by 2028.
For Saeed, data centers are akin to highways: essential to modern life, disruptive to nearby communities, and shaped by policy choices. The question, he argues, is not whether AI infrastructure should exist, but how transparently and fairly it is built.
Economist Probes the Energy Costs of the AI Boom
While headlines often frame AI as an energy crisis, Georgia Tech environmental and energy economist and BBISS Faculty Fellow Tony Harding is focused on measuring its real — and uneven — impacts. Harding, an assistant professor in the Jimmy and Rosalynn Carter School of Public Policy, uses economic modeling to examine how AI adoption affects energy use, emissions, and local communities.
In recent work published in Environmental Research Letters, Harding and his co-author analyzed how productivity gains from AI could influence national energy demand. Their findings suggest that, at a macro level, AI-related activity may increase annual U.S. energy use by about 0.03% and CO₂ emissions by roughly 0.02%.
“Those numbers are small in the context of the overall economy,” Harding said. “But the impacts are highly uneven.”
That unevenness is evident in where data centers are built. While Northern Virginia remains the country’s top data center hub, with 343 operational data centers, states like Georgia, which currently has 94 operational data centers, are rapidly attracting facilities due to reliable power and favorable tax policies.
Harding’s latest research focuses on local effects, asking why data centers cluster in urban areas, how they influence housing markets, what happens to electricity prices, and whether they exacerbate water stress. Early evidence suggests large facilities can increase local electricity rates, contributing to public backlash and regulatory response. In Georgia, the Public Service Commission has begun requiring new, high power draw customers (like data centers) to cover more of the costs associated with grid expansion.
Harding’s goal is to give policymakers better evidence to design incentives and guardrails. “To manage these technologies responsibly,” he said, “we need a clear picture of their intended and unintended consequences.”
Gamifying a Strained and Aging Power Grid
Daniel Molzahn is tackling another side of the problem: how to modernize an aging power grid under growing demand. Electricity demand is expected to rise about 25% by 2030, driven by data centers, electric vehicles, and broadscale electrification. At the same time, much of the U.S. electricity grid is nearing the end of its lifespan, with many transformers being decades old.
To make these challenges tangible, Molzahn, an associate professor in the School of Electrical and Computer Engineering, developed a browser-based game with a group of students through Georgia Tech’s Vertically Integrated Projects program called Current Crisis. Players take on the role of a utility decision-maker, balancing reliability, wildfire risk, renewable integration, and affordability.
The game grew out of Molzahn’s National Science Foundation CAREER award and reflects his belief that complex systems are best understood experientially. Its initial focus is wildfire resilience, modeling how grid infrastructure can both spark and suffer damage from fires.
But resilience comes at a cost. Burying power lines, for example, reduces wildfire risk but dramatically increases expenses. Players must confront the same tradeoffs utilities face: improve reliability or keep rates low.
Molzahn hopes the game will help students and the public grapple with the realities of planning future power systems. “These choices aren’t abstract,” he said. “They shape affordability, resilience, and our path toward a cleaner grid.”
The project now involves nearly 40 students from across campus, supported by Sustainability NEXT funding and a collaboration with Jessica Roberts, former BBISS Faculty Fellow and director of the Technology-Integrated Learning Environments (TILES) Lab in the School of Interactive Computing.
“As a learning scientist, I look at how to engage people with science and scientific data and get people having conversations they might not otherwise have,” says Roberts, who hopes the seed grant helps the team determine first that they are going in the right direction and, second, how to broaden the impact.
One student, Stella Quinto Lima, a graduate research assistant in Human-Centered Computing, has made the game the focus of her doctoral thesis. Through the game, she wants players to notice their misconceptions about the power grid, energy use, and AI, and to use critical thinking to identify, question, and possibly undo those misconceptions.
“I hope that we can really engage adults and help them see it’s not black and white. The game is not only about power grids, but how AI affects the grid, how it affects our lives, and how it will impact our future.”
The team plans to expand the game’s features, use it in outreach programs, and analyze player decisions as a source of data to study energy-system decision-making.
“We want to change the conversation about power and power grid stability, reliability, and sustainability, Roberts said, “and find a way to get this message to a larger public.”
Brent Verrill, Research Communications Program Manager, BBISS
The city of Augusta is a major hub for health and life sciences, boasting five hospitals and the Medical College of Georgia.
The Georgia Institute of Technology and Augusta University have launched a collaborative effort to boost the city’s medical device innovation ecosystem.
The Augusta region is already a major hub for health and life sciences, boasting five hospitals and the Medical College of Georgia, the nation’s 13th oldest medical school and one of its largest.
Additionally, the advocacy nonprofit Georgia Life Sciences designated the region a BioReady Gold community. This ratings system recognizes its existing bioscience assets and its commitment to expanding infrastructure and commercialization, marking Augusta as a desired choice for biotech companies looking for suitable sites to expand.
Leading the work at Georgia Tech are the Georgia Manufacturing Extension Partnership (GaMEP) and Advanced Technology Development Center (ATDC).
GaMEP is a program of the Enterprise Innovation Institute, Tech’s chief economic development arm. It brings a dedicated team with the unique skills required to help innovators clearly understand the requirements needed to bring medical devices to market.
“When entrepreneurs gain insight into the regulatory and quality requirements early in development, they can make informed, strategic decisions that can significantly reduce both time and cost,” said Sarah Jo Tucker, industry manager for GaMEP’s medical device group. “We partner closely with innovators throughout the process and bring deep expertise in the regulatory requirements while they bring expertise in their technology. Together, we can move products efficiently and confidently from concept to commercialization.”
ADTC, part of Georgia Tech’s Office of Commercialization, is the state’s premier technology incubator and the oldest university-based incubator in the country. ATDC provides guidance and resources for entrepreneurs and founders to successfully launch and scale their technology companies.
Since its founding in 1980, ATDC’s startup graduates have attracted more than $6.2 billion in investment and generated over $14 billion in revenue in Georgia. Through the partnership with Augusta University, ATDC uses its expertise to serve entrepreneurs in the medical device field.
"Medical innovation across the state of Georgia is critical for our health tech industries to thrive,” said Chris Dickson, ATDC’s startup catalyst in the Augusta region. “We identify investment-ready medical technology startups and provide the support needed while they are scaling their businesses.”
A major hub for the life sciences, Augusta University is home to a wealth of researchers in the biomedical and related fields. This makes the institution ideally situated to help facilitate medical device commercialization.
Guido Verbeck understands this dynamic firsthand. A professor of chemistry and biochemistry at Augusta University, he is also an entrepreneur and medical device innovator.
“Academia is a fantastic platform for launching ideas, but there must be an understanding of how to bring a device to market,” said Verbeck. “Physicians and practitioners who are also academics are solving problems in real time, but they often lack the resources and support to get their ideas to production and commercialization.”
Lynsey Steinberg, director of innovation for Augusta University’s strategic partnerships and economic development team, summed up collaboration’s goal.
“When we tap our depth of talent, innovation, and community collaboration, this region has what it takes to become a launchpad for medical device startups — a place where bold ideas find the purpose they need to succeed to solve real-world problems,” she said.
Eve Tolpa
eve.tolpa@innovate.gatech.edu
Meta CEO Mark Zuckerberg took the witness stand last week in Los Angeles County Superior Court to defend his company from accusations that social media harms children.
A lawsuit filed by a 20-year-old plaintiff alleges Instagram and other social media apps are designed to make young users addicted to their platforms.
Meanwhile, social media experts believe the algorithms that drive content on these platforms play a role in hooking users and keeping them scrolling for extensive periods of time.
A new study led by Georgia Tech might confirm this suspicion.
Using recently acquired data from more than 10,000 adolescent users, Munmun De Choudhury will audit TikTok’s recommendation algorithm and study its impact on young people’s behavior and mental health.
De Choudhury is leading a multi-institutional research team on a four-year, $1.7 million grant from the Huo Family Foundation.
“We hope to learn the different types of negative exposures that young people experience when using TikTok,” De Choudhury said. “This can help us characterize what they’re watching and build computational methods to understand the consumption behaviors of these participants and how they’re affected by the algorithm.”
De Choudhury, a professor in Georgia Tech’s School of Interactive Computing, is collaborating with Amy Orben, a professor at the University of Cambridge, and Homa Hosseinmardi, an assistant professor at UCLA, on the project.
Social media platforms have become increasingly reluctant to share their data in recent years, posing a challenge for researchers like De Choudhury.
“We can’t do the type of studies we did 10 years ago with X (formerly Twitter) because the API is much more restrictive,” she said. “There are limited ways to programmatically access people’s data now.
“We must go through a tedious, manual process to get around declining access to social media data. This data-gathering process is essential given the sensitive nature of mental health research. You want data that is shared with consent.”
Orben collected TikTok data from more than 10,000 young people in the UK who consented to provide their personal data archives in accordance with the European Union’s General Data Protection Regulation (GDPR).
The collected data includes watch histories, which De Choudhury said distinguishes this research from other social media studies that focus on what users post.
“We don’t understand passive social media consumption very well, so we hope to close that gap and learn what that looks like,” she said. “That could complement or contrast what we know about people’s active engagement on these platforms. Is what they’re consuming directly related to what they’re posting? How does passive consumption affect young people’s mental health?”
A clearer picture of how algorithm-based content affects young people could result in design interventions to minimize negative effects. De Choudhury said studying data from young people is critical because it’s not too late to steer them away from unhealthy behavioral patterns.
“Some of the earliest signs or symptoms of mental health conditions appear in adolescence,” she said. “If appropriate care and support are provided, maybe it’s possible to prevent these symptoms from becoming full-blown in the future.”
What the research team learns about TikTok could also provide broader insight into other social media platforms.
TikTok has been influential in how social media platforms display video content. Competitors like Instagram and X modeled their video presentation after TikTok’s, which can easily lead to doomscrolling.
“Our hope is that our findings can be generalized, with the caveat the data we have is exclusively from TikTok,” De Choudhury said. “Other platforms have similar video-sharing and consumption features where the video automatically plays from one to the next. We hope what we learn from TikTok will be applicable to people’s activities elsewhere, though it will require future work beyond this project to draw concrete conclusions.”
De Choudhury said an additional part of the study will be using artificial intelligence (AI) to simulate video feeds.
In 2024, Hosseinmardi led a study at the University of Pennsylvania on YouTube’s recommendation algorithm and used bots that either followed or ignored the recommendations.
De Choudhury said they will use a similar method for TikTok.
“The feeds will be realistic but generated by AI to see the potential pathways to consumption rabbit holes,” she said. “This should give us some insight into how algorithms influence the negative and positive exposures people might be having on TikTok.”
Based in the UK and established in 2009, the Huo Family Foundation supports community education initiatives in the UK, the U.S., and China.
The organization announced in January its launch of the Huo Family Foundation Science Programme. The new program is committing $17.6 million to fund 20 new multi-year research grants that explore the impact of digital technology on the brain development, social behavior, and mental health of young people.
“Digital technology is profoundly shaping childhood and young adulthood, yet there is limited causal evidence of its effects,” said Yan Huo, founder of the Huo Family Foundation, in a press release. “We are proud to support exceptional researchers advancing vital scientific understanding.”