Imagine a future where robotic guide dogs lead the visually impaired, flying cars navigate the skies, and electric self-driving vehicles communicate effortlessly with pedestrians.

That future is being shaped today at Georgia Tech’s Center for Human-AI-Robot Teaming (CHART). Led by Bruce Walker, a professor in the School of Psychology and the School of Interactive Computing, the newly launched Center aims to transform how humans, artificial intelligence, and robots work together. By focusing on the dynamic partnership between humans and intelligent systems, CHART will explore how humans can collaborate more effectively with artificial intelligence systems and robots to solve critical scientific and societal challenges.

“There are wonderful Georgia Tech units like the Institute for People and Technology and the Institute for Robotics and Machines  that do an incredible job focusing on using and creating intelligent systems and technology,” says Walker. “CHART adds value to this ecosystem with our emphasis on the interactive partnership between humans, AI technology, and robots and machines with agency.”

Based in the School of Psychology, CHART has built an international and interdisciplinary consortium of researchers and innovators from academia and industry. Its impressive membership includes researchers from five Georgia Tech colleges, 18 universities worldwide, industry, public policy organizations, cities, and NASA.

“With expertise encompassing psychology, design, interactive computing, robotics, aerospace engineering, mechanical engineering, public policy, and business, CHART leverages a wealth of knowledge to help us tackle multifaceted challenges — and we’re adding new members every week,” says Walker.

To help shepherd this growth, CHART’s Steering Committee includes School of Psychology Professor Christopher Wiese and Assistant Professor Mengyao Li and School of Mechanical Engineering Assistant Professor Ye Zhao.

Tomorrow’s technology

Several research programs already underway at CHART showcase its vision of deeply transformative, human-centered research:

Robotic guide dogs

Walker co-leads this research with Sehoon Ha, an assistant professor in the School of Interactive Computing. The project explores the partnership between a robotic guide dog robot and a human as they navigate the physical and social environment. Key concerns include trust, communication, sharing of responsibilities, and how the human-robot team integrates into social settings. The project also addresses practical design issues like ensuring the robot operates quietly to avoid interfering with auditory cues critical for blind users.

Flying cars

This project investigates how humans will interact with emerging flying vehicle technologies. It explores user interfaces, control systems, and human-machine interaction design, including whether traditional steering controls might evolve into joystick-like mechanisms. Broader issues include how flying cars will fit into current infrastructure, impacts on pilot licensing policy and regulation, and the psychology of adopting futuristic technologies.

Pedestrians and self-driving cars

Researchers are exploring how driverless electric vehicles and pedestrians can communicate to keep our future streets safe, including how vehicles signal their intentions to pedestrians. Teams are also implications for safety and public policy, including accident liability and the quiet nature of electric vehicles.

Generative AI in Education

This project examines how students use generative AI like ChatGPT as collaborators in learning. The research explores its effects on outcomes, education policy, and curriculum development.

Meet CHART Founding Director Bruce Walker

Walker is excited about CHART’s future and its role in improving the world.

“We’ve got an ambitious plan and with the caliber of researchers we have assembled from around the world, the possibilities are limitless,” says Walker. “I see Georgia Tech leading the way as a center of gravity in this space.”

His background renders him well-suited to the interdisciplinary nature of the Center. Walker brings a wealth of experience in psychology, human-computer interaction, and related fields, with research interests spanning sonification and auditory displays, trust in automation, technology adoption, human-AI-robot teaming, and assistive technologies. In addition to CHART, he's the director of the Georgia Tech Sonification Lab.

Walker’s academic research has resulted in more than 250 journal articles and proceedings, and he has consulted for NASA, state and federal governments, private companies, and the military. He is also an active entrepreneur, founding startups and working on projects related to COVID diagnosis, skin cancer detection, mental health monitoring, gun safety, and digital scent technology. 

Reflecting on the journey ahead, Walker says, “We’ve come out of the gate strong. I look forward to the innovations ahead and continuing to cultivate a community of future leaders in this field.”

The Georgia Institute of Technology will receive up to $2 million to research advanced semiconductor packaging technologies. Georgia Tech was selected as a partner institution by the South Korean Ministry of Trade. 

The Institute for Matter and Systems (IMS), George W. Woodruff School of Mechanical Engineering, and the 3D Systems Packaging Research Center (PRC) will work with Myongji University and industry partners in South Korea on a seven-year collaborative project that focuses on developing core evaluation technologies for advanced semiconductor packaging. 

The project is led by Seung-Joon Paik, IMS research engineer; Yongwon Lee, research engineer in the George W. Woodruff School of Mechanical Engineering; and Kyong-Sik “Jack” Moon, PRC research engineer. It is funded by the Korea Planning & Evaluation Institute of Industrial Technology of the Ministry of Trade, Industry and Energy in Korea.

The project aims to develop validation technologies for next-generation 3D packaging with strategic globally competitive capabilities. The developed platform will meet the high growing demand for advanced packaging technologies for artificial intelligence, high-performance computing, and chiplet-based semiconductor. As a designated partner, Georgia Tech will play a pivotal role in developing core evaluation technologies. 

The project’s outcomes will contribute to the commercialization of dependable packaging technologies and the resilience of the global semiconductor supply chain.

Origami — the Japanese art of folding paper — could be at the next frontier in innovative materials.

Practiced in Japan since the early 1600s, origami involves combining simple folding techniques to create intricate designs. Now, Georgia Tech researchers are leveraging the technique as the foundation for next-generation materials that can both act as a solid and predictably deform, “folding” under the right forces. The research could lead to innovations in everything from heart stents to airplane wings and running shoes.

Recently published in Nature Communications, the study, “Coarse-grained fundamental forms for characterizing isometries of trapezoid-based origami metamaterials,” was led by first author James McInerney, who is now a NRC Research Associate at the Air Force Research Laboratory. McInerney, who completed the research while a postdoctoral student at the University of Michigan, was previously a doctoral student at Georgia Tech in the group of study co-author Zeb Rocklin. The team also includes Glaucio Paulino (Princeton University), Xiaoming Mao (University of Michigan), and Diego Misseroni (University of Trento).

“Origami has received a lot of attention over the past decade due to its ability to deploy or transform structures,” McInerney says. “Our team wondered how different types of folds could be used to control how a material deforms when different forces and pressures are applied to it” — like a creased piece of cardboard folding more predictably than one that might crumple without any creases.

The applications of that type of control are vast. “There are a variety of scenarios ranging from the design of buildings, aircraft, and naval vessels to the packaging and shipping of goods where there tends to be a trade-off between enhancing the load-bearing capabilities and increasing the total weight,” McInerney explains. “Our end goal is to enhance load-bearing designs by adding origami-inspired creases — without adding weight.”

The challenge, Rocklin adds, is using physics to find a way to predictably model what creases to use and when to achieve the best results.

Deformable solids

Rocklin, a theoretical physicist and associate professor in the School of Physics at Georgia Tech, emphasizes the complex nature of these types of materials. “If I tug on either end of a sheet of paper, it's solid — it doesn’t separate,” he explains. “But it's also flexible — it can crumple and wave depending on how I move it. That’s a very different behavior than what we might see in a conventional solid, and a very useful one.”

But while flexible solids are uniquely useful, they are also very hard to characterize, he says. “With these materials, it is often difficult to predict what is going to happen — how the material will deform under pressure because they can deform in many different ways. Conventional physics techniques can't solve this type of problem, which is why we're still coming up with new ways to characterize structures in the 21st century.”

When considering origami-inspired materials, physicists start with a flat sheet that's carefully creased to create a specific three-dimensional shape; these folds determine how the material behaves. But the method is limited: only parallelogram-based origami folding, which uses shapes like squares and rectangles, had previously been modeled, allowing for limited types of deformation.

“Our goal was to expand on this research to include trapezoid faces,” McInerney says. Parallelograms have two sets of parallel sides, but trapezoids only need to have one set of parallel sides. Introducing these more variable shapes makes this type of creasing more difficult to model, but potentially more versatile.

Breathing and shearing

“From our models and physical tests, we found that trapezoid faces have an entirely different class of responses,” McInerney shares. In other words — using trapezoids leads to new behavior.

The designs had the ability to change their shape in two distinct ways: "breathing" by expanding and contracting evenly, and “shearing" by deforming in a twisting motion. “We learned that we can use trapezoid faces in origami to constrain the system from bending in certain directions, which provides different functionality than parallelogram faces,” McInerney adds. 

Surprisingly, the team also found that some of the behavior in parallelogram-based origami carried over to their trapezoidal origami, hinting at some features that might be universal across designs.

“While our research is theoretical, these insights could give us more opportunities for how we might deploy these structures and use them,” Rocklin shares.

Future folding

“We still have a lot of work to do,” McInerney says, sharing that there are two separate avenues of research to pursue. “The first is moving from trapezoids to more general quadrilateral faces, and trying to develop an effective model of the material behavior — similar to the way this study moved from parallelograms to trapezoids.” Those new models could help predict how creased materials might deform under different circumstances, and help researchers compare those results to sheets without any creases at all. “This will essentially let us assess the improvement our designs provide,” he explains.

“The second avenue is to start thinking deeply about how our designs might integrate into a real system,” McInerney continues. “That requires understanding where our models start to break down, whether it is due to the loading conditions or the fabrication process, as well as establishing effective manufacturing and testing protocols.”

“It’s a very challenging problem, but biology and nature are full of smart solids — including our own bodies — that deform in specific, useful ways when needed,” Rocklin says. “That’s what we’re trying to replicate with origami.”

This research was funded by the Office of Naval Research, European Union, Army Research Office, and National Science Foundation.

DOI: https://doi.org/10.1038/s41467-025-57089-x 

A Georgia Tech doctoral student’s dissertation could help physicians diagnose neuropsychiatric disorders, including schizophrenia, autism, and Alzheimer’s disease. The new approach leverages data science and algorithms instead of relying on traditional methods like cognitive tests and image scans.

Ph.D. candidate Md Abdur Rahaman’s dissertation studies brain data to understand how changes in brain activity shape behavior. 

Computational tools Rahaman developed for his dissertation look for informative patterns between the brain and behavior. Successful tests of his algorithms show promise to help doctors diagnose mental health disorders and design individualized treatment plans for patients.

“I've always been fascinated by the human brain and how it defines who we are,” Rahaman said. 

“The fact that so many people silently suffer from neuropsychiatric disorders, while our understanding of the brain remains limited, inspired me to develop tools that bring greater clarity to this complexity and offer hope through more compassionate, data-driven care.”

Rahaman’s dissertation introduces a framework focusing on granular factoring. This computing technique stratifies brain data into smaller, localized subgroups, making it easier for computers and researchers to study data and find meaningful patterns.

Granular factoring overcomes the challenges of size and heterogeneity in neurological data science. Brain data is obtained from neuroimaging, genomics, behavioral datasets, and other sources. The large size of each source makes it a challenge to study them individually, let alone analyze them simultaneously, to find hidden inferences. 

Rahaman’s research allows researchers and physicians to move past one-size-fits-all approaches. Instead of manually reviewing tests and scans, algorithms look for patterns and biomarkers in the subgroups that otherwise go undetected, especially ones that indicate neuropsychiatric disorders.

“My dissertation advances the frontiers of computational neuroscience by introducing scalable and interpretable models that navigate brain heterogeneity to reveal how neural dynamics shape behavior,” Rahaman said. 

“By uncovering subgroup-specific patterns, this work opens new directions for understanding brain function and enables more precise, personalized approaches to mental health care.”

Rahaman defended his dissertation on April 14, the final step in completing his Ph.D. in computational science and engineering. He will graduate on May 1 at Georgia Tech’s Ph.D. Commencement. 

After walking across the stage at McCamish Pavilion, Rahaman’s next step in his career is to go to Amazon, where he will work in the generative artificial intelligence (AI) field. 

Graduating from Georgia Tech is the summit of an educational trek spanning over a decade. Rahaman hails from Bangladesh where he graduated from Chittagong University of Engineering and Technology in 2013. He attained his master’s from the University of New Mexico in 2019 before starting at Georgia Tech. 

“Munna is an amazingly creative researcher,” said Vince Calhoun, Rahman’s advisor. Calhoun is the founding director of the Translational Research in Neuroimaging and Data Science Center (TReNDS).

TReNDS is a tri-institutional center spanning Georgia Tech, Georgia State University, and Emory University that develops analytic approaches and neuroinformatic tools. The center aims to translate the approaches into biomarkers that address areas of brain health and disease.    

“His work is moving the needle in our ability to leverage multiple sources of complex biological data to improve understanding of neuropsychiatric disorders that have a huge impact on an individual’s livelihood,” said Calhoun.

Georgia Tech professors Michelle LaPlaca and W. Hong Yeo have been selected as recipients of Peterson Professorships with the Children’s Healthcare of Atlanta Pediatric Technology Center (PTC) at Georgia Tech. The professorships, supported by the G.P. “Bud” Peterson and Valerie H. Peterson Faculty Endowment Fund, are meant to further energize the Georgia Tech and Children’s partnership by engaging and empowering researchers involved in pediatrics.

In a joint statement, PTC co-directors Wilbur Lam and Stanislav Emelianov said, “The appointment of Dr. LaPlaca and Dr. Yeo as Peterson Professors exemplifies the vision of Bud and Valerie Peterson — advancing innovation and collaboration through the Pediatric Technology Center to bring breakthrough ideas from the lab to the bedside, improving the lives of children and transforming healthcare.”

LaPlaca is a professor and associate chair for Faculty Development in the Department of Biomedical Engineering, a joint department between Georgia Tech and Emory University. Her research is focused on traumatic brain injury and concussion, concentrating on sources of heterogeneity and clinical translation. Specifically, she is working on biomarker discovery, the role of the glymphatic system, and novel virtual reality neurological assessments.    

“I am thrilled to be chosen as one of the Peterson Professors and appreciate Bud and Valerie Peterson’s dedication to pediatric research,” she said. “The professorship will allow me to broaden research in pediatric concussion assessment and college student concussion awareness, as well as to identify biomarkers in experimental models of brain injury.”

In addition to the research lab, LaPlaca will work with an undergraduate research class called Concussion Connect, which is part of the Vertically Integrated Projects program at Georgia Tech.

“Through the PTC, Georgia Tech and Children’s will positively impact brain health in Georgia’s pediatric population,” said LaPlaca.

Yeo is the Harris Saunders, Jr. Professor in the George W. Woodruff School of Mechanical Engineering and the director of the Wearable Intelligent Systems and Healthcare Center at Georgia Tech. His research focuses on nanomanufacturing and membrane electronics to develop soft biomedical devices aimed at improving disease diagnostics, therapeutics, and rehabilitation.

“I am truly honored to be awarded the Peterson Professorship from the Children’s PTC at Georgia Tech,” he said. “This recognition will greatly enhance my research efforts in developing soft bioelectronics aimed at advancing pediatric healthcare, as well as expand education opportunities for the next generation of undergraduate and graduate students interested in creating innovative medical devices that align seamlessly with the recent NSF Research Traineeship grant I received. I am eager to contribute to the dynamic partnership between Georgia Tech and Children’s Healthcare of Atlanta and to empower innovative solutions that will improve the lives of children.”

The Peterson Professorships honor the former Georgia Tech President and First Lady, whose vision for the importance of research in improving pediatric healthcare has had an enormous positive impact on the care of pediatric patients in our state and region.

The Children’s PTC at Georgia Tech brings clinical experts from Children’s together with Georgia Tech scientists and engineers to develop technological solutions to problems in the health and care of children. Children’s PTC provides extraordinary opportunities for interdisciplinary collaboration in pediatrics, creating breakthrough discoveries that often can only be found at the intersection of multiple disciplines. These collaborations also allow us to bring discoveries to the clinic and the bedside, thereby enhancing the lives of children and young adults. The mission of the PTC is to establish the world’s leading program in the development of technological solutions for children’s health, focused on three strategic areas that will have a lasting impact on Georgia’s kids and beyond.

Reagan Cook stood at a career crossroads when her undergraduate degree in mechanical engineering intersected with her recent master’s in data analytics.

She wanted to connect her experience in manufacturing with her burgeoning interest in data science but wasn’t sure which way to turn. Then, she stumbled upon a job opportunity that brought both into one path forward: A fellowship focused on artificial intelligence in manufacturing through the Partnership for Inclusive Innovation, or PIN.

“I happened upon this fellowship and the vertical I landed on was AI in manufacturing, which was a good marriage of the two disciplines,” said Cook, who began the one-year paid position over the summer. The PIN fellowship, part of Georgia Institute of Technology’s Enterprise Innovation Institute, places early career professionals into public and private opportunities.

The fellowship is made possible through support from Georgia Artificial Intelligence in Manufacturing, or Georgia AIM. Georgia AIM supports several PIN fellows each year through the AI in Manufacturing vertical. Participants spend six months working on a research project through the Georgia Tech Manufacturing Institute (GTMI) and then six months with a partner company where they focus on a project that enhances the use of smart technologies.

Cook recently completed her first six-month rotation as a researcher with the Melkote Advanced Manufacturing Research Group at Georgia Tech, working with GTMI Associate Director Shreyes Melkote. She is now in her next role at Carbice, an Atlanta semiconductor manufacturer.

That’s the interesting part of the PIN fellowship: those accepted into the program gain experience in both the public and private sectors. Upon completing the program, fellows enter the workforce with a unique, innovative skillset that contributes to the emerging roles AI is creating in manufacturing.

The PIN program also helps address a gap in the workforce. There is a growing need for professionals who understand AI and smart technologies, and the program’s public/private partnership provides useful training and experience to early career professionals who are eager to solve these challenges.

In Cook’s case, her first job after college was with a small manufacturer doing engineering design and CAD work. Her role expanded a bit to accommodate her data analytics background while working on her master’s degree practicum project. But due to the size of the company, her work returned to strictly engineering after she graduated. In contrast, through the PIN fellowship, Cook is working on developing machine learning models that can be used to search for parts in a database of CAD designs. This would allow manufacturers looking for CAD drawings or 3D models to find similar parts with designs already created, saving time by giving engineers a starting point. This research allows her to leverage both her analytics and engineering knowledge.

"I feel like I am learning a lot,” said Cook. The research position allows her to apply theoretical knowledge from her master’s degree in a research environment. “That’s been very interesting and eye-opening. I’m still early in my career and my only experience is fairly traditional corporate jobs, so working in the realm of the unknown is a different situation. With research, you’re just exploring and have no assurances that what you’re doing is going to work. ”

Moving to Carbice for the second half of her fellowship adds another layer of learning, she added, because it’s one thing to test out a theory in a lab; it’s different when you are working for a company that needs to see results.

“Working in the private sector allows you to identify and reality-check the needs of actual workplaces,” she added. “Because sometimes you have a compelling idea and interesting research, but in a corporate setting, first, is it useful, and second, if it is useful, is it even something the industry wants or is willing to adopt?”

This is a paradox Cook will face not only during the second half of her fellowship, but also going forward in her career. The foundational experiences attained through the PIN fellowship will give Cook an edge as she moves into her next role. Many manufacturers are interested in adopting AI and smart technologies, but the challenge is in identifying problems to solve.

Cook said she is confident the fellowship will give her new insights that can be beneficial to future employers. The program also offers networking opportunities and connections with respected professionals that will be beneficial in years to come, she added.

“It’s really good to have both the public and private perspectives. And because I’ve worked in a couple different manufacturing environments, I’m interested in how different my manufacturing rotation will be and if I can identify patterns, similar issues, or inefficiencies. And all that is useful knowledge to have,” she said. “For me specifically, the content of this work is going to be very helpful in tying my whole resume together.”

For more details on the AI and Manufacturing-focused PIN fellowship supported by Georgia AIM, visit the PIN website.

A Georgia Tech alum’s dissertation introduced ways to make artificial intelligence (AI) more accessible, interpretable, and accountable. Although it’s been a year since his doctoral defense, Zijie (Jay) Wang’s (Ph.D. ML-CSE 2024) work continues to resonate with researchers.

Wang is a recipient of the 2025 Outstanding Dissertation Award from the Association for Computing Machinery Special Interest Group on Computer-Human Interaction (ACM SIGCHI). The award recognizes Wang for his lifelong work on democratizing human-centered AI.

“Throughout my Ph.D. and industry internships, I observed a gap in existing research: there is a strong need for practical tools for applying human-centered approaches when designing AI systems,” said Wang, now a safety researcher at OpenAI.

“My work not only helps people understand AI and guide its behavior but also provides user-friendly tools that fit into existing workflows.”

[Related: Georgia Tech College of Computing Swarms to Yokohama, Japan, for CHI 2025]

Wang’s dissertation presented techniques in visual explanation and interactive guidance to align AI models with user knowledge and values. The work culminated from years of research, fellowship support, and internships.

Wang’s most influential projects formed the core of his dissertation. These included:

• CNN Explainer: an open-source tool developed for deep-learning beginners. Since its release in July 2020, more than 436,000 global visitors have used the tool.
• DiffusionDB: a first-of-its-kind large-scale dataset that lays a foundation to help people better understand generative AI. This work could lead to new research in detecting deepfakes and designing human-AI interaction tools to help people more easily use these models.
• GAM Changer: an interface that empowers users in healthcare, finance, or other domains to edit ML models to include knowledge and values specific to their domain, which improves reliability.
• GAM Coach: an interactive ML tool that could help people who have been rejected for a loan by automatically letting an applicant know what is needed for them to receive loan approval.
• Farsight: a tool that alerts developers when they write prompts in large language models that could be harmful and misused.  

“I feel extremely honored and lucky to receive this award, and I am deeply grateful to many who have supported me along the way, including Polo, mentors, collaborators, and friends,” said Wang, who was advised by School of Computational Science and Engineering (CSE) Professor Polo Chau.

“This recognition also inspired me to continue striving to design and develop easy-to-use tools that help everyone to easily interact with AI systems.”

Like Wang, Chau advised Georgia Tech alumnus Fred Hohman (Ph.D. CSE 2020). Hohman won the ACM SIGCHI Outstanding Dissertation Award in 2022.

Chau’s group synthesizes machine learning (ML) and visualization techniques into scalable, interactive, and trustworthy tools. These tools increase understanding and interaction with large-scale data and ML models. 

Chau is the associate director of corporate relations for the Machine Learning Center at Georgia Tech. Wang called the School of CSE his home unit while a student in the ML program under Chau.

Wang is one of five recipients of this year’s award to be presented at the 2025 Conference on Human Factors in Computing Systems (CHI 2025). The conference occurs April 25-May 1 in Yokohama, Japan. 

SIGCHI is the world’s largest association of human-computer interaction professionals and practitioners. The group sponsors or co-sponsors 26 conferences, including CHI.

Wang’s outstanding dissertation award is the latest recognition of a career decorated with achievement.

Months after graduating from Georgia Tech, Forbes named Wang to its 30 Under 30 in Science for 2025 for his dissertation. Wang was one of 15 Yellow Jackets included in nine different 30 Under 30 lists and the only Georgia Tech-affiliated individual on the 30 Under 30 in Science list.

While a Georgia Tech student, Wang earned recognition from big names in business and technology. He received the Apple Scholars in AI/ML Ph.D. Fellowship in 2023 and was in the 2022 cohort of the J.P. Morgan AI Ph.D. Fellowships Program.

Along with the CHI award, Wang’s dissertation earned him awards this year at banquets across campus. The Georgia Tech chapter of Sigma Xi presented Wang with the Best Ph.D. Thesis Award. He also received the College of Computing’s Outstanding Dissertation Award.

“Georgia Tech attracts many great minds, and I’m glad that some, like Jay, chose to join our group,” Chau said. “It has been a joy to work alongside them and witness the many wonderful things they have accomplished, and with many more to come in their careers.”

What’s the hottest thing in electronics and high-performance computing? In a word, it’s “cool.”

To be more precise, it’s a liquid cooling system developed at Georgia Tech for electronics aimed at solving a long-standing problem: overheating.

Developed by Daniel Lorenzini, a 2019 Tech graduate who earned his Ph.D. in mechanical engineering, the cooling system uses microfluidic channels — tiny, intricate pathways for liquids — that are embedded within the chip packaging.

He worked with VentureLab, a Tech program in the Office of Commercialization, to spin his research into a startup company, EMCOOL, headquartered in Norcross.

“Our solution directly addresses the heat at the source of the silicon chip and therefore makes it faster,” Lorenzini said. “Our design has our system sitting directly on the silicon chips that generate the most heat. Using the fluids in the micro-pin fins, it carries the heat that’s produced away from the chip.”

That cooling solution is directly integrated into the electronic components, making it significantly more efficient than conventional cooling methods, because it enhances the heat dissipation process.

The result is a much lower risk of overheating and reduced power consumption, he said.

Lorenzini, who researched and refined the technology in the lab of Yogendra Joshi at the George W. Woodruff School of Mechanical Engineering, was awarded a patent for the technology in September 2024.

Now, EMCOOL, which has five empoloyees, is actively pursuing venture capital funding to scale its technology and address the escalating thermal management challenges posed by AI processors in modern data centers.

The system uses a cooling block with tiny, pin-like fins on one side and a special thermal interface material on the other. There's also a junction attached to the block, with ports for the fluid to flow in and out. The cooling fluid moves through the micro-pin fins and helps to carry away the heat.

Since the ports are designed to match the shape of the fins, it ensures that the fluid flows efficiently and the heat is dissipated as effectively as possible at chip-scale. 

As electronic devices — from high-performance personal computers to data centers used for artificial intelligence processing — become more powerful, they generate more heat. This excess heat can damage components or cause the device to underperform.

Traditional cooling methods, which include fans or heat sinks, often struggle to keep pace with the increasing demands of the newer model electronics. Lorenzini’s microfluidic system addresses the challenge of overheating with his patented, more effective, compact, and integrated cooling solution.

With the guidance of Jonathan Goldman, director of Quadrant-i in Tech’s Office of Commercialization, Lorenzini secured grant funding through the National Science Foundation and the Georgia Research Alliance to further the research and build design prototypes.

“We immediately had the sense there was commercial potential here,” Goldman said. “Thermal management, or getting rid of heat, is a ubiquitous problem in the computer industry, so when we saw what Daniel was doing, we immediately began to engage with him to understand what the commercial potential was.”

Indeed, the initial focus for the technology was the $159 billion global electronic gaming market. Gamers need a lot of computing power, which generates a lot of heat, causing lag.

But beyond gaming systems, the company, which manufactures custom cooling blocks and kits at its Norcross facility, is eyeing more sectors, which also suffer from overheating, Goldman said.

The technology addresses similar overheating electronics challenges in high-performance computing, telecommunications, and energy systems.

“This work propels us forward in pushing the boundaries of what traditional cooling technologies can achieve because by harnessing the power of microfluidics, EMCOOL's systems offer a compact and energy-efficient way to manage heat,” Goldman said. “This has the potential to revolutionize industries reliant on high-performance computing, where heat management is a constant challenge.”

In a groundbreaking study published in Nature, researchers from Georgia Tech and Emory University have developed a new model that could enable precise, life-saving medication delivery for blood clot patients. The novel technique uses a 3D microchip

Wilbur Lam, professor at Georgia Tech and Emory University, and a clinician at Children’s Healthcare of Atlanta, led the study. He worked closely with Yongzhi Qiu, an assistant professor in the Department of Pediatrics at Emory University School of Medicine. 

The significance of the thromboinflammation-on-a-chip model, is that it mimics clots in a human-like way, allowing them to last for months and resolve naturally. This model helps track blood clots and more effectively test treatments for conditions including sickle cell anemia, strokes, and heart attacks. 

Read the full story from Emory University

In a significant move to bolster Georgia's workforce, Georgia Tech has partnered with Georgia Quick Start to advance manufacturing training and skill development. This collaboration, formalized by the signing of a Memorandum of Understanding on April 8, aims to elevate the quality and efficiency of manufacturing workforce training across the state.

“At Georgia Tech, innovation isn’t just about discovery — it’s about solving real-world challenges,” said Executive Vice President for Research Tim Lieuwen. “Georgia Quick Start ensures that cutting-edge research in advanced manufacturing translates into practical training solutions. Together, we are equipping Georgia’s workforce with the skills needed to drive economic growth and industry advancement.”

As manufacturing technologies and artificial intelligence continue to evolve, U.S. manufacturers increasingly require skilled workers experienced in advanced manufacturing. For decades, Georgia Quick Start, administered by the Technical College System of Georgia, has been addressing this need and has been recognized as the country’s top workforce training program for 15 years. 

Now, researchers at Georgia Tech will collaborate with Georgia Quick Start to enhance these efforts by developing Extended Reality (XR) training programs, providing a scalable and experiential solution to meet the growing demand for training. 

“We have been so successful for so many years because we stay focused on relevance, flexibility, and responsiveness,” said Scott McMurray, deputy commissioner for Georgia Quick Start. “This partnership is an example of how Quick Start is able to develop and deliver effective training even for companies working on the leading edge of advanced manufacturing technologies.”

Extended Reality, Scaled Training

XR technologies use a combination of virtual and augmented reality to create immersive, interactive experiences. By simulating real-world manufacturing environments and processes, XR has the potential to allow trainees to practice and refine their skills in a controlled, risk-free setting through standardized training experiences. This not only enhances the learning experience but also ensures consistency in training quality across a large workforce.

“Virtual reality scales training by gamifying complex tasks and removing the need for costly or hazardous physical equipment. Augmented reality scales on-the-job training by providing adaptive, context-aware guidance exactly when and where it’s needed, reducing the need for expert supervision,” said manufacturing XR researcher Mohsen Moghaddam, Gary C. Butler Family associate professor in the H. Milton Stewart School of Industrial and Systems Engineering and the George W. Woodruff School of Mechanical Engineering. “Together, they make training more consistent, up-to-date, accessible, and safe, especially for workers who may hesitate to ask for assistance from peers or supervisors out of fear of judgment.”

The collaboration will leverage Moghaddam’s research and the AR/VR training space within the expanded Advanced Manufacturing Pilot Facility, providing a state-of-the-art environment for developing and deploying XR training technologies. Researchers from the Georgia Tech Manufacturing Institute (GTMI) and Georgia AIM(Artificial Intelligence in Manufacturing) will also play pivotal roles in the development of these training programs.

“Partnerships like these highlight the power of the integrated University of Georgia and Technical College System of Georgia’s workforce development ecosystem,” said Thomas Kurfess, Regents’ Professor and GTMI executive director. “Our country not only needs the creation of new jobs but also the skilled workforce to fill them. At Georgia Tech and GTMI, we are serving as an enabler of innovation in that workforce development.”