Anirudh Sivakumar (right) and Gabe Kwong led development of new gene-free biosensors for cancer detection.
Georgia Tech researchers have developed biosensors with advanced sleuthing skills and the technology may revolutionize cancer detection and monitoring.
The tiny detectives can identify key biological markers using logical reasoning inspired by the “AND” function in computers — like, when you need your username and password to log in. And unlike traditional biosensors comprised of genetic materials — cells, bits of DNA — these are made of manufactured molecules.
These new biosensors are more precise and simpler to manufacture, reducing the number of false positives and making them more practical for clinical use. And because the sensors are cell-free, there’s a reduced risk for immunogenic side effects.
“We think the accuracy and simplicity of our biosensors will lead to accessible, personalized, and effective treatments, ultimately saving lives,” said Gabe Kwong, associate professor and Robert A. Milton Endowed Chair in the Wallace H. Coulter Department of Biomedical Engineering, who led the study, published this month in Nature Nanotechnology.
Breaking With Tradition
The researchers set out to address the limitations in current biosensors for cancer, like the ones designed for CAR-T cells to allow them to recognize tumor cells. These advanced biosensors are made of genetic material, and there is growing interest to reduce the potential for off-target toxicity by using Boolean “AND-gate” computer logic. That means they’re designed to release a signal only when two specific conditions are met.
“Traditionally, these biosensors involve genetic engineering using cell-based systems, which is a complex, time-consuming, and expensive process,” said Kwong.
So, his team developed biosensors made of iron oxide nanoparticles and special molecules called cyclic peptides. Synthesizing nanomaterials and peptides is a simpler, less costly process than genetic engineering, according to Kwong, “which means we can likely achieve large-scale, economical production of high-precision biosensors.”
Unlocking the AND-gate
Biosensors detect cancer signals and track treatment progress by turning biological signals into readable outputs for doctors. With AND-gate logic, two distinct inputs are required for an output.
Accordingly, the researchers engineered cyclic peptides — small amino acid chains — to respond only when they encounter two specific types of enzymes, proteases called granzyme B (secreted by the immune system) and matrix metalloproteinase (from cancer cells). The peptides generate a signal when both proteases are present and active.
Think of a high-security lock that needs two unique keys to open. In this scenario, the peptides are the lock, activating the sensor signal only when cancer is present and being confronted by the immune system.
“Our peptides allow for greater accuracy in detecting cancer activity,” said the study’s lead author, Anirudh Sivakumar, a postdoctoral researcher in Kwong’s Laboratory for Synthetic Immunity. “It’s very specific, which is important for knowing when immune cells are targeting and killing tumor cells.”
Super Specific
In animal studies, the biosensors successfully distinguished between tumors that responded to a common cancer treatment called immune checkpoint blockade therapy — ICBT, which enhances the immune system — from tumors that resisted treatment.
During these tests, the sensors also demonstrated their ability to avoid false signals from other, unrelated health issues, such as when the immune system confronted a flu infection in the lungs, away from the tumor.
“This level of specificity can be game changing,” Kwong said. “Imagine being able to identify which patients are responding to the therapy early in their treatment. That would save time and improve patient outcomes.”
The first step toward this simpler, precise form of cancer diagnostics began with an ambitious but humble ($50,000) seed grant from the Petit Institute for Bioengineering and Bioscience five years ago for a collaboration between Kwong’s lab and the lab of M.G. Finn, professor and chair in the School of Chemistry and Biochemistry.
It evolved into a multi-institutional project supported by grants from the National Science Foundation and National Institutes of Health that included researchers from the University of California-Riverside, as well as Georgia Tech faculty researchers Finn and Peng Qiu, associate professor in the Coulter Department.
“The progression of the research, from an initial seed grant all the way to animal studies, was very smooth,” Kwong said. “Ultimately, a collaborative, multidisciplinary effort turned our early vision into something that could have a great impact in healthcare.”
Citation: Anirudh Sivakumar, Hathaichanok Phuengkham, Hitha Rajesh, Quoc D. Mac, Leonard C. Rogers, Aaron D. Silva Trenkle, Swapnil Subhash Bawage, Robert Hincapie, Zhonghan Li, Sofia Vainikos, Inho Lee, Min Xue, Peng Qiu, M. G. Finn, Gabriel A. Kwong. “AND-gated protease-activated nanosensors for programmable detection of anti-tumour immunity.” Nature Nanotechnology (January 2025). https://doi.org/10.1038/s41565-024-01834-8
Funding: This research was supported in part by National Institutes of Health (NIH) grants 5U01CA265711, 5R01CA237210, 1DP2HD091793, and 5DP1CA280832.
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Jerry Grillo
Glycine, one of the critical amino acids that the system coverts carbon dioxide into. (Image Credit: NASA)
Professor Pamela Peralta-Yahya
Ph.D. Student Shaafique Chowdhury, first author of the study.
Ph.D. Student Ray Westerberg
“Part of what makes a cell-free system so efficient,” Westenberg says, “is that it can use cellular enzymes without needing the cells themselves. By generating the enzymes and combining them in the lab, the system can directly convert carbon dioxide into the desired chemicals.”
Amino acids are essential for nearly every process in the human body. Often referred to as ‘the building blocks of life,’ they are also critical for commercial use in products ranging from pharmaceuticals and dietary supplements, to cosmetics, animal feed, and industrial chemicals.
And while our bodies naturally make amino acids, manufacturing them for commercial use can be costly — and that process often emits greenhouse gasses like carbon dioxide (CO2).
In a landmark study, a team of researchers has created a first-of-its kind methodology for synthesizing amino acids that uses more carbon than it emits. The research also makes strides toward making the system cost-effective and scalable for commercial use.
“To our knowledge, it’s the first time anyone has synthesized amino acids in a carbon-negative way using this type of biocatalyst,” says lead corresponding author Pamela Peralta-Yahya, who emphasizes that the system provides a win-win for industry and environment. “Carbon dioxide is readily available, so it is a low-cost feedstock — and the system has the added bonus of removing a powerful greenhouse gas from the atmosphere, making the synthesis of amino acids environmentally friendly, too.”
The study, “Carbon Negative Synthesis of Amino Acids Using a Cell-Free-Based Biocatalyst,” published today in ACS Synthetic Biology, is publicly available. The research was led by Georgia Tech in collaboration with the University of Washington, Pacific Northwest National Laboratory, and the University of Minnesota.
The Georgia Tech research contingent includes Peralta-Yahya, a professor with joint appointments in the School of Chemistry and Biochemistry and School of Chemical and Biomolecular Engineering (ChBE); first author Shaafique Chowdhury, a Ph.D. student in ChBE; Ray Westenberg, a Ph.D student in Bioengineering; and Georgia Tech alum Kimberly Wennerholm (B.S. ChBE ’23).
Costly chemicals
There are two key challenges to synthesizing amino acids on a large scale: the cost of materials, and the speed at which the system can generate amino acids.
While many living systems like cyanobacteria can synthesize amino acids from CO2, the rate at which they do it is too slow to be harnessed for industrial applications, and these systems can only synthesize a limited number of chemicals.
Currently, most commercial amino acids are made using bioengineered microbes. “These specially designed organisms convert sugar or plant biomass into fuel and chemicals,” explains first author Chowdhury, “but valuable food resources are consumed if sugar is used as the feedstock — and pre-processing plant biomass is costly.” These processes also release CO2 as a byproduct.
Chowdhury says the team was curious “if we could develop a commercially viable system that could use carbon dioxide as a feedstock. We wanted to build a system that could quickly and efficiently convert CO2 into critical amino acids, like glycine and serine.”
The team was particularly interested in what could be accomplished by a ‘cell-free’ system that leveraged some process of a cellular system — but didn’t actually involve living cells, Peralta-Yahya says, adding that systems using living cells need to use part of their CO2 to fuel their own metabolic processes, including cell growth, and have not yet produced sufficient quantities of amino acids.
“Part of what makes a cell-free system so efficient,” Westenberg explains, “is that it can use cellular enzymes without needing the cells themselves. By generating the enzymes and combining them in the lab, the system can directly convert carbon dioxide into the desired chemicals. Because there are no cells involved, it doesn’t need to use the carbon to support cell growth — which vastly increases the amount of amino acids the system can produce.”
A novel solution
While scientists have used cell-free systems before, one of the necessary chemicals, the cell lysate biocatalyst, is extremely costly. For a cell-free system to be economically viable at scale, the team needed to limit the amount of cell lysate the system needed.
After creating the ten enzymes necessary for the reaction, the team attempted to dilute the biocatalyst using a technique called ‘volumetric expansion.’ “We found that the biocatalyst we used was active even after being diluted 200-fold,” Peralta-Yahya explains. “This allows us to use significantly less of this high-cost material — while simultaneously increasing feedstock loading and amino acid output.”
It’s a novel application of a cell-free system, and one with the potential to transform both how amino acids are produced, and the industry’s impact on our changing climate.
“This research provides a pathway for making this method cost-effective and scalable,” Peralta-Yahya says. “This system might one day be used to make chemicals ranging from aromatics and terpenes, to alcohols and polymers, and all in a way that not only reduces our carbon footprint, but improves it.”
Funding: Advanced Research Project Agency-Energy (ARPA-E), U.S. Department of Energy and the U.S. Department of Energy, Office of Science, Biological and Environmental Research Program.
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Written by Selena Langner
W. Hong Yeo is leading a $3 million NSF research training program to develop a new generation of engineers focused on creating sustainable medical devices.
Georgia Tech researcher W. Hong Yeo has been awarded a $3 million grant to help develop a new generation of engineers and scientists in the field of sustainable medical devices.
“The workforce that will emerge from this program will tackle a global challenge through sustainable innovations in device design and manufacturing,” said Yeo, Woodruff Faculty Fellow and associate professor in the George W. Woodruff School of Mechanical Engineering and the Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech and Emory University.
The funding, from the National Science Foundation (NSF) Research Training (NRT) program, will address the environmental impacts resulting from the mass production of medical devices, including the increase in material waste and greenhouse gas emissions.
Under Yeo’s leadership, the Georgia Tech team comprises multidisciplinary faculty: Andrés García (bioengineering), HyunJoo Oh (industrial design and interactive computing), Lewis Wheaton (biology), and Josiah Hester (sustainable computing). Together, they’ll train 100 graduate students, including 25 NSF-funded trainees, who will develop reuseable, reliable medical devices for a range of uses.
“We plan to educate students on how to develop medical devices using biocompatible and biodegradable materials and green manufacturing processes using low-cost printing technologies,” said Yeo. “These wearable and implantable devices will enhance disease diagnosis, therapeutics, rehabilitation, and health monitoring.”
Students in the program will be challenged by a comprehensive, multidisciplinary curriculum, with deep dives into bioengineering, public policy, physiology, industrial design, interactive computing, and medicine. And they’ll get real-world experience through collaborations with clinicians and medical product developers, working to create devices that meet the needs of patients and care providers.
The Georgia Tech NRT program aims to attract students from various backgrounds, fostering a diverse, inclusive environment in the classroom — and ultimately in the workforce.
The program will also introduce a new Ph.D. concentration in smart medical devices as part of Georgia Tech's bioengineering program, and a new M.S. program in the sustainable development of medical devices. Yeo also envisions an academic impact that extends beyond the Tech campus.
“Collectively, this NRT program's curriculum, combining methods from multiple domains, will help establish best practices in many higher education institutions for developing reliable and personalized medical devices for healthcare,” he said. “We’d like to broaden students' perspectives, move past the current technology-first mindset, and reflect the needs of patients and healthcare providers through sustainable technological solutions.”
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Jerry Grillo
Ankur Singh has developed a new way of programming T cells that retains their naïve state, making them better fighters. — Photo by Jerry Grillo
This is an image of a T cell on a nanowire array. The arrow indicates where a nanowire has penetrated the cell, delivering therapeutic miRNA.
Adoptive T-cell therapy has revolutionized medicine. A patient’s T-cells — a type of white blood cell that is part of the body’s immune system — are extracted and modified in a lab and then infused back into the body, to seek and destroy infection, or cancer cells.
Now Georgia Tech bioengineer Ankur Singh and his research team have developed a method to improve this pioneering immunotherapy.
Their solution involves using nanowires to deliver therapeutic miRNA to T-cells. This new modification process retains the cells’ naïve state, which means they’ll be even better disease fighters when they’re infused back into a patient.
“By delivering miRNA in naïve T cells, we have basically prepared an infantry, ready to deploy,” Singh said. “And when these naïve cells are stimulated and activated in the presence of disease, it’s like they’ve been converted into samurais.”
Lean and Mean
Currently in adoptive T-cell therapy, the cells become stimulated and preactivated in the lab when they are modified, losing their naïve state. Singh’s new technique overcomes this limitation. The approach is described in a new study published in the journal Nature Nanotechnology.
“Naïve T-cells are more useful for immunotherapy because they have not yet been preactivated, which means they can be more easily manipulated to adopt desired therapeutic functions,” said Singh, the Carl Ring Family Professor in the Woodruff School of Mechanical Engineering and the Wallace H. Coulter Department of Biomedical Engineering.
The raw recruits of the immune system, naïve T-cells are white blood cells that haven’t been tested in battle yet. But these cellular recruits are robust, impressionable, and adaptable — ready and eager for programming.
“This process creates a well-programmed naïve T-cell ideal for enhancing immune responses against specific targets, such as tumors or pathogens,” said Singh.
The precise programming naïve T-cells receive sets the foundational stage for a more successful disease fighting future, as compared to preactivated cells.
Giving Fighter Cells a Boost
Within the body, naïve T-cells become activated when they receive a danger signal from antigens, which are part of disease-causing pathogens, but they send a signal to T-cells that activate the immune system.
Adoptive T-cell therapy is used against aggressive diseases that overwhelm the body’s defense system. Scientists give the patient’s T-cells a therapeutic boost in the lab, loading them up with additional medicine and chemically preactivating them.
That’s when the cells lose their naïve state. When infused back into the patient, these modified T-cells are an effective infantry against disease — but they are prone to becoming exhausted. They aren’t samurai. Naïve T-cells, though, being the young, programmable recruits that they are, could be.
The question for Singh and his team was: How do we give cells that therapeutic boost without preactivating them, thereby losing that pristine, highly suggestable naïve state? Their answer: Nanowires.
NanoPrecision: The Pointed Solution
Singh wanted to enhance naïve T-cells with a dose of miRNA. miRNA is a molecule that, when used as a therapeutic, works as a kind of volume knob for genes, turning their activity up or down to keep infection and cancer in check. The miRNA for this study was developed in part by the study’s co-author, Andrew Grimson of Cornell University.
“If we could find a way to forcibly enter the cells without damaging them, we could achieve our goal to deliver the miRNA into naïve T cells without preactivating them,” Singh explained.
Traditional modification in the lab involves binding immune receptors to T-cells, enabling the uptake of miRNA or any genetic material (which results in loss of the naïve state). “But nanowires do not engage receptors and thus do not activate cells, so they retain their naïve state,” Singh said.
The nanowires, silicon wafers made with specialized tools at Georgia Tech’s Institute for Electronics and Nanotechnology, form a fine needle bed. Cells are placed on the nanowires, which easily penetrate the cells and deliver their miRNA over several hours. Then the cells with miRNA are flushed out from the tops of the nanowires, activated, eventually infused back into the patient. These programmed cells can kill enemies efficiently over an extended time period.
“We believe this approach will be a real gamechanger for adoptive immunotherapies, because we now have the ability to produce T-cells with predictable fates,” says Brian Rudd, a professor of immunology at Cornell University, and co-senior author of the study with Singh.
The researchers tested their work in two separate infectious disease animal models at Cornell for this study, and Singh described the results as “a robust performance in infection control.”
In the next phase of study, the researchers will up the ante, moving from infectious disease to test their cellular super soldiers against cancer and move toward translation to the clinical setting. New funding from the Georgia Clinical & Translational Science Alliance is supporting Singh’s research.
CITATION: Kristel J. Yee Mon, Sungwoong Kim, Zhonghao Dai, Jessica D. West, Hongya Zhu5, Ritika Jain, Andrew Grimson, Brian D. Rudd, Ankur Singh. “Functionalized nanowires for miRNA-mediated therapeutic programming of naïve T cells,” Nature Nanotechnology.
FUNDING: Curci Foundation, NSF (EEC-1648035, ECCS-2025462, ECCS-1542081), NIH (5R01AI132738-06, 1R01CA266052-01, 1R01CA238745-01A1, U01CA280984-01, R01AI110613 and U01AI131348).
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Jerry Grillo
When he was in college, Hong Yeo's father died in his sleep from a heart attack, and Yeo changed his academic and research efforts as a result. Now, he and his research collaborators have developed a device that monitors vital signs during sleep, and it's the type of thing that may have helped doctors intervene in his father's illness if it had been available. This Sleep Scan device is a type of mask you can easily take on and off, and it has now been tested with human subjects and is close to being available commercially.
Hong Yeo’s father, Yonghyun Yeo, with his mother in Korea.
Taewoog Kang, a post-doctoral student in mechanical engineering, works to repair a tiny circuit in Hong Yeo’s lab on Georgia Tech’s campus.
The call from his mom is still vivid 20 years later. Moments this big and this devastating can define lives, and for Hong Yeo, today a Georgia Tech mechanical engineer, this call certainly did. Yeo was a 21-year-old in college studying car design when his mom called to tell him his father had died in his sleep. A heart attack claimed the life of the 49-year-old high school English teacher who had no history of heart trouble and no signs of his growing health threat. For the family, it was a crushing blow that altered each of their paths.
“It was an uncertain time for all of us,” said Yeo. “This loss changed my focus.”
For Yeo, thoughts and dreams of designing cars for Hyundai in Korea turned instead toward medicine. The shock of his father going from no signs of illness to gone forever developed into a quest for medical answers that might keep other families from experiencing the pain and loss his family did — or at least making it less likely to happen.
Yeo’s own research and schooling in college pointed out a big problem when it comes to issues with sleep and how our bodies’ systems perform — data. He became determined to invent a way to give medical doctors better information that would allow them to spot a problem like his father’s before it became life-threatening.
His answer: a type of wearable sleep data system. Now very close to being commercially available, Yeo’s device comes after years of working on the materials and electronics for an easy-to-wear, comfortable mask that can gather data about sleep over multiple days or even weeks, allowing doctors to catch sporadic heart problems or other issues. Different from some of the bulky devices with straps and cords currently available for at-home heart monitoring, it offers the bonuses of ease of use and comfort, ensuring little to no alteration to users’ bedtime routine or wear. This means researchers can collect data from sleep patterns that are as close to normal sleep as possible.
“Most of the time now, gathering sleep data means the patient must come to a lab or hospital for sleep monitoring. Of course, it’s less comfortable than home, and the devices patients must wear make it even less so. Also, the process is expensive, so it’s rare to get multiple nights of data,” says Audrey Duarte, University of Texas human memory researcher.
Duarte has been working with Yeo on this system for more than 10 years. She says there are so many mental and physical health outcomes tied to sleep that good, long-term data has the potential to have tremendous impact.
“The results we’ve seen are incredibly encouraging, related to many things —from heart issues to areas I study more closely like memory and Alzheimer’s,” said Duarte.
Yeo’s device may not have caught the arrhythmia that caused his father’s heart attack, but nights or weeks of data would have made effective medical intervention much more likely.
Inspired by his own family’s loss, Yeo’s life’s work has become a tool of hope for others.
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Emory University and Georgia Institute of Technology researchers are using a $2.46 million grant to test and continue developing a wearable BioPatch for farmworkers and others who work outside, funded by the National Institute of Environmental Health Sciences. This BioPatch will use multiple sensors to predict heat-related illnesses, dehydration, and acute kidney injury. By transmitting data to a smart phone or other device, artificial intelligence tools will provide real-time warnings to workers with the goal of reducing health risks associated with occupational heat exposure.
Researchers with Georgia Tech and Emory University are field testing a new device that could help protect people who work outside from heat related injury. It’s a skin patch you can wear while working that sends detailed information to a smartphone or other device about important health markers like skin hydration and body temperature. The device takes different measurements than health wearables on the market currently and will be paired with an artificial intelligence program to predict health hazards. The team is calling the device BioPatch, and it’s being put to the test with landscaping crews. Researchers hope use of the device can guide better decisions about working in the heat.
The project involves collaboration between principal investigators Vicki Hertzberg from Emory University, W. Hong Yeo from Georgia Tech, and Li Xiong from Emory University. Their expertise spans statistics, mechanical and biomedical engineering, and computer science, respectively. Roxana Chicas of the Emory School of Nursing and Jeff Sands of the Emory School of Medicine, along with members of the Farmworker Association of Florida, are also part of the team. This video shows the device and data collection during a key component of testing during the summer.
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The Institute for Data Engineering and Science, in conjunction with several Interdisciplinary Research Institutes (IRIs) at Georgia Tech, have awarded seven teams of researchers from across the Institute a total of $105,000 in seed funding geared to better position Georgia Tech to perform world-class interdisciplinary research in data science and artificial intelligence development and deployment.
The goals of the funded proposals include identifying prominent emerging research directions on the topic of AI, shaping IDEaS future strategy in the initiative area, building an inclusive and active community of Georgia Tech researchers in the field that potentially include external collaborators, and identifying and preparing groundwork for competing in large-scale grant opportunities in AI and its use in other research fields.
Below are the 2023 recipients and the co-sponsoring IRIs:
Proposal Title: "AI for Chemical and Materials Discovery" + “AI in Microscopy Thrust”
PI: Victor Fung, CSE | Vida Jamali, ChBE| Pan Li, ECE | Amirali Aghazadeh Mohandesi, ECE
Award: $20k (co-sponsored by IMat)
Overview: The goal of this initiative is to bring together expertise in machine learning/AI, high-throughput computing, computational chemistry, and experimental materials synthesis and characterization to accelerate material discovery. Computational chemistry and materials simulations are critical for developing new materials and understanding their behavior and performance, as well as aiding in experimental synthesis and characterization. Machine learning and AI play a pivotal role in accelerating material discovery through data-driven surrogate models, as well as high-throughput and automated synthesis and characterization.
Proposal Title: " AI + Quantum Materials”
PI: Zhigang JIang, Physics | Martin Mourigal, Physics
Award: $20k (Co-Sponsored by IMat)
Overview: Zhigang Jiang is currently leading an initiative within IMAT entitled “Quantum responses of topological and magnetic matter” to nurture multi-PI projects. By crosscutting the IMAT initiative with this IDEAS call, we propose to support and feature the applications of AI on predictive and inverse problems in quantum materials. Understanding the limit and capabilities of AI methodologies is a huge barrier of entry for Physics students, because researchers in that field already need heavy training in quantum mechanics, low-temperature physics and chemical synthesis. Our most pressing need is for our AI inclined quantum materials students to find a broader community to engage with and learn. This is the primary problem we aim to solve with this initiative.
PI: Jeffrey Skolnick, Bio Sci | Chao Zhang, CSE
Proposal Title: Harnessing Large Language Models for Targeted and Effective Small Molecule 4 Library Design in Challenging Disease Treatment
Award: $15k (co-sponsored by IBB)
Overview: Our objective is to use large language models (LLMs) in conjunction with AI algorithms to identify effective driver proteins, develop screening algorithms that target appropriate binding sites while avoiding deleterious ones, and consider bioavailability and drug resistance factors. LLMs can rapidly analyze vast amounts of information from literature and bioinformatics tools, generating hypotheses and suggesting molecular modifications. By bridging multiple disciplines such as biology, chemistry, and pharmacology, LLMs can provide valuable insights from diverse sources, assisting researchers in making informed decisions. Our aim is to establish a first-in-class, LLM driven research initiative at Georgia Tech that focuses on designing highly effective small molecule libraries to treat challenging diseases. This initiative will go beyond existing AI approaches to molecule generation, which often only consider simple properties like hydrogen bonding or rely on a limited set of proteins to train the LLM and therefore lack generalizability. As a result, this initiative is expected to consistently produce safe and effective disease-specific molecules.
PI: Yiyi He, School of City & Regional Plan | Jun Rentschler, World Bank
Proposal Title: “AI for Climate Resilient Energy Systems”
Award: $15k (co-sponsored by SEI)
Overview: We are committed to building a team of interdisciplinary & transdisciplinary researchers and practitioners with a shared goal: developing a new framework which model future climatic variations and the interconnected and interdependent energy infrastructure network as complex systems. To achieve this, we will harness the power of cutting-edge climate model outputs, sourced from the Coupled Model Intercomparison Project (CMIP), and integrate approaches from Machine Learning and Deep Learning models. This strategic amalgamation of data and techniques will enable us to gain profound insights into the intricate web of future climate-change-induced extreme weather conditions and their immediate and long-term ramifications on energy infrastructure networks. The seed grant from IDEaS stands as the crucial catalyst for kick-starting this ambitious endeavor. It will empower us to form a collaborative and inclusive community of GT researchers hailing from various domains, including City and Regional Planning, Earth and Atmospheric Science, Computer Science and Electrical Engineering, Civil and Environmental Engineering etc. By drawing upon the wealth of expertise and perspectives from these diverse fields, we aim to foster an environment where innovative ideas and solutions can flourish. In addition to our internal team, we also have plans to collaborate with external partners, including the World Bank, the Stanford Doerr School of Sustainability, and the Berkeley AI Research Initiative, who share our vision of addressing the complex challenges at the intersection of climate and energy infrastructure.
PI: Jian Luo, Civil & Environmental Eng | Yi Deng, EAS
Proposal Title: “Physics-informed Deep Learning for Real-time Forecasting of Urban Flooding”
Award: $15k (co-sponsored by BBISS)
Overview: Our research team envisions a significant trend in the exploration of AI applications for urban flooding hazard forecasting. Georgia Tech possesses a wealth of interdisciplinary expertise, positioning us to make a pioneering contribution to this burgeoning field. We aim to harness the combined strengths of Georgia Tech's experts in civil and environmental engineering, atmospheric and climate science, and data science to chart new territory in this emerging trend. Furthermore, we envision the potential extension of our research efforts towards the development of a real-time hazard forecasting application. This application would incorporate adaptation and mitigation strategies in collaboration with local government agencies, emergency management departments, and researchers in computer engineering and social science studies. Such a holistic approach would address the multifaceted challenges posed by urban flooding. To the best of our knowledge, Georgia Tech currently lacks a dedicated team focused on the fusion of AI and climate/flood research, making this initiative even more pioneering and impactful.
Proposal Title: “AI for Recycling and Circular Economy”
PI: Valerie Thomas, ISyE and PubPoly | Steven Balakirsky, GTRI
Award: $15k (co-sponsored by BBISS)
Overview: Most asset management and recycling use technology that has not changed for decades. The use of bar codes and RFID has provided some benefits, such as for retail returns management. Automated sorting of recyclables using magnets, eddy currents, and laser plastics identification has improved municipal recycling. Yet the overall field has been challenged by not-quite-easy-enough identification of products in use or at end of life. AI approaches, including computer vision, data fusion, and machine learning provide the additional capability to make asset management and product recycling easy enough to be nearly autonomous. Georgia Tech is well suited to lead in the development of this application. With its strength in machine learning, robotics, sustainable business, supply chains and logistics, and technology commercialization, Georgia Tech has the multi-disciplinary capability to make this concept a reality, in research and in commercial application.
Proposal Title: “Data-Driven Platform for Transforming Subjective Assessment into Objective Processes for Artistic Human Performance and Wellness”
PI: Milka Trajkova, Research Scientist/School of Literature, Media, Communication | Brian Magerko, School of Literature, Media, Communication
Award: $15k (co-sponsored by IPaT)
Overview: Artistic human movement at large, stands at the precipice of a data-driven renaissance. By leveraging novel tools, we can usher in a transparent, data-driven, and accessible training environment. The potential ramifications extend beyond dance. As sports analytics have reshaped our understanding of athletic prowess, a similar approach to dance could redefine our comprehension of human movement, with implications spanning healthcare, construction, rehabilitation, and active aging. Georgia Tech, with its prowess in AI, HCI, and biomechanics is primed to lead this exploration. To actualize this vision, we propose the following research questions with ballet as a prime example of one of the most complex types of artistic movements: 1) What kinds of data - real-time kinematic, kinetic, biomechanical, etc. captured through accessible off-the-shelf technologies, are essential for effective AI assessment in ballet education for young adults?; 2) How can we design and develop an end-to-end ML architecture that assesses artistic and technical performance?; 3) What feedback elements (combination of timing, communication mode, feedback nature, polarity, visualization) are most effective for AI- based dance assessment?; and 4) How does AI-assisted feedback enhance physical wellness, artistic performance, and the learning process in young athletes compared to traditional methods?
- Christa M. Ernst
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Christa M. Ernst | Research Communications Program Manager
Robotics | Data Engineering | Neuroengineering
christa.ernst@research.gatech.edu
Professor Omer Inan is set to take the stage at the upcoming TEDxAtlanta 2023: We Rise event on May 19.
Professor Omer Inan is set to take the stage at the upcoming TEDxAtlanta 2023: We Rise event on May 19.
As the Linda J. and Mark C. Smith Chair in bioscience and bioengineering in Tech’s School of Electrical and Computer Engineering (ECE), Inan designs clinically relevant medical devices and systems and translates them from the lab to patient care applications. In his talk, Inan will be discussing his groundbreaking research on wearable healthcare technologies and the potential they hold for revolutionizing the field.
Inan is a member of the prestigious Medical and Biological Engineering (AIMBE) College of Fellows (elected in 2022) for his “outstanding contributions to the non-invasive assessment of the mechanical aspects of cardiovascular health and performance using wearable devices.” Additional achievements include an Academy Award for Technical Achievement from The Academy of Motion Picture Arts and Sciences (The Oscars, 2021), the Georgia Power Professor of Excellence for the College of Engineering (2019), and the National Science Foundation Faculty Early Career Development Program award (NSF CAREER, 2018).
TEDxAtlanta 2023: WE RISE brings together an impressive group of participants from diverse backgrounds, experiences, and perspectives. The speakers include entrepreneurs, activists, educators, artists, scientists, and many other changemakers who have risen above challenges to make a positive impact on the world.
The event's participants will share their stories and insights on how they have overcome adversity, embraced innovation, and challenged the status quo to make a difference in their communities and beyond. Through their talks, they will inspire and empower attendees to rise above their own challenges and take action towards creating a better future for all.
TEDxAtlanta 2023: WE RISE will take place on Friday, May 19 from 9 a.m. – 6:30 p.m. at the Rialto Center for the Arts (80 Forsyth Street Northwest Atlanta, GA 30303). Learn more and purchase tickets at tedxatlanta.com.
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Dan Watson
An aerial view of the SPRUCE enclosure.
Sphagnum mosses were taken from different SPRUCE enclosures and incubated in glass jars for the study (Photo Jennifer Glass).
A closeup of a member of the research team holding Sphagnum moss, one of the key drivers of carbon sequestration in peatlands. (Photo Jennifer Glass).
If you’re an avid gardener, you may have considered peat moss — decomposed Sphagnum moss that helps retain moisture in soil — to enhance your home soil mixture. And while the potting medium can help plants thrive, it’s also a key component of peatlands: wetlands characterized by a thick layer of water-saturated, carbon-rich peat beneath living Sphagnum moss, trees, and other plant life.
These ecosystems cover just 3% of Earth’s land area, but “peatlands store over one-third of all soil carbon on the planet,” explains Joel Kostka, professor and associate chair of Research in the School of Biological Sciences at Georgia Tech.
This carbon storage is supported in large part by microbes. Two microbial processes in particular — nitrogen fixation and methane oxidation — strike a delicate balance, working together to give Sphagnum mosses access to critical nutrients in nutrient-depleted peatlands.
The coupling of these two processes is often referred to as the “missing link” of nutrient cycling in peatlands. Yet, how these processes will respond to changing climates along northern latitudes is unclear.
“There are tropical peatlands — but the majority of peatlands are in northern environments.” notes Caitlin Petro, a research scientist who works with Kostka in Biological Sciences at Tech. “And those are going to be hit harder by climate change.”
Kostka and Petro recently led a collaborative study to investigate how this critical type of ecosystem (and the “missing link” of microbial processes that support it) may react to the increased temperature and carbon dioxide levels predicted to come with climate change. The team, which also includes researchers from the Oak Ridge National Laboratory (ORNL), Florida State University, and the University of Tennessee, Knoxville, just published their work in the scientific journal Global Change Biology.
By testing the effects of increasing temperature and carbon dioxide on the growth of Sphagnum moss, its associated microbiome, and overall ecosystem health, Kostka and Petro say computational models will be better equipped to predict the effects of climate change.
“Down the road,” Kostka added, “we hope the results can be used by environmental managers and governments to adaptively manage or geoengineer peatlands to thrive in a warmer world.”
Raising the heat
To see how northern peatlands will react to climate change, the team, which also included School of Earth and Atmospheric Sciences Associate Professor Jennifer Glass, turned to the ORNL Spruce and Peatland Responses Under Changing Environments (SPRUCE) experiment — a unique field lab in northern Minnesota where the team warms peat bogs and experimentally changes the amount of carbon dioxide in the atmosphere.
Starting in 2016, the team exposed different parts of SPRUCE’s experimental peatlands to a gradient of higher temperatures ranging from an increase of 0°C to 9°C, capturing the Intergovernmental Panel on Climate Change models’ predicted 4°C to 6°C increase in northern regions by 2100.
The moss’s reaction was significant. Although nearly 100% of the bog’s surface was covered in moss at the beginning of the experiment, moss coverage dropped with each increase in temperature, plummeting to less than 15% in the warmest conditions.
Critically, the two microbial processes that had previously been consistently linked fell out of sync at higher temperatures.
“Peatlands are extremely nutrient-poor and microbial nitrogen fixation represents a major nitrogen input to the ecosystem,” Kostka explained. Fixing nitrogen is the process of turning atmospheric nitrogen into an organic compound that the moss can use for photosynthesis, while methane oxidation allows the moss to use methane released from decomposing peat as energy. “Methane oxidation acts to fuel nitrogen fixation while scavenging a really important greenhouse gas before it is released to the atmosphere. This study shows that these two processes, which are catalyzed by the Sphagnum microbiome, become disconnected as the moss dies.”
“These processes occurring together are really important for the community,” Petro explained. Yet many microbes that are able to both fix nitrogen and oxidize methane were absent in the mosses collected from higher temperature enclosures. And while elevated carbon dioxide levels appeared to offset some of the changes in nitrogen cycling caused by warming, the decoupling of these processes remained.
“These treatments are altering a fairly well-defined and consistent plant microbiome that we find in many different environments, and that has this consistent function,” Petro explained. “It's like a complete functional shift in the community.”
Though it’s not clear which of these changes — the moss dying or the altered microbial activity — is driving the other, it is clear that with warmer temperatures and higher carbon dioxide levels comes a cascade of unpredictable outcomes for peat bogs.
“In addition to the direct effects of climate warming on ecosystem function,” Petro adds, “it will also introduce all of these off-shooting effects that will impact peatlands in ways that we didn't predict before.”
This work was supported by the National Science Foundation (DEB grant no. 1754756). The SPRUCE project is supported by the U.S. Department of Energy's Office of Science, Biological, and Environmental Research (DOE BER) and the USDA Forest Service.
DOI: https://doi.org/10.1111/gcb.16651
Citation: Petro, C., et al. Climate drivers alter nitrogen availability in surface peat and decouple N2 fixation from CH4 oxidation in the Sphagnum moss microbiome. Global Change Biology. (2023).
Aerial Photo: Hanson, P.J., M.B. Krassovski, and L.A. Hook. 2020. SPRUCE S1 Bog and SPRUCE Experiment Aerial Photographs. Oak Ridge National Laboratory, TES SFA, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A. https://doi.org/10.3334/CDIAC/spruce.012 (UAV image number 0050 collected on October 4, 2020).
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Writer: Audra Davidson
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Director of Communications, College of Sciences
An innovative healthcare startup that just launched out of Georgia Tech uses artificial intelligence to predict how a patient’s heart will respond to a specific implant before the procedure beings.
The team’s groundbreaking research in cardiovascular engineering technology, led by Professor Prasad Dasi, is changing how the medical industry approaches heart care, giving a fresh perspective and a more successful outcome for heart surgeons and patients.
"The decisions that the cardiologists or surgeons make today can impact not only the immediate surgical procedure that they are going to have, but it will impact the rest of their patients’ lives" said Dasi, a professor and associate chair for undergraduate studies in the Coulter Department of Biomedical Engineering at Georgia Tech and Emory University. "Our technology helps doctors make a more informed decision on a patient-by-patient basis for the best possible outcome for those suffering from heart disease or needing a heart implant."
Choosing to Disclose the Heart Valve Technology
Through research commercialization, Dasi was able to license his technology and transform the way heart patients receive care. Dasi chose to take the innovative path and started his own company, Dasi Simulations, along with co-founder and CEO Teri Sirset, to commercialize and disclose the heart valve technology.
“After being able to secure some initial seed funding for our startup, it was time to acquire a licensing agreement from Georgia Tech,” Dasi recalled.
Dasi and Sirset realized that licensing this technology would be a crucial milestone in their journey of establishing a successful business, and they moved forward to disclose their invention to Georgia Tech’s Office of Technology Licensing (OTL).
Working with the Office of Technology Licensing
The Dasi Simulations heart valve technology was successfully licensed through the OTL in the summer of 2022. The licensing agreement was part of a larger inter-institutional agreement between Georgia Tech, Ohio State University, Piedmont Hospital, and Emory University. Dasi credits Raghupathy "Siva" Sivakumar, vice president of the Office of Commercialization at Georgia Tech, with providing great advice throughout the process, as well as the OTL team for creating a smooth licensing experience.
“I met with Siva, and he gave me so much good advice on navigating the aspects of getting into commercialization. He was a great mentor for me,” said Dasi. “I found working with the OTL to be pleasant and a relatively fast experience, and I would definitely encourage other professors and researchers to disclose their ideas. I think that is the first step and developing mentorships is also worthwhile and can lead to more successful advancements in technology.”
Seeing the Benefits of Licensing
As a result of becoming licensed, Dasi Simulations is already making waves in the medical industry with its game-changing heart valve technology. The product is in nearly 50 hospitals, and the device is expecting FDA clearance later this year. The startup currently employs 25 engineers, and a beta version of the product is generating revenue.
“I want to see this technology continue to become the standard of care because every patient deserves the best possible outcome,” said Dasi, reflecting on the next steps for the company now that it is officially licensed.
Dasi Simulation’s heart valve technology is accelerating the medical industry by increasing accessibility to better diagnostics and faster treatments. After years of hard work and dedication from Professor Dasi and Dasi Simulation, cardiovascular healthcare's future is brighter than ever.
“This is an exciting development for Dasi, Sirset, and Dasi Simulations LLC, and Georgia Tech. OTL is excited to have licensed this important research, and we all look forward to seeing how this new technology continues to evolve and help people with heart conditions,” said OTL Director Mary Albertson .
To learn more about Technology Licensing from Georgia Tech, please visit https://commercialization.gatech.edu/technology-licensing
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Lacey Cameron
lacey.cameron@gatech.edu