The Georgia Tech EcoCommons (Photo by Nick Hubbard)
The College of Sciences at Georgia Tech is proud to launch Science for Georgia’s Tomorrow, a new center focused on research that aims to improve life across the state of Georgia.
“From resilient communities and agriculture, to health and sustainable energy resources, Science for Georgia's Tomorrow will focus on improving the lives of Georgians and their communities,” Dean Susan Lozier says.
An expansion of the College’s strategic plan, Science for Georgia's Tomorrow — Sci4GT, for short — will serve as a statewide fulcrum, fostering research in direct service to Georgia cities, counties, and communities.
The center specifically addresses critical health and climate challenges throughout Georgia, and aims to pave the way for increased public-private partnerships. The initiative will also expand access — broadening participation opportunities for Georgia students and communities to engage with research.
The search for an inaugural faculty director has commenced, and will be followed by a dedicated cluster hire in 2025, funded by the Office of the Provost. Dean Lozier, who also serves as a professor in the School of Earth and Atmospheric Sciences, has reserved funds from the College of Sciences Betsy Middleton and John Clark Sutherland Dean’s Chair to initiate the center.
Selected from a pool of 17 faculty proposals, two dedicated faculty cluster hires will focus on improving the health of Georgians and Georgia’s communities — and the resilience of humans and ecosystems to current and anticipated climate change in the state. Appointments will be sought across the College’s six schools.
“These proposals address themes that are critically important right now for Georgia Tech research growth: sustainability and climate, along with health and well-being,” says Julia Kubanek, Vice President for Interdisciplinary Research at Georgia Tech and a professor in the School of Biological Sciences and the School of Chemistry and Biochemistry. “This is an opportunity for Georgia to be a model for the nation on how to solve health disparities.”
“These new cluster hires will strengthen the College’s existing research programs,” Lozier adds. “They will also facilitate large collaborations across campus, and educate the next generation of scientists who will tackle these problems in Georgia and beyond.”
An adjacent effort, the new College of Sciences Rising Tide Program, is selecting promising early-career scientists for a two-year virtual mentorship initiative.
The Rising Tide Program will work in tandem with the Sci4GT cluster hire, complementing the strong culture of mentorship in the College, while providing a pathway to support local research at the Institute.
“Rising Tide aims to help the College recruit scientists with professional or lived experiences in the Southeast — or focused on research with particular relevance to the Southeast,” explains Rising Tide Director Alex Robel, associate professor in the School of Earth and Atmospheric Sciences. “One of our key goals is to bring more faculty to Georgia Tech who can contribute to research and teaching that’s particularly relevant to communities in Georgia.”
“The reach of Georgia Tech is global,” Lozier adds. “Our fingerprints are on discoveries and innovations that benefit people and their communities around the world. As researchers at a leading public university in the state of Georgia, we are also cognizant of the responsibility and opportunity to focus our efforts more intently here at home.”
The College has launched an internal leadership search for the Science for Georgia’s Tomorrow center, with an expected appointment to be announced in February 2025. The inaugural director will have the opportunity to shape the direction of this new initiative by:
All faculty who hold a majority appointment within the College of Sciences are eligible and encouraged to apply. Learn more and apply via InfoReady.
Initial support for Sci4GT is generously provided by the College of Sciences Betsy Middleton and John Clark Sutherland Dean's Chair fund. Cluster hire funding has been awarded by Provost Steven W. McLaughlin.
Sci4GT will also seek funding from state, national and international organizations, private foundations, and government agencies to expand impact. Philanthropic support will also be sought in the form of professorships, programmatic support for the center, and seed funding.
Written by: Selena Langner
Media contact: Jess Hunt-Ralston
Georgia Tech researchers have created a dataset that trains computer models to understand nuances in human speech during financial earnings calls. The dataset provides a new resource to study how public correspondence affects businesses and markets.
SubjECTive-QA is the first human-curated dataset on question-answer pairs from earnings call transcripts (ECTs). The dataset teaches models to identify subjective features in ECTs, like clarity and cautiousness.
The dataset lays the foundation for a new approach to identifying disinformation and misinformation caused by nuances in speech. While ECT responses can be technically true, unclear or irrelevant information can misinform stakeholders and affect their decision-making.
Tests on White House press briefings showed that the dataset applies to other sectors with frequent question-and-answer encounters, notably politics, journalism, and sports. This increases the odds of effectively informing audiences and improving transparency across public spheres.
The intersecting work between natural language processing and finance earned the paper acceptance to NeurIPS 2024, the 38th Annual Conference on Neural Information Processing Systems. NeurIPS is one of the world’s most prestigious conferences on artificial intelligence (AI) and machine learning (ML) research.
"SubjECTive-QA has the potential to revolutionize nowcasting predictions with enhanced clarity and relevance,” said Agam Shah, the project’s lead researcher.
[MICROSITE: Georgia Tech at NeurIPS 2024]
“Its nuanced analysis of qualities in executive responses, like optimism and cautiousness, deepens our understanding of economic forecasts and financial transparency."
SubjECTive-QA offers a new means to evaluate financial discourse by characterizing language's subjective and multifaceted nature. This improves on traditional datasets that quantify sentiment or verify claims from financial statements.
The dataset consists of 2,747 Q&A pairs taken from 120 ECTs from companies listed on the New York Stock Exchange from 2007 to 2021. The Georgia Tech researchers annotated each response by hand based on six features for a total of 49,446 annotations.
The group evaluated answers on:
The Georgia Tech group validated their dataset by training eight computer models to detect and score these six features. Test models comprised of three BERT-based pre-trained language models (PLMs), and five popular large language models (LLMs) including Llama and ChatGPT.
All eight models scored the highest on the relevance and clarity features. This is attributed to domain-specific pretraining that enables the models to identify pertinent and understandable material.
The PLMs achieved higher scores on the clear, optimistic, specific, and cautious categories. The LLMs scored higher in assertiveness and relevance.
In another experiment to test transferability, a PLM trained with SubjECTive-QA evaluated 65 Q&A pairs from White House press briefings and gaggles. Scores across all six features indicated models trained on the dataset could succeed in other fields outside of finance.
"Building on these promising results, the next step for SubjECTive-QA is to enhance customer service technologies, like chatbots,” said Shah, a Ph.D. candidate studying machine learning.
“We want to make these platforms more responsive and accurate by integrating our analysis techniques from SubjECTive-QA."
SubjECTive-QA culminated from two semesters of work through Georgia Tech’s Vertically Integrated Projects (VIP) Program. The VIP Program is an approach to higher education where undergraduate and graduate students work together on long-term project teams led by faculty.
Undergraduate students earn academic credit and receive hands-on experience through VIP projects. The extra help advances ongoing research and gives graduate students mentorship experience.
Computer science major Huzaifa Pardawala and mathematics major Siddhant Sukhani co-led the SubjECTive-QA project with Shah.
Fellow collaborators included Veer Kejriwal, Abhishek Pillai, Rohan Bhasin, Andrew DiBiasio, Tarun Mandapati, and Dhruv Adha. All six researchers are undergraduate students studying computer science.
Sudheer Chava co-advises Shah and is the faculty lead of SubjECTive-QA. Chava is a professor in the Scheller College of Business and director of the M.S. in Quantitative and Computational Finance (QCF) program.
Chava is also an adjunct faculty member in the College of Computing’s School of Computational Science and Engineering (CSE).
"Leading undergraduate students through the VIP Program taught me the powerful impact of balancing freedom with guidance,” Shah said.
“Allowing students to take the helm not only fosters their leadership skills but also enhances my own approach to mentoring, thus creating a mutually enriching educational experience.”
Presenting SubjECTive-QA at NeurIPS 2024 exposes the dataset for further use and refinement. NeurIPS is one of three primary international conferences on high-impact research in AI and ML. The conference occurs Dec. 10-15.
The SubjECTive-QA team is among the 162 Georgia Tech researchers presenting over 80 papers at NeurIPS 2024. The Georgia Tech contingent includes 46 faculty members, like Chava. These faculty represent Georgia Tech’s Colleges of Business, Computing, Engineering, and Sciences, underscoring the pertinence of AI research across domains.
"Presenting SubjECTive-QA at prestigious venues like NeurIPS propels our research into the spotlight, drawing the attention of key players in finance and tech,” Shah said.
“The feedback we receive from this community of experts validates our approach and opens new avenues for future innovation, setting the stage for transformative applications in industry and academia.”
Bryant Wine, Communications Officer
bryant.wine@cc.gatech.edu
A new machine learning (ML) model from Georgia Tech could protect communities from diseases, better manage electricity consumption in cities, and promote business growth, all at the same time.
Researchers from the School of Computational Science and Engineering (CSE) created the Large Pre-Trained Time-Series Model (LPTM) framework. LPTM is a single foundational model that completes forecasting tasks across a broad range of domains.
Along with performing as well or better than models purpose-built for their applications, LPTM requires 40% less data and 50% less training time than current baselines. In some cases, LPTM can be deployed without any training data.
The key to LPTM is that it is pre-trained on datasets from different industries like healthcare, transportation, and energy. The Georgia Tech group created an adaptive segmentation module to make effective use of these vastly different datasets.
The Georgia Tech researchers will present LPTM in Vancouver, British Columbia, Canada, at the 2024 Conference on Neural Information Processing Systems (NeurIPS 2024). NeurIPS is one of the world’s most prestigious conferences on artificial intelligence (AI) and ML research.
“The foundational model paradigm started with text and image, but people haven’t explored time-series tasks yet because those were considered too diverse across domains,” said B. Aditya Prakash, one of LPTM’s developers.
“Our work is a pioneer in this new area of exploration where only few attempts have been made so far.”
[MICROSITE: Georgia Tech at NeurIPS 2024]
Foundational models are trained with data from different fields, making them powerful tools when assigned tasks. Foundational models drive GPT, DALL-E, and other popular generative AI platforms used today. LPTM is different though because it is geared toward time-series, not text and image generation.
The Georgia Tech researchers trained LPTM on data ranging from epidemics, macroeconomics, power consumption, traffic and transportation, stock markets, and human motion and behavioral datasets.
After training, the group pitted LPTM against 17 other models to make forecasts as close to nine real-case benchmarks. LPTM performed the best on five datasets and placed second on the other four.
The nine benchmarks contained data from real-world collections. These included the spread of influenza in the U.S. and Japan, electricity, traffic, and taxi demand in New York, and financial markets.
The competitor models were purpose-built for their fields. While each model performed well on one or two benchmarks closest to its designed purpose, the models ranked in the middle or bottom on others.
In another experiment, the Georgia Tech group tested LPTM against seven baseline models on the same nine benchmarks in a zero-shot forecasting tasks. Zero-shot means the model is used out of the box and not given any specific guidance during training. LPTM outperformed every model across all benchmarks in this trial.
LPTM performed consistently as a top-runner on all nine benchmarks, demonstrating the model’s potential to achieve superior forecasting results across multiple applications with less and resources.
“Our model also goes beyond forecasting and helps accomplish other tasks,” said Prakash, an associate professor in the School of CSE.
“Classification is a useful time-series task that allows us to understand the nature of the time-series and label whether that time-series is something we understand or is new.”
One reason traditional models are custom-built to their purpose is that fields differ in reporting frequency and trends.
For example, epidemic data is often reported weekly and goes through seasonal peaks with occasional outbreaks. Economic data is captured quarterly and typically remains consistent and monotone over time.
LPTM’s adaptive segmentation module allows it to overcome these timing differences across datasets. When LPTM receives a dataset, the module breaks data into segments of different sizes. Then, it scores all possible ways to segment data and chooses the easiest segment from which to learn useful patterns.
LPTM’s performance, enhanced through the innovation of adaptive segmentation, earned the model acceptance to NeurIPS 2024 for presentation. NeurIPS is one of three primary international conferences on high-impact research in AI and ML. NeurIPS 2024 occurs Dec. 10-15.
Ph.D. student Harshavardhan Kamarthi partnered with Prakash, his advisor, on LPTM. The duo are among the 162 Georgia Tech researchers presenting over 80 papers at the conference.
Prakash is one of 46 Georgia Tech faculty with research accepted at NeurIPS 2024. Nine School of CSE faculty members, nearly one-third of the body, are authors or co-authors of 17 papers accepted at the conference.
Along with sharing their research at NeurIPS 2024, Prakash and Kamarthi released an open-source library of foundational time-series modules that data scientists can use in their applications.
“Given the interest in AI from all walks of life, including business, social, and research and development sectors, a lot of work has been done and thousands of strong papers are submitted to the main AI conferences,” Prakash said.
“Acceptance of our paper speaks to the quality of the work and its potential to advance foundational methodology, and we hope to share that with a larger audience.”
Bryant Wine, Communications Officer
bryant.wine@cc.gatech.edu
Cybersecurity researchers have discovered new vulnerabilities that could provide criminals with wireless access to the computer systems in automobiles, aircraft, factories, and other cyber-physical systems.
The computers used in vehicles and other cyber-physical systems rely on a specialized internal network to communicate commands between electronics. Because it took place internally, it was traditionally assumed that attackers could only influence this network through physical access.
In collaboration with Hyundai, researchers from Georgia Tech’s Cyber-Physical Systems Security Research Lab (CPSec) observed that threat models used to evaluate the security of these technologies were outdated.
The team, led by Ph.D. student Zhaozhou Tang, found that vehicle technology advancements allowed attackers to launch new attacks, improve existing attacks, and circumvent current defense systems.
For example, Tang’s findings included the possibility for attackers to remotely compromise the computers used in cars and aircraft through Wi-Fi, cellular, Bluetooth, and other wireless channels.
“Our job was to thoroughly review existing information and find ways to protect against these attacks,” he said. “We found new threats and proposed a defense system that can protect against the new and old attacks.”
In response to their findings, the team developed ERACAN, the first comprehensive defense system against this new generation of attackers. Designed to detect new and old attacks, ERACAN can deploy defenses when necessary.
The system also classifies the attacks it reacts to, providing security experts with the tools for detailed analysis. It has a detection rate of 100% for all attacks launched by conventional methods and detects enhanced threat models 99.7% of the time.
The project received a distinguished paper award at the 2024 ACM Conference on Computer and Communications Security (CCS 24) held in Salt Lake City. Tang presented the paper at the October conference.
“This was Zhaozhou’s first paper in his Ph.D. program, and he deserves recognition for his groundbreaking work on automotive cybersecurity,” said Saman Zonouz, associate professor in the School of Cybersecurity and Privacy and the School of Electrical and Computer Engineering.
The U.S. Department of Homeland Security has designated the transportation sector as one of the nation’s 16 critical infrastructure sectors. Ensuring its security is vital to national security and public safety.
“Modern vehicles, which rely heavily on controller area networks for essential operations, are integral components of this infrastructure,” said Zonouz. “With the increasing sophistication of cyberthreats, safeguarding these systems has become critical to ensuring the resilience and security of transportation networks.”
This paper introduced to the scientific community the first comprehensive defense system to address advanced threats targeting vehicular controller area networks.
The CPSec team is putting the technology it has developed into practice in collaboration with Hyundai America Technical Center, Inc., which sponsors the work. Tang hopes ERACAN’s success will raise awareness of these new threats in the research community and industry.
“It will help them build future defenses,” he said. “We have demonstrated the best practice to defend against these attacks.”
Tang received his bachelor’s degree at Georgia Tech, where he first performed security-related work for the automobile industry. While working with Zonouz on his master’s degree, he decided to change course and pursue research initiatives like vehicle security in a Ph.D. program.
“It is interesting how it came full circle,” he said. “I will continue on this path of automobile security throughout my Ph.D.”
ERACAN: Defending Against an Emerging CAN Threat Model, was written by Zhaozhou Tang, Khaled Serag from the Qatar Computing Research Institute, Saman Zonouz, Berkay Celik and Dongyan Xu from Purdue University, and Raheem Beyah, professor and dean of the College of Engineering. The CPSec Lab is a collaboration between the School of Cybersecurity and Privacy and the School of Electrical and Computer Engineering.
John Popham
Communications Officer II
School of Cybersecurity and Privacy
Researchers are receiving more than $4 million from DARPA to develop a new framework to analyze and model sophisticated attacks on software.
A common tactic cybercriminals use is an exploit chain, a series of interconnected steps or vulnerabilities that attackers exploit to breach software systems. Each step leverages the capability achieved in the preceding step, forming a systematic pathway to compromise.
Recognizing the severity of this threat, researchers at the School of Cybersecurity and Privacy (SCP) at Georgia Tech will work with Trusted Science and Technology Inc. to turn Metrology for Assessing the Leverage of and Liability for Compromises (METALLIC) into a working prototype of a security modeling and assessment framework.
“We are developing a foundation framework to analyze and reason about cyber chains of exploits,” said Sukarno Mertoguno, SCP research professor and project lead.
“The structure we will implement in this project enables characterization and evaluation of exploit components, semi-automated repair, and adaptation of the chain to the changes in operating environment.”
The METALLIC project holds significant promise for advancing cybersecurity practices. For instance, METALLIC could help organizations detect and neutralize exploit chains faster, reducing the average time to identify and mitigate a breach from days to hours.
By providing a comprehensive framework for modeling, analyzing, and mitigating exploit chains, METALLIC has the potential to empower security professionals with the tools and knowledge needed to better protect software systems from sophisticated cyberattacks.
This project represents an important step towards a more secure digital future, where individuals and organizations can confidently engage in online activities without fear of compromise.
Researchers and engineers with extensive expertise in various cybersecurity domains will spearhead the METALLIC project.
Mertoguno will lead the Georgia Tech team and be responsible for system security, systems-centric models, and scalable analysis. Wenke Lee, a professor at SCP, is responsible for vulnerability research, especially on mobile devices. Taesoo Kim, a professor at SCP, is responsible for exploit discovery and chaining. Brendan Saltaformaggio, an associate professor at SCP, will focus on root cause analysis.
John Popham
Communications Officer II
School of Cybersecurity and Privacy
Astronomers using NASA's James Webb Space Telescope found candidates for the first brown dwarfs outside of our galaxy in a young star cluster in the Small Magellanic Cloud (NGC 602). (ESA/Webb, NASA & CSA, P. Zeidler, E. Sabbi, A. Nota, M. Zamani)
The School of Physics will launch the new B.S. in Astrophysics program in summer 2025. This new major is the latest addition to the College of Sciences’ academic offerings and responds to increased student demand for courses and research opportunities in astrophysics. A minor in astrophysics will also be offered starting next summer.
According to David Ballantyne, associate chair for Academic Programs and professor in the School of Physics, the new major is unique because it focuses on the future of astronomy and astrophysics, especially in the era of discoveries made by the James Webb Space Telescope and the Laser Interferometer Gravitational-Wave Observatory (LIGO).
“We made a concerted effort when crafting this degree to make it modern and forward-facing,” says Ballantyne. “It is very much focused on the next decade of astronomy and astrophysics, providing a strong emphasis on computational skills, data analysis, and big data.”
The new degree includes coursework on the fundamental physical processes and laws that govern planetary systems, stars, galaxies, and the Universe as a whole. These core topics are complemented by training in computational and data analysis techniques that can be applied to a variety of disciplines.
For Ballantyne, the degree program should appeal to students who are interested in pursuing careers in space science research as well as those interested in non-research career paths.
“This program prepares students to solve complex problems in a very quantitative, rigorous way. Such problem solving and computational skills are highly marketable for a range of career paths,” he adds.
While astronomy coursework and outreach have long existed at the Institute, astrophysics officially began in 2008, when the School of Physics launched the Center for Relativistic Astrophysics (CRA). Today, the Center boasts more than a dozen faculty and research scientists, with expertise spanning high-energy astrophysics, extrasolar planets, gravitational-wave astronomy, and astroparticle physics.
As the CRA’s faculty roster grew, the School expanded its offering of astrophysics courses. A concentration in astrophysics for physics majors was launched during the 2013-14 academic year. A short time later, the School introduced an astrophysics certificate for non-majors. The new astrophysics major and minor — which will replace the concentration and certificate, respectively — reflects a new chapter in the history of astrophysics education and research at Georgia Tech.
“Most of our peer institutions have an astronomy or astrophysics degree so the creation of this program at Georgia Tech was a natural fit,” says Ballantyne. “Our program fills a critical need considering that there are few options in the U.S. Southeast for students to obtain this type of training at an institution of Georgia Tech’s caliber.”
Current students can declare the astrophysics major starting next semester, following the standard major change process for undergraduates. The astrophysics minor will be available to all Georgia Tech undergraduates starting summer 2025.
Astrophysics will be added to the list of majors beginning with the admissions application for Summer 2025 (transfer students) and the 2026-27 academic year (first-year students).
In the interim, transfer students enrolling for the Spring 2025 semester should follow the standard major change process for undergraduates. Students applying to Georgia Tech for the 2025-26 academic year should select “physics” as their major during the application process and choose “astrophysics” once admitted, during the major confirmation process.
Lindsay C. Vidal
Assistant Director of Communications
College of Sciences
The Department of Commerce has granted the Semiconductor Research Corporation (SRC), its partners, and Georgia Institute of Technology $285 million to establish and operate the 18th Manufacturing USA Institute. The Semiconductor Manufacturing and Advanced Reseach with Twins (SMART USA) will focus on using digital twins to accelerate the development and deployment of microelectronics. SMART USA, with more than 150 expected partner entities representing industry, academia, and the full spectrum of supply chain design and manufacturing, will span more than 30 states and have combined funding totaling $1 billion.
This is the first-of-its-kind CHIPS Manufacturing USA Institute.
“Georgia Tech’s role in the SMART USA Institute amplifies our trailblazing chip and advanced packaging research and leverages the strengths of our interdisciplinary research institutes,” said Tim Lieuwen, interim executive vice president for Research. “We believe innovation thrives where disciplines and sectors intersect. And the SMART USA Institute will help us ensure that the benefits of our semiconductor and advanced packaging discoveries extend beyond our labs, positively impacting the economy and quality of life in Georgia and across the United States.”
The 3D Systems Packaging Research Center (PRC), directed by School of Electrical and Computer Engineering Dan Fielder Professor Muhannad Bakir, played an integral role in developing the winning proposal. Georgia Tech will be designated as the Digital Innovation Semiconductor Center (DISC) for the Southeastern U.S.
“We are honored to collaborate with SRC and their team on this new Manufacturing USA Institute. Our partnership with SRC spans more than two decades, and we are thrilled to continue this collaboration by leveraging the Institute’s wide range of semiconductor and advanced packaging expertise,” said Bakir.
Through the Institute of Matter and Systems’ core facilities, housed in the Marcus Nanotechnology Building, DISC will accelerate semiconductor and advanced packaging development.
“The awarding of the Digital Twin Manufacturing USA Institute is a culmination of more than three years of work with the Semiconductor Research Corporation and other valued team members who share a similar vision of advancing U.S. leadership in semiconductors and advanced packaging,” said George White, senior director for strategic partnerships at Georgia Tech.
“As a founding member of the SMART USA Institute, Georgia Tech values this long-standing partnership. Its industry and academic partners, including the HBCU CHIPS Network, stand ready to make significant contributions to realize the goals and objectives of the SMART USA Institute,” White added.
Georgia Tech also plans to capitalize on the supply chain and optimization strengths of the No. 1-ranked H. Milton Stewart School of Industrial and Systems Engineering (ISyE). ISyE experts will help develop supply-chain digital twins to optimize and streamline manufacturing and operational efficiencies.
David Henshall, SRC vice president of Business Development, said, “The SMART USA Institute will advance American digital twin technology and apply it to the full semiconductor supply chain, enabling rapid process optimization, predictive maintenance, and agile responses to chips supply chain disruptions. These efforts will strengthen U.S. global competitiveness, ensuring our country reaps the rewards of American innovation at scale.”
Amelia Neumeister | Research Communications Program Manager
Leadership at the Memorandum of Understanding signing with the Korea Institute of Industrial Technology (KITECH). From left to right: Sangpyo Suh, Consulate General of Korea in Atlanta; Chaouki Abdallah, former executive vice president of Research at Georgia Tech; Sang Mok Lee, president of KITECH; and Barton Lowrey, director of the Georgia Department of Economic Development.
In a significant step towards fostering international collaboration and advancing cutting-edge technologies in manufacturing, Georgia Tech recently signed Memorandums of Understanding (MoUs) with the Korea Institute of Industrial Technology (KITECH) and the Korea Automotive Technology Institute (KATECH). Facilitated by the Georgia Tech Manufacturing Institute (GTMI), this landmark event underscores Georgia Tech’s commitment to global partnerships and innovation in manufacturing and automotive technologies.
“This is a great fit for the institute, the state of Georgia, and the United States, enhancing international cooperation,” said Thomas Kurfess, GTMI executive director and Regents’ Professor in the George W. Woodruff School of Mechanical Engineering (ME). “An MoU like this really gives us an opportunity to bring together a larger team to tackle international problems.”
“An MoU signing between Georgia Tech and entities like KITECH and KATECH signifies a formal agreement to pursue shared goals and explore collaborative opportunities, including joint research projects, academic exchanges, and technological advancements,” said Seung-Kyum Choi, an associate professor in ME and a major contributor in facilitating both partnerships. “Partnering with these influential institutions positions Georgia Tech to expand its global footprint and enhance its impact, particularly in areas like AI-driven manufacturing and automotive technologies.”
The state of Georgia has seen significant growth in investments from Korean companies. Over the past decade, approximately 140 Korean companies have committed around $23 billion to various projects in Georgia, creating over 12,000 new jobs in 2023 alone. This influx of investment underscores the strong economic ties between Georgia and South Korea, further bolstered by partnerships like those with KITECH and KATECH.
“These partnerships not only provide access to new resources and advanced technologies,” says Choi, “but create opportunities for joint innovation, furthering GTMI’s mission to drive transformative breakthroughs in manufacturing on a global scale.”
The MoUs with KITECH and KATECH are expected to facilitate a wide range of collaborative activities, including joint research projects that leverage the strengths of both institutions, academic exchanges that enrich the educational experiences of students and faculty, and technological advancements that push the boundaries of current manufacturing and automotive technologies.
“My hopes for the future of Georgia Tech’s partnerships with KITECH and KATECH are centered on fostering long-term, impactful collaborations that drive innovation in manufacturing and automotive technologies,” Choi noted. “These partnerships do not just expand our reach; they solidify our leadership in shaping the future of manufacturing, keeping Georgia Tech at the forefront of industry breakthroughs worldwide.”
Georgia Tech has a history of successful collaborations with Korean companies, including a multidecade partnership with Hyundai. Recently, the Institute joined forces with the Korea Institute for Advancement of Technology (KIAT) to establish the KIAT-Georgia Tech Semiconductor Electronics Center to advance semiconductor research, fostering sustainable partnerships between Korean companies and Georgia Tech researchers.
“Partnering with KATECH and KITECH goes beyond just technological innovation,” said Kurfess, “it really enhances international cooperation, strengthens local industry, drives job creation, and boosts Georgia’s economy.”
Shreyes Melkote, associate director of the Georgia Tech Manufacturing Institute, signing the Memorandum of Understanding with the Korea Automotive Technology Institute.
Na-Seung Sik, president of the Korea Automotive Technology Institute, signing the Memorandum of Understanding with Georgia Tech at the Georgia Tech Manufacturing Institute.
Audra Davidson
Research Communications Program Manager
Georgia Tech Manufacturing Institute
Francesca Storici and her research team discovered a surprising role for RNA in DNA repair, insights that could lead to better treatments for cancer and other diseases. Photo by Chris McKenney
A multi-institutional team of researchers, led by Georgia Tech’s Francesca Storici, has discovered a previously unknown role for RNA. Their insights could lead to improved treatments for diseases like cancer and neurodegenerative disorders while changing our understanding of genetic health and evolution.
RNA molecules are best known as protein production messengers. They carry genetic instructions from DNA to ribosomes — the factories inside cells that turn amino acids into the proteins necessary for many cell functions. But Storici’s team found that RNA can also help cells repair a severe form of DNA damage called a double-strand break, or DSB.
A DSB means both strands of the DNA helix have been severed. Cells have the tools to make some repairs, but a DSB is significant damage — and if not properly fixed can lead to mutations, cell death, or cancer. (Interestingly, cancer treatments, like chemotherapy and radiation, can cause DSBs.)
Storici, a professor in the School of Biological Sciences, has dedicated her research to studying the molecules and mechanisms underlying damaged DNA repairs. Ten years ago, she and collaborators discovered that RNA could serve as a template for DSB repair.
“Now we’ve learned that RNA can directly promote DSB repair mechanisms,” said Storici, whose lab teamed with mathematics experts in the lab of Nataša Jonoska from the University of South Florida. They’re all part of the Southeast Center for Mathematics and Biology based at Georgia Tech. They explain their discovery in the journal Nature Communications.
“These findings open up a new understanding of RNA's potential role in maintaining genome integrity and driving evolutionary changes,” added Storici.
The researchers used variation-distance graphs to visualize millions of DSB repair events, offering a comprehensive snapshot of sequence variations. The graphs highlighted major differences in repair patterns, depending on the DSB position.
This mathematical approach also uncovered significant differences in repair efficiency, pointing to RNA's potential in modulating DSB repair outcomes.
“These findings underscore the critical role of mathematical visualization in understanding complex biological mechanisms and could pave the way for targeted interventions in genome stability and therapeutic research,” said Jonoska.
When a DSB happens in DNA, it’s like a load-bearing beam in a building breaking. A careful, precise repair is needed to ensure the building’s — or the DNA’s — stability. The pieces must be rejoined accurately to prevent further damage or mutation. Repairing a damaged building requires having a reliable foreman on the job site. A DSB requires something very similar.
“A key mechanism we identified is that RNA can help position and hold the broken DNA ends in place, facilitating the repair process,” explained Storici, whose team conducted the research in both human and yeast cells.
Specifically, they found that RNA molecules and the broken section of DNA can match up like puzzle pieces. When RNA has this kind of complementarity with the DNA break site, it acts as a scaffold, or a guide, beyond its traditional coding function, showing the cellular machinery where to make repairs. Over millennia, cells have evolved complex mechanisms to fix DSB, each of them functioning like different tools from the same toolbox.
Storici’s team showed that RNA can influence which tools are used, depending on its complementarity to the broken DNA strands. This means that in addition to being the important protein production messenger, RNA acts as both a foreman and laborer when it comes to DNA repair.
A deeper understanding of RNA’s role in DNA repair could lead to new strategies for strengthening repair mechanisms in healthy cells, potentially reducing the harmful effects of treatments like chemotherapy and radiation.
“RNA has a much broader function than we knew,” Storici said. “We still have a lot of research to do into these mechanisms, but this work opens up new ways for exploring how RNA could be harnessed in healthcare, potentially leading to new treatments for cancer and other genetic diseases.”
As Storici and other researchers continue probing RNA’s effects in DNA repair, their revelations could have a lasting impact on human health and evolution. That means better gene therapies, new cancer treatments and anti-aging strategies — and also the ability to influence how organisms adapt and evolve.
CITATION: Youngkyu Jeon, Yilin Lu, Margherita Maria Ferrari, Tejasvi Channagiri, Penghao Xu, Chance Meers, Yiqi Zhang, Sathya Balachander, Vivian S. Park, Stefania Marsili, Zachary F. Pursell, Nataša Jonoska, Francesca Storici. “RNA-mediated double-strand break repair by end-joining mechanisms.” Nature Communications https://doi.org/10.1038/s41467-024-51457-9
FUNDING: NIH grants GM115927, ES028271; NSF grant MCB-1615335; Howard Hughes Medical Institute Faculty Scholar grant 55108574; Southeast Center for Mathematics and Biology NSF DMS-1764406; Simons Foundation grant 59459; NSF grants CCF-2107267 and DMS-2054321.
Nataša Jonoska and Youngkyu Jeon. Jonoska's lab collaborated with the lab of Francesca Storici. Jeon, a former PhD student in the Storici lab, was lead author of the study.
Jerry Grillo