Georgia Tech Battery Day opened with a full house on March 30, 2023, at the Global Learning Center in the heart of Midtown Atlanta. More than 230 energy researchers and industry participants convened to discuss and advance energy storage technologies via lightning talks, panel discussions, student poster sessions, and networking sessions throughout the day. Matt McDowell, associate professor in the Woodruff School of Mechanical Engineering and the School of Materials Science and Engineering as well as the initiative lead for energy storage at the Strategic Energy Institute and the Institute of Materials, started the day with an overview of the relevant research at Georgia Tech. His talk shed light on Georgia becoming the epicenter of the battery belt of the Southeast with recent key industry investments and the robust energy-storage research community present at Georgia Tech.

According to the Metro Atlanta Chamber of Commerce, since 2020, Georgia has had $21 billion invested or announced in EV-related projects with 26,700 jobs created. With investments in alternate energy technologies growing exponentially in the nation, McDowell revealed Georgia Tech is well-positioned to make an impact on the next generation energy storage technologies and extended an open invitation to industry members to partner with researchers. As one of the most research-intensive academic institutions in the nation, Georgia Tech has more than $1.3 billion in research and other sponsored funds and produces the highest number of engineering doctoral graduates in the nation.

“More than half of Georgia Tech's strategic initiatives are focused on improving the efficiency and sustainability of energy storage, supporting clean energy sources, and mitigating climate change," said Chaouki Abdallah, executive vice president for research at Georgia Tech. "As a leader in battery technologies research, we are bringing together engineers, scientists, and researchers in academia and industry to conduct innovative research to address humanity's most urgent and complex challenges, and to advance technology and improve the human condition."

Rich Simmons, director of research and studies at the Strategic Energy Institute moderated the first panel discussion that included industry panelists from Panasonic, Cox Automotive, Bluebird Corp., Delta Airlines and Hyundai Kia. The panelists analyzed the opportunities and challenges in the electric transportation sector and explained their current focus areas in energy storage. The panel affirmed that while EVs have been around for more than three decades, the industry is still in its infancy and there is a huge potential to advance technology in all areas of the EV sector.

The discussion also brought forth important factors like safety, lifecycle, and sustainability in driving innovations in the energy storage sector. The attendees also discussed supply chain issues, a hot topic in almost all sectors of the nation, and the need to develop a diversity of resources for more resilient systems. The industry panelists affirmed a strong interest in partnering on research and development projects as well as gaining access to university talent.

Gleb Yushin, professor in the School of Material Science and Engineering and co-founder of Sila Nanotechnologies Inc., presented his battery research and development success story at Georgia Tech. Sila is a Georgia Tech start-up founded in 2011 and has produced the world’s first commercially available high-silicon-content anode for lithium-ion batteries in 2021. Materials manufactured in its U.S. facilities will power electric vehicles starting with the Mercedes-Benz G-class series in 2023.

The program included lightning talks on cutting-edge research in battery materials, specifically solid-state electrolytes and plastic crystal embedded elastomer electrolytes (PCEEs) by Seung Woo Lee, associate professor in the George W. Woodruff School of Mechanical Engineering. Santiago Grijalva, professor in the School of Electrical and Computer Engineering, discussed the challenges and opportunities for the successful use of energy storage for the grid.

Tequila Harris, initiative lead for Energy and Manufacturing and professor in the George W. Woodruff School of Mechanical Engineering, spoke to energy materials and carbon-neutral applications. Presenting a case for roll-to-roll manufacturing of battery materials, Harris said that the need for quick, high yield manufacturing processes and alternative materials and structures were important considerations for the industry.

Materials, manufacturing, and market opportunities were the topic for the next panel moderated by McDowell and included panelists from Albemarle, Novelis, Solvay, Truist Securities, and Energy Impact Partners. Analyzing the current challenges, the panelists brought up hiring and workforce development, increasing capacity and building the ecosystem, decarbonizing existing processes, and understanding federal policies and regulations.

Lightning talks later in the afternoon by researchers at Georgia Tech touched on the latest developments in the cross-disciplinary research bridging mechanical engineering, chemical engineering, AI manufacturing, and material science in energy storage research. Topics included safe rechargeable batteries with water-based electrolytes (Nian Liu, assistant professor, School of Chemical & Biomolecular Engineering), AI-accelerated manufacturing (Aaron Stebner, associate professor, School of Materials Science and Engineering), battery recycling (Hailong Chen, associate professor, School of Materials Science and Engineering), and parametric life-cycle models for a solid-state battery circular economy (Ilan Stern, research scientist from GTRI).

Another industry panel on grid, infrastructure and communities moderated by Faisal Alamgir, professor in the School of Materials Science and Engineering included panelists from Southern Company, Stryten Energy, and the Metro Atlanta Chamber of Commerce. Improving the grid resiliency and storage capacity; proximity to the energy source; optimizing and implementing new technology in an equitable way; standardization of the evolving business models; economic development and resource building through skilled workforce; educating the consumer; and getting larger portions of the grid with renewable energy were top of mind with the panelists.

“Energy-storage-related R&D efforts at Georgia Tech are extensive and include next-gen battery chemistry development, battery characterization, recycling, and energy generation and distribution,” said McDowell. “There is a tremendous opportunity to leverage the broad expertise we bring to advance energy storage systems. Battery Day has been hugely successful in not only bringing this expertise to the forefront, but also in affirming the need for continued interaction with the companies engaged in this arena. Our mission is to serve as a centralized focal point for research interactions between companies in the battery/EV space and faculty members on campus.”

Idling at a crossroads no longer, the automotive industry is embracing electrification like never before. With more electric vehicles purchased in 2022 than any year prior, consumers are beginning to follow their lead. Yet, while opportunity abounds, new challenges will require an innovative approach to ensure a sustainable and accessible electric future for all.

With historic investments from major players in the EV space, including Rivian, Kia, and Hyundai, the state of Georgia is uniquely positioned to serve as a leader in this effort. As the state's leading research institute, Georgia Tech is on the cutting edge of the movement. 

The transportation sector is the largest greenhouse gas emitter in the U.S. at nearly 30%, with passenger vehicles accounting for around 80% of the sector's total output1 as of 2019. Electric vehicles are widely regarded as a budding solution to reduce emissions, but even as both demand and production continue to increase, EVs currently account for around 1% of the cars on America's roadways. 

From the supply chain to the infrastructure needed to support alternative-fuel vehicles alongside consumer hesitancy, achieving the goals set by both the public and private sectors — including the Biden Administration's target of EVs making up at least 50% of new car sales by 2030 — will not be easy. Through research and development, policy, and collaboration, Tech experts are working toward finding solutions that will serve as catalysts during this transitionary period for the environment and the way Americans drive.

Check out the full story. 

This news release first appeared in the University of Arkansas Division of Agriculture newsroom, and has been tailored for Georgia Tech readers.

Researchers at Georgia Tech, the University of Arkansas System, the University of Nebraska-Lincoln, and Fort Valley State University in Georgia were awarded a $5 million grant to increase use of artificial intelligence and robotics in chicken processing to reduce waste in deboning and detect pathogens.

The grant from the U.S. Department of Agriculture’s National Institute of Food and Agriculture will establish the Center for Scalable and Intelligent Automation in Poultry Processing. The center, led by the University of Arkansas System Division of Agriculture, will join researchers from five institutions in three states in efforts to adapt robotic automation to chicken meat processing.

Douglas Britton, manager of the Agricultural Technology Research Program at the Georgia Tech Research Institute (GTRI), said his team was very excited to work on this project with experts at the four other institutions.

“The ultimate goal is to drive transformational innovation into the poultry and meat processing industry through automation, robotics, AI, and VR technologies,” Britton said. “Building on years of work in the GTRI Agricultural Technology Research Program, we are pleased to see that the USDA-NIFA has chosen this team to continue these efforts.”

Georgia Tech is a major partner in the project, and was awarded $2 million to focus on automating the processing lines that turn chickens into meat, said Jeyam Subbiah, professor and head of the food science department for the Division of Agriculture and the Dale Bumpers College of Agricultural, Food and Life Sciences at the University of Arkansas, and director of the project. The grant is for four years.

The Arkansas Agricultural Experiment Station, the research arm of the Division of Agriculture, will receive $2.2 million from the grant primarily to focus on food safety automation for poultry processing plants.

The remaining grant money will be divided between Julia McQuillan, Willa Cather professor of sociology at the University of Nebraska-Lincoln, and Brou Kuoakou, associate dean for research at Fort Valley State University in Georgia.

Jeff Buhr, a USDA Agricultural Research Service scientist, will contribute his expertise in broiler physiology to guide robotic deboning of meat, Subbiah said.

Georgia is the nation’s top broiler producer. Arkansas is number 3, according to 2021 figures from USDA.

Meeting the challenge

The recent impetus to automate chicken processing began with the Covid-19 pandemic, Subbiah said. The illness spread quickly among workers on the processing line. Since the worst of the pandemic, the poultry industry, like many others, has been having trouble hiring enough workers.

“Poultry processing lines began 70 to 80 years ago,” Subbiah said. “Since then, there have been only incremental changes in technology. Today, there’s a need for transformative change.”

Humans can feel when a knife hits a bone. In contrast, existing automation in poultry processing, like deboners, wastes a lot of meat.

“Human deboners leave about 13 percent of meat on the bones,” Subbiah said. “Automated deboners leave 16 to 17 percent. On an industrial scale, that’s a significant loss in value. We will use artificial intelligence and virtual reality to improve precision and reduce wastage.”

Automation can relieve labor shortages, Subbiah said. It also allows plants to locate in rural areas with a smaller labor force but nearer poultry houses and with lower property costs.

Initially, people working remotely may help advance robotic processing. Subbiah envisions workers logging on from home with virtual-reality goggles and haptics gloves to control robots located miles away.

While working remotely, the labor force will teach artificial intelligence how to cut up chickens of varying sizes and shapes.

“Automated machines right now are programmed to debone or cut up chickens based on an average size and shape. But no chicken is that size or shape,” Subbiah said. “Robot-wielded knives cut meat poorly. The machines have to learn how to adjust to the reality of random sizes and shapes.”

Georgia Tech’s participating scientists are all part of GTRI:

• Douglas Britton, manager of the Agricultural Technology Research Program
• Colin Trevor Usher, senior research scientist and branch head of robotics systems and technology, Agricultural Technology Research Program
• Ai-Ping Hu, principal research engineer, Agricultural Technology Research Program
• Konrad Ahlin, research engineer, Intelligent Sustainable Technologies Division
• Michael Park, research engineer, Intelligent Sustainable Technologies Division
• Benjamin Joffe, research scientist, Intelligent Sustainable Technologies Division
• Shreyes Melkote, the Morris M. Bryan, Jr. Professorship in Mechanical Engineering, associate director of the Georgia Tech Manufacturing Institute and executive director of the Novelis Innovation Hub

“We are thrilled to partner with our colleagues here in the Division of Agriculture, as well as our colleagues at Georgia Tech and the other participating institutions on this exciting project,” said David Caldwell, head of the Division of Agriculture’s poultry science department and director of the Center of Excellence for Poultry Science.

“We expect the findings from these coordinated research projects will be impactful for our stakeholders in the commercial poultry industry here in Northwest Arkansas and throughout the entire industry,” Caldwell said. “This project will help keep moving technology forward in processing and food safety of poultry.”

For more information about the project, see the original press release on the University of Arkansas Division of Agriculture website.

Ryan Lawler realized early on in her academic career that a scientist with a great idea can potentially change the world.

“But I didn’t realize the role that real estate can play in that,” said Lawler, general manager of BioSpark Labs – the collaborative, shared laboratory environment taking shape at Science Square at Georgia Tech.

Sitting adjacent to the Tech campus and formerly known as Technology Enterprise Park, Science Square is being reactivated and positioned as a life sciences research destination. The 18-acre site is abuzz with new construction, as an urban mixed-use development rises from the property.

Meanwhile, positioned literally on the ground floor of all this activity is BioSpark Labs, located in a former warehouse, fortuitously adjacent to the Global Center for Medical Innovation. It’s one of the newer best-kept secrets in the Georgia Tech research community.

BioSpark exists because the Georgia Tech Real Estate Office,  led by Associate Vice President Tony Zivalich, recognized the need of this kind of lab space. Zivalich and his team have overseen the ideation, design, and funding of the facility, partnering with Georgia Advanced Technology Ventures, as well as the Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech and Emory University, and the core facilities of the Petit Institute for Bioengineering and Bioscience.

“We are in the middle of a growing life sciences ecosystem, part of a larger vision in biotech research,” said Lawler, who was hired on to manage the space, bringing to the job a wealth of experience as a former research scientist and lab manager with a background in molecular and synthetic biology.

Researchers’ Advocate

BioSpark was designed to be a launch pad for high-potential entrepreneurs. It provides a fully equipped and professionally operated wet lab, in addition to a clean room, meeting and office space, to its current roster of clients, five life sciences and biotech startup, a number certain to increase – because BioSpark is undergoing a dramatic expansion that will include 11 more labs (shared and private space), an autoclave room, equipment and storage rooms.

“We want to provide the necessary services and support that an early-stage company needs to begin lab operations on day one,” said Lawler, who has put together a facility with $1.7 million in lab equipment. “I understand our clients’ perspective, I understand researchers and their experiments, and their needs, because I have first-hand proficiency in that world. So, I can advocate on their behalf.”

CO2 incubators, a spectrophotometer, a biosafety cabinet, a fume hood, a -80° freezer, an inverted microscope, and the autoclave are among the wide range of apparatus. Plus, a virtual treasure trove of equipment is available to BioSpark clients off-site through the Core Facilities of the Petit Institute for Bioengineering and Bioscience on the Georgia Tech campus.

“One of the unique things about us is, we’re agnostic,” Lawler said. “That is, our startups can come from anywhere. We have companies that have grown out of labs at Georgia State, Alabama State, Emory, and Georgia Tech. And we have interest from entrepreneurs from San Diego, who are considering relocating people from mature biotech markets to our space.”

Ground Floor Companies

Marvin Whiteley wants to help humans win the war against bacteria, and he has a plan, something he’s been cooking up for about 10 years, which has now manifested in his start-up company, SynthBiome, one of the five startups based at BioSpark Labs.

“We can discover a lot of antibiotics in the lab but translating them into the clinic has been a major challenge – antibiotic resistance is the main reason,” said Whiteley, professor in the School of Biological Sciences at Georgia Tech. “Something might work in a test tube easily enough and it might work in a mouse. But the thing is, bacteria know that mice are different - and and so bacteria act differently in mice than in humans.”

SynthBiome was built to help accelerate drug discovery. With that goal in mind, Whiteley and has team set out to develop a better, more effective preclinical model. “We basically learned to let the bacteria tell us what it’s like to be in a human,” Whiteley said. “So, we created a human environment in a test tube.”

Whiteley has said a desire to help people is foundational to his research. He wants to change how successful therapies are made. The same can be said for Dr. Pooja Tiwari, who launched her company, Arnav Biotech, to develop mRNA-based therapeutics and vaccines. Arnav Biotech also serves as a contract researcher and manufacturer, helping other researchers and companies interested in exploring mRNA in their work.

“There are only a handful of people who have deep knowledge of working in mRNA research, and this limits the access to it” said Tiwari, a former postdoctoral researcher at Georgia Tech and Emory. “We’d like to democratize access to mRNA-based therapeutics and vaccines by developing accessible and cost-effective mRNA therapeutics for global needs”.

Arnav – which has RNA right there in the name – in Sanskrit means ‘ocean.’ An ocean has no discernible borders, and Tiwari is working to build a biotech company that eliminates borders in equitable access to mRNA-based therapeutics and vaccines.

With this mission in mind, Arnav is developing mRNA-based, broad-spectrum antivirals as well as vaccines against pandemic potential viruses before the next pandemic hits. Arnav has recently entered in a collaboration with Sartorius BIA Separations, a company based on Slovenia, to advance their mRNA pipeline. While building its own mRNA therapeutics pipeline, Arnav is also helping other scientists explore mRNA as an alternative therapeutic and vaccine platform through its contract services. 

“I think of the vaccine scientist who makes his medicine using proteins, but would like to explore the mRNA option,” Tiwari posits. “Maybe he doesn’t want to make the full jump into it. That’s where we come in, helping to drive interest in this field and help that scientist compare his traditional vaccines to see what mRNA vaccines looks like.”

She has all the equipment and instruments that she needs at BioSpark Labs and was one of the first start-ups to put down roots there. So far, it’s been the perfect partnership, Tiwari said, adding, “It kind of feels like BioSpark and Arnav are growing up together.”

Coral reef conservation is a steppingstone to protect marine biodiversity and life in the ocean as we know it. The health of coral also has huge societal implications: reef ecosystems provide sustenance and livelihoods for millions of people around the world. Conserving biodiversity in reef areas is both a social issue and a marine biodiversity priority.

In the face of climate change, Annalisa Bracco, professor in the School of Earth and Atmospheric Sciences at Georgia Institute of Technology, and Lyuba Novi, a postdoctoral researcher, offer a new methodology that could revolutionize how conservationists monitor coral. The researchers applied machine learning tools to study how climate impacts connectivity and biodiversity in the Pacific Ocean’s Coral Triangle — the most diverse and biologically complex marine ecosystem on the planet. Their research, recently published in Nature Communications Biology, overcomes time and resource barriers to contextualize the biodiversity of the Coral Triangle, while offering hope for better monitoring and protection in the future.

“We saw that the biodiversity of the Coral Triangle is incredibly dynamic,” Bracco said. “For a long time, it has been postulated that this is due to sea level change and distribution of land masses, but we are now starting to understand that there is more to the story.”

Connectivity refers to the conditions that allow different ecosystems to exchange genetic material such as eggs, larvae, or the young. Ocean currents spread genetic material and also create the dynamics that allow a body of water — and thus ecosystems — to maintain consistent chemical, biological, and physical properties. If coral larvae are spread to an ecoregion where the conditions are very similar to the original location, the larvae can start a new coral.

Bracco wanted to see how climate, and specifically the El Niño Southern Oscillation (ENSO) in its phases — El Niño, La Niña, and neutral conditions — impacts connectivity in the Coral Triangle. Climate events that move large masses of warm water in the Pacific Ocean bring enormous changes and have been known to exacerbate coral bleaching, in which corals turn white due to environmental stressors and become vulnerable to disease.

“Biologists collect data in situ, which is extremely important,” Bracco said. “But it’s not possible to monitor enormous regions in situ for many years — that would require a constant presence of scuba divers. So, figuring out how different ocean regions and large marine ecosystems are connected over time, especially in terms of foundational species, becomes important.”

Machine Learning for Discovering Connectivity

Years ago, Bracco and collaborators developed a tool, Delta Maps, that uses machine learning to identify “domains,” or regions within any kind of system that share the same dynamic. Bracco initially used it to analyze domains of climate variability in models but also suspected it could be used to study ecoregions in the ocean.

For this study, they used the tool to map out domains of connectivity in the Coral Triangle using 30 years of sea surface temperature data. Sea surface temperatures change in response to ocean currents over scales of weeks and months and across distances of tens of kilometers. These changes are relevant to coral connectivity, so the researchers built their machine learning tool based on this observation, using changes in surface ocean temperature to identify regions connected by currents. They also separated the time periods that they were considering into three categories: El Niño events, La Niña events, and neutral or “normal” times, painting a picture of how connectivity was impacted during major climate events in particular ecoregions.

Novi then applied a ranking system to the different ecoregions they identified. She used rank page centrality, a machine learning tool that was invented to rank webpages on the internet, on top of Delta Maps to identify which coral ecoregions were most strongly connected and able to receive the most coral larvae from other regions. Those regions would be the ones most likely sustain and survive through a bleaching event.

Climate Dynamics and Biodiversity

Bracco and Novi found that climate dynamics have contributed to biodiversity because of the way climate introduces variability to the currents in the equatorial Pacific Ocean. The researchers realized that alternation of El Niño and La Niña events has allowed for enormous genetic exchanges between the Indian and Pacific Oceans and enabled the ecosystems to survive through a variety of different climate situations.

“There is never an identical connection between ecoregions in all ENSO phases,” Bracco said. “In other parts of the world ocean, coral reefs are connected through a fixed, often small, number of ecoregions, and if you eliminate this fixed number of connections by bleaching all connected reefs, you will not be able to rebuild the corals in any of them. But in the Pacific the connections are changing all the time and are so dynamic that soon enough the bleached reef will receive larvae from completely different ecoregions in a different ENSO phase.”

They also concluded that, because of the Coral Triangle’s dynamic climate component, there is more possibility for rebuilding biodiversity there than anywhere else on the planet. And that the evolution of biodiversity in the Coral Triangle is not only linked to landmasses or sea levels but also to the evolution of ENSO through geological times. The researchers found that though ENSO causes coral bleaching, it has helped the Coral Triangle become so rich in biodiversity.

Better Monitoring Opportunities

Because coral reef survival has been designated a priority by the United Nations Sustainable Development Goals, Bracco and Novi’s research is poised to have broad applications. The researchers’ method identified which ecoregions conservationists should try hardest to protect and also the regions that conservationists could expect to have the most luck with protection measures. Their methodology can also help to identify which regions should be monitored more and the ones that could be considered lower priority for now due to the ways they are currently thriving.

“This research opens a lot of possibilities for better monitoring strategies, and especially how to monitor given a limited amount of resources and money,” Bracco said. “As of now, coral monitoring often happens when groups have a limited amount of funding to apply to a very specific localized region. We hope our method can be used to create a better monitoring over larger scales of time and space.”

CITATION: Novi, L., Bracco, A. “Machine learning prediction of connectivity, biodiversity and resilience in the Coral Triangle.” Commun Biol 5, 1359 (2022). 

DOI: https://doi.org/10.1038/s42003-022-04330-8

Artificial intelligence is already making headlines in the new year with the box office success of the movie M3GAN. Along with a TikTok dance craze and lots of laughs, the over-the-top horror movie/dark comedy about an AI-powered robot that runs amok is also inspiring discussion about the growing presence and impact of artificial intelligence in everyday life.

From the movie house to the warehouse to your house, AI seems like it's everywhere. That's because with a steady stream of new research and innovative applications reaching into nearly every industry and business sector, it is everywhere. Nevertheless, AI still holds enormous potential as the field continues to evolve.

To get a sense of what this evolution could look like in 2023, we turned to a small group of Ph.D. students from the College of Computing community that are currently pushing foundational and applied AI research forward in a broad spectrum of disciplines and fields.

The students shared their opinions on where AI might be headed in the new year, what some of the big tech stories could be, and why ethics in AI are so critically important.

Where will artificial intelligence and machine learning have the most impact in 2023?

"Artificial intelligence and machine learning will continue to have a huge impact on manufacturing and warehouses with labor shortages and worker turnover continuing to be a concern as more manufacturing and operations jobs are brought back to the United States from overseas. Additionally, AI/ML will continue to help ensure that manufacturing and warehouse facilities are operating as efficiently as possible from energy and material savings to worker safety and parts quality." – Zoe Klesmith Alexander, computational science and engineering Ph.D. student

"Right now, deep learning is on a trajectory to transform the creation space. Artwork and images, videos, data representation and storytelling, co-authoring, and summarizing documents... It's gotten really good." – Ben Hoover, machine learning Ph.D. student

"I think machine learning and AI will keep playing a huge role in how the world and society will be shaped over the next decade in many ways. It will make many other fields more efficient through ML and AI tools we are developing. In 2023, I think ML and AI will have the most impact on social media platforms, helping reduce hate speech, rumor spread, etc." – Agam A. Shah, machine learning Ph.D. student

"One of the big impacts this year may be driverless cars being in your neighborhood. Otherwise, it will be a slow steady drip of GPT3 and other OpenAI models suffusing all applications, making programmers much faster, making journalists faster, making academic articles and lit reviews much faster. We're at a 4th grader level, and I hope by the end of this year we'll be at the 6th grader level. Also, indoor turn-by-turn navigation will be everywhere in 2023 as well." – Brandon Biggs, human-centered computing Ph.D. student

What will be some of the big tech stories in 2023?

"ChatGPT and the GitHub Copilot lawsuit will keep making it into the news and cause more controversies. In general, AI ethics will become more important and get more focus as the technology keeps advancing." – Fabian Fleischer, cybersecurity, and privacy Ph.D. student

"Driverless car fleets will be coming to a city near you. A new battery technology will allow phones to keep their charge for a week. Meta realizes virtual reality (VR) head-mounted displays are for a limited market and uses headphones and phones to provide VR experiences." – Brandon Biggs

What’s an issue or industry that you think could benefit from a computing solution?

"Our reinterpretation of modern deep learning as energy-based associative memories has the potential to transform any industry that relies on foundation models -- giant architectures that require models that are "self-supervised" (learn on their own from data)." – Ben Hoover

"Inclusion in everything. Over 90 percent of websites on the internet have elements that are inaccessible to 25 percent of the world's population who have disabilities. Inclusive design will be the most important area where technology can be redesigned and created to have multiple sensory modalities and be properly programmed." – Brandon Biggs

"Currently, financial markets are far from efficient because they do not fully incorporate information available in large unstructured text data. With the latest development in natural language processing techniques, we can better understand the economy and therefore price financial markets better." – Agam A. Shah

There’s been increasing recognition of the vital role ethics should play in artificial intelligence. How do you see this issue evolving in the next year?

"Specifically in my research, I think explainable AI (XAI) is very important, especially if non-experts in ML will be using black-box ML solutions in a factory. It will be important for humans to trust and to understand the models especially if the models are being using to monitor quality on a safety-critical part.

"Additionally, using XAI for human interaction with robots that utilize deep learning to make decisions will be increasingly important as technologies like collaborative robots (cobots) are integrated into factories. I think in my area of research that it is always important to use automation to aid humans in jobs that are safe for humans to do and not to replace them." – Zoe Klesmith Alexander

"Big data is pretty much at its peak. Deep data, where your Alexa knows everything about you, or your phone knows everything about you, and rather than saying 'other people who watched this show liked this show,' it's going to say, 'I know you liked these shows, I think you'll like this show because of these reasons, one of which is because other people who liked all these other shows liked this show.' The ethical element will be how much of this data should these models use, and are people going to build a personal dataset that they can share with other apps, or is each app going to need to build their own dataset? The ethical question is who owns this data." – Brandon Biggs

"I think ethics will become more and more important going forward. We are making huge breakthroughs in machine learning and artificial intelligence, but the systems we are creating are producing racist, sexist, and stereotypical results. For example, a recent system, Galactica, developed by Facebook (Meta) is powerful. It can produce research articles by just simply providing it with the title. It comes with some serious ethical concerns, in some cases, it produces racist, sexist text. So, as we will keep developing better models and making success in parallel, we need to always keep in mind the ethical implications of these models." – Agam A. Shah

What research are you working on that you think people should know about or will have impact in 2023?

"Part of my research focuses on data-driven modeling of additive manufacturing processes to better control dimensional quality of the final part. Another part of my research focuses on detecting anomalies in real-time using computer vision and machine learning for both warehouses and manufacturing processes." – Zoe Klesmith Alexander

"Right now, deep learning is built on feed-forward mathematical operations that have little resemblance to the brain. I am working on a physics inspired approach to deep learning built around recurrent networks and energy functions. These architectures have the same mathematical foundation as the famous, biologically plausible Hopfield Network." – Ben Hoover

"I am currently working on two projects which, in my opinion, will have an impact in 2023. In one project, we are measuring the exposure of public firms to ongoing inflation. We are also understanding how inflation affects different firms differently based on the pricing power of the firm. As inflation is the highest in the last 40 years, our study is highly relevant now and in the coming years till we get inflation back in control.

"The second work is related to the first work in some ways. As inflation is rising, to control the inflation Federal Reserve Bank is tightening its monetary policy. In our second work, we are measuring the stance of monetary policy (measuring hawkish vs dovish stance) of the Fed using state-of-the-art NLP models to see its impact in various financial markets (Treasury market, Stock market, Crypto market, etc.)" – Agam A. Shah

Though it is a cornerstone of virtually every process that occurs in living organisms, the proper folding and transport of biological proteins is a notoriously difficult and time-consuming process to experimentally study.

In a new paper published in eLife, researchers in the School of Biological Sciences and the School of Computer Science have shown that AF2Complex may be able to lend a hand.

Building on the models of DeepMind’s AlphaFold 2, a machine learning tool able to predict the detailed three-dimensional structures of individual proteins, AF2Complex — short for AlphaFold 2 Complex — is a deep learning tool designed to predict the physical interactions of multiple proteins. With these predictions, AF2Complex is able to calculate which proteins are likely to interact with each other to form functional complexes in unprecedented detail.

“We essentially conduct computational experiments that try to figure out the atomic details of supercomplexes (large interacting groups of proteins) important to biological functions,” explained Jeffrey Skolnick, Regents’ Professor and Mary and Maisie Gibson Chair in the School of Biological Sciences, and one of the corresponding authors of the study. With AF2Complex, which was developed last year by the same research team, it’s “like using a computational microscope powered by deep learning and supercomputing.”

In their latest study, the researchers used this ‘computational microscope’ to examine a complicated protein synthesis and transport pathway, hoping to clarify how proteins in the pathway interact to ultimately transport a newly synthesized protein from the interior to the outer membrane of the bacteria — and identify players that experiments might have missed. Insights into this pathway may identify new targets for antibiotic and therapeutic design while providing a foundation for using AF2Complex to computationally expedite this type of biology research as a whole.

Computing complexes

Created by London-based artificial intelligence lab DeepMind, AlphaFold 2 is a deep learning tool able to generate accurate predictions about the three-dimensional structure of single proteins using just their building blocks, amino acids. Taking things a step further, AF2Complex uses these structures to predict the likelihood that proteins are able to interact to form a functional complex, what aspects of each structure are the likely interaction sites, and even what protein complexes are likely to pair up to create even larger functional groups called supercomplexes.

“The successful development of AF2Complex earlier this year makes us believe that this approach has tremendous potential in identifying and characterizing the set of protein-protein interactions important to life,” shared Mu Gao, a senior research scientist at Georgia Tech. “To further convince the broad molecular biology community, we [had to] demonstrate it with a more convincing, high impact application.”

The researchers chose to apply AF2Complex to a pathway in Escherichia coli (E. coli), a model organism in life sciences research commonly used for experimental DNA manipulation and protein production due to its relative simplicity and fast growth. 

To demonstrate the tool’s power, the team examined the synthesis and transport of proteins that are essential for exchanging nutrients and responding to environmental stressors: outer membrane proteins, or OMPs for short. These proteins reside on the outermost membrane of gram-negative bacteria, a large family of bacteria characterized by the presence of inner and outer membranes, like E. coli. However, the proteins are created inside the cell and must be transported to their final destinations. 

“After more than two decades of experimental studies, researchers have identified some of the protein complexes of key players, but certainly not all of them,” Gao explained. AF2Complex “could enable us to discover some novel and interesting features of the OMP biogenesis pathway that were missed in previous experimental studies.”

New insights

Using the Summit supercomputer at the Oak Ridge National Laboratory, the team, which included computer science undergraduate Davi Nakajima An, put AF2Complex to the test. They compared a few proteins known to be important in the synthesis and transport of OMPs to roughly 1,500 other proteins — all of the known proteins in E. coli’s cell envelope — to see which pairs the tool computed as most likely to interact, and which of those pairs were likely to form supercomplexes. 

To determine if AF2Complex’s predictions were correct, the researchers compared the tool’s predictions to known experimental data. “Encouragingly,” said Skolnick, “among the top hits from computational screening, we found previously known interacting partners.” Even within those protein pairs known to interact, AF2Complex was able to highlight structural details of those interactions that explain data from previous experiments, lending additional confidence to the tool’s accuracy.

In addition to known interactions, AF2Complex predicted several unknown pairs. Digging further into these unexpected partners revealed details on what aspects of the pairs might interact to form larger groups of functional proteins, likely active configurations of complexes that have previously eluded experimentalists, and new potential mechanisms for how OMPs are synthesized and transported. 

“Since the outer membrane pathway is both vital and unique to gram-negative bacteria, the key proteins involved in this pathway could be novel targets for new antibiotics,” said Skolnick. “As such, our work that provides molecular insights about these new drug targets might be valuable to new therapeutic design.”

Beyond this pathway, the researchers are hopeful that AF2Complex could mean big things for biology research. 

“Unlike predicting structures of a single protein sequence, predicting the structural model of a supercomplex can be very complicated, especially when the components or stoichiometry of the complex is unknown,” Gao noted. “In this regard, AF2Complex could be a new computational tool for biologists to conduct trial experiments of different combinations of proteins,” potentially expediting and increasing the efficiency of this type of biology research as a whole.

AF2Complex is an open-source tool available to the public and can be downloaded here.

This work was supported in part by the DOE Office of Science, Office of Biological and Environmental Research (DOE DE-SC0021303) and the Division of General Medical Sciences of the National Institute Health (NIH R35GM118039). DOI: https://doi.org/10.7554

The Scalable Asymmetric Lifecycle En­gage­ment Microelectronics Work­force Development program (SCALE) has announced the program will extend another five years and expand with $10.8 million additional Department of Defense (DoD) funding, with a ceiling of $99 million.

SCALE officials said this expansion of the nation’s preeminent program will further its goal to develop a next-generation workforce that can return the United States to prominence in global microelectronics manufacturing.

Georgia Tech participates in the partnership, which is led by Purdue University and managed by NSWC Crane. SCALE facilitates the training of highly skilled U.S. microelectronics engineers, hardware designers and manufacturing experts. SCALE brings together a public-private-academic partnership of 17 universities and 34 partners within the defense industry and government. 

“This is an extremely exciting time in the country and at Tech for microchip design and manufacturing,” said Arijit Raychowdhury, the Steve W. Chaddick School Chair of Tech’s School of Electrical and Computer Engineering (ECE). “These newly announced funds for the SCALE program will help Georgia Tech recruit a new, diverse group of students ready to work in defense microelectronics. We’re thrilled to be a SCALE partner university and honored to be leading many of the project’s specialty areas.”

SCALE provides unique courses, mentoring, internship matching and targeted research projects for college students interested in five microelectronics specialty areas. Georgia Tech ECE faculty members will be the primary investigators for three of the areas: 

• system on a chip will be led by Raychowdhury;
• radiation-hardening will be led by John Cressler;
• and heterogeneous integration/advanced packaging will be led by Madhavan Swaminathan.

The other two focus areas are embedded system security/trusted AI and supply chain awareness.

Industry and government partners regularly meet and update a list of knowledge, skills, and abilities important for new entrants to the workforce. The SCALE universities then update their curriculum to ensure the students are prepared for upcoming needs in the rapidly advancing microelectronics field.

Peter Bermel, SCALE director and the Elmore Associate Professor of Electrical and Computer Engineering at Purdue, said the United States will need 50,000 trained semiconductor engineers to meet overwhelming and rapidly growing demand.

“The United States is committed to expanding and strengthening its semiconductor industry and workforce rapidly over the next five years,” Bermel said. “SCALE takes a holistic approach to the microelectronics workforce gap by comprehensively addressing system challenges for workforce training and recruiting.”

Goals for the next five years include:

• Expanding student participation in SCALE fivefold to more than 1,000.
• Developing learning models for K-12 classrooms.
• Collaborating with community colleges nationwide to develop microelectronics classes.

The demand for microelectronics increased by 26.2% in 2021. But while the United States consumes about half of the chips produced worldwide, the country only manufactures about 12%, highlighting the pressing need for the U.S. to strengthen its domestic semiconductor supply chains and increase industrial capacity.

The funding announcement is the latest highlight in Georgia Tech’s leadership role in bolstering microelectronics and workforce development. Tech’s large engineering and science faculty bring a broad set of research expertise to strengthen the country’s semiconductor capacity. The Institute is uniquely positioned to train the microelectronics workforce, drive future microelectronics advances, and provide fabrication and packaging facilities for industry, academic and government partners to develop and test new solutions.

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The Georgia Institute of Technology, or Georgia Tech, is a top 10 public research university developing leaders who advance technology and improve the human condition. The Institute offers business, computing, design, engineering, liberal arts, and sciences degrees. Its nearly 44,000 students, representing 50 states and 149 countries, study at the main campus in Atlanta, at campuses in France and China, and through distance and online learning. As a leading technological university, Georgia Tech is an engine of economic development for Georgia, the Southeast, and the nation, conducting more than $1 billion in research annually for government, industry, and society.

Aaron Stebner outlined an aggressive plan for artificial intelligence and manufacturing when he applied for a faculty position in 2019. In his cover letter, he promised “to establish the Georgia Institute of Technology as a world leader in additive manufacturing of solid materials (ceramics & metals) R&D, especially in the fusion of data sciences and AI to create new, world-leading technologies.”

Stebner thought it would take 10-15 years of incremental steps and funding to achieve the goal. He was wrong.

Thanks to a new $65 million grant from the U.S. Department of Commerce’s Economic Development Administration, announced by President Joe Biden, Stebner’s plan will begin to become a reality — and include the entire state of Georgia and all of its manufacturing sectors from agriculture to airplanes — two years after arriving on campus.

The largest of the nine projects within the larger Georgia AI Manufacturing (GA-AIM) technology corridor grant will allow Stebner and Georgia Tech to transform the Advanced Manufacturing Pilot Facility (AMPF) into the Artificial Intelligence Manufacturing Pilot Facility (AI-MPF). The 24,000 square-foot facility on 14th Street will more than double in size after Georgia Tech and statewide GA-AIM partners were selected as one of 21 Phase II awardees in the $1 billion Build Back Better Regional Challenge (BBB) competition, part of the Investing in America’s Communities initiative under the American Rescue Plan Act of 2021.

AMPF has been a shell waiting for a vision like Build Back Better to fill it out,” said Stebner, associate professor the George W. Woodruff School of Mechanical Engineering and the School of Materials Science and Engineering. “Now we will transform the facility into one of the nation’s first manufacturing labs designed for autonomy with the goal of helping the state and the nation to be world AI manufacturing leaders.”

Read the entire story on the College of Engineering website.