The teams awarded will focus on strategic new initiatives in Artificial Intelligence.

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 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

Edge devices, such as wearables, cameras, smartphones, and smart home devices, have become the foundation of our daily interactions with technology. But the exponential growth in the number of these devices comes at a significant environmental cost, currently accounting for more than a third of the 4% of global carbon emissions attributed to information and communication technologies. This ecological impact is projected to worsen as the number of edge devices surges into trillions over the next few decades.

Josiah Hester, associate professor in the College of Computing, along with researchers from Cornell and Harvard Universities, has received a $2 million grant from the newly established Design for Environmental Sustainability in Computing program at the National Science Foundation. The investigators aim to study and mitigate the environmental impact of edge computing devices. Their winning project will make carbon and sustainability a first-order design parameter for future edge computing devices that range from tiny, energy-harvesting Internet of Things devices — often found in manufacturing lines, cars, agriculture, and cities — to higher performance consumer electronics like tablets and smartphones.

As part of the research, investigators will capture a first-of-its-kind dataset on actual emissions and resource usage of complex fabrication processes, build and validate tools for carbon-aware design, and establish an Electronic Sustainability Record for edge devices, similar to nutrition labels for food, or a digital health record, that allows consumers and manufacturers to understand the carbon costs of computing devices and use that in decision-making. The grant proposal was catalyzed through the Brook Byers Institute for Sustainable Systems Initiative Leads program, with additional funds from the Institute for Data Engineering and Science.

“Right now, hardware designers, programmers, and consumers have only a vague idea of the actual carbon cost of the phone, wearable, or smart device they are working with. With rising e-waste and technology’s increasing contributions to climate change, we have to figure out how to do better. This project will lay the foundations for edge devices that can last for decades, or at least have a lifetime commensurate with the carbon cost, potentially reducing e-waste, emissions, and environmental footprint,” said Hester. “Our design tools, new datasets, and carbon models will consider factors like energy, e-waste, and water usage from the manufacturing of computational devices, as well as operational carbon footprint from factors like machine learning and software lifecycles.”

With the grant money, Hester’s team will develop an end-to-end framework that prioritizes environmental impact, while considering user experience, performance, and efficiency when designing edge devices. The framework, which they are calling Delphi, will enable sustainable technological growth by laying out a path for the design of environmentally conscious edge devices with substantially longer lifecycles.
 
“Eventually, this research could lead to a kind of ‘nutrition label’ for computing devices, like your phone, to empower consumers with data to make more sustainability-friendly purchasing and use decisions,” Hester said. “This could incentivize and enable hardware companies to build lower carbon devices meant to last for many years, versus trading up after a contract renewal. We have a long way to go before this is reality, but this project will lay foundational steps in data collection, model building, and design tools — a sustainable vision of edge computing.”

The water coming out of your faucet is safe to drink, but that doesn’t mean it’s completely clean. Chlorine has long been the standard for water treatment, but it often contains trace levels of disinfection byproducts and unknown contaminants. Georgia Institute of Technology researchers developed the minus approach to handle these harmful byproducts.

Instead of relying on traditional chemical addition (known as the plus approach), the minus approach avoids disinfectants, chemical coagulants, and advanced oxidation processes typical to water treatment processes. It uses a unique mix of filtration methods to remove byproducts and pathogens, enabling water treatment centers to use ultraviolet light and much smaller doses of chemical disinfectants to minimize future bacterial growth down the distribution system.

“The minus approach is a groundbreaking philosophical concept in water treatment,” said Yongsheng Chen, the Bonnie W. and Charles W. Moorman IV Professor in the School of Civil and Environmental Engineering. “Its primary objective is to achieve these outcomes while minimizing the reliance on chemical treatments, which can give rise to various issues in the main water treatment stream.”

Chen and his student Elliot Reid, the primary author, presented the minus approach in the paper, “The Minus Approach Can Redefine the Standard of Practice of Drinking Water Treatment,” in The American Chemical Society.

The minus approach physically separates emerging contaminants and disinfection byproducts from the main water treatment process using these already proven processes:

• Bank filtration withdraws water from naturally occurring or constructed banks like rivers or lakes. As the water travels through the layers of soil and gravel, it naturally filters out impurities, suspended particles, and certain microorganisms.
• Biofiltration uses biological processes to treat water by passing it through filter beds made of sand, gravel, or activated carbon that can support the growth of beneficial microorganisms, which in turn can remove contaminants.  
• Adsorption occurs when an adsorbent material like activated carbon is used to trap contaminants.
• Membrane filtration uses a semi-permeable membrane to separate particles and impurities from the main treatment process.

The minus approach is intended to engage the water community in designing safer, more sustainable, and more intelligent systems. Because its technologies are already available and proven, the minus approach can be implemented immediately.

It can also integrate with artificial intelligence (AI) to improve filtration’s effectiveness. AI can aid process optimization, predictive maintenance, faulty detection and diagnosis, energy optimization, and decision-support systems. AI models have also been able to reliably predict the origin of different types of pollution in source water, and models have also successfully detected pipeline damage and microbial contamination, allowing for quick and efficient maintenance.

“This innovative philosophy seeks to revolutionize traditional water treatment practices by providing a more sustainable and environmentally friendly solution,” Chen said. “By reducing the reliance on chemical treatments, the minus approach mitigates the potential risks associated with the use of such chemicals, promoting a safer water supply for both human consumption and environmental protection.”

CITATION: Elliot Reid, Thomas Igou, Yangying Zhao, John Crittenden, Ching-Hua Huang, Paul Westerhoff, Bruce Rittmann, Jörg E. Drewes, and Yongsheng Chen

Environmental Science & Technology 2023 57 (18), 7150-7161

DOI: 10.1021/acs.est.2c09389

As the nation's power grid undergoes a transformative shift with historic investment in clean energy, Joe Hagerman understands the importance of this moment for the National Electric Energy Testing, Research and Applications Center (NEETRAC). It presents the center with a distinct opportunity to showcase expertise, drive progress, and actively shape the future of the grid.

NEETRAC, a leading research and testing resource for the electric energy industry, housed under the Georgia Tech School of Electrical and Computer Engineering (ECE), has announced the appointment of Hagerman as its director, starting June 1.

“Under the leadership of former Director Rick Hartlein, NEETRAC has established itself as a trusted authority in testing and research for the electric power industry,” said Hagerman. “Thanks to this reputation, we are now poised to take a leading role in the country's de-carbonization and re-electrification priorities. The potential for strengthening our ties with the Institute, the state of Georgia, and federal entities is a once in a lifetime opportunity.”

Hagerman joins NEETRAC after directing the Energy, Policy, and Innovation Center (EPICenter), a division of the Strategic Energy Institute.

Prior to Georgia Tech, Hagerman served as a section head at the U.S. Department of Energy’s Oak Ridge National Laboratory. He also has served as the deputy chief scientist of the ;National Rural Electric Cooperative Association and as a senior policy advisory at the U.S. Office of Energy’s Energy Efficiency and Renewable Energy.

“As NEETRAC prepares for the next phase of its journey, Joe's passion, visionary approach, and bridge-building abilities will be indispensable for success,” said Arijit Raychowdhury, professor and Steve W. Chaddick School Chair in ECE. “His policy work and technical expertise in grid systems speak for themselves, especially regarding emerging areas like renewables, connected equipment, and cybersecurity. I’m thrilled to have Joe leading the way.”

The Right Time for Growth

The domestic demand for electricity continues to steadily rise because of the government's ambitious renewable and carbon-free energy objectives, the increased electrification of transportation and heating, and the growing demand for digitally connected devices.

Add this to an aging power grid, and incentives and investments for making the grid stronger and more resilient are at an all-time high for the electric power industry.

Hagerman looks to leverage his governmental research reputation and knowledge of the Georgia Tech landscape to enhance NEETRAC's existing strengths and explore new opportunities. He seeks to establish new connections — both inside and outside of the Institute — for the center, enabling it to effectively drive innovation and address the evolving needs of the industry.

“The power grid stands as a remarkable feat of human engineering, and its sheer physical scale is incredible,” said Hagerman. “Incorporating changes is not as simple as flipping a switch. It requires extensive knowledge and countless hours of rigorous testing. Thankfully, NEETRAC and Georgia Tech possess an abundance of expertise — and a world class staff — that can be harnessed to navigate these challenges successfully.”

An Invaluable Industry Resource

For more than 25 years, NEETRAC — located just south of the Atlanta campus, near the Hartsfield-Jackson Atlanta International Airport — has played a vital role in facilitating collaboration between the electric energy industry and academia.

Everything connected to the power grid — even power poles to bucket trucks — can be tested and researched at the center. NEETRAC’s experienced engineers and technicians seek to deliver innovative, effective solutions to all problems related to the transmission and distribution of electric energy.

As a membership-supported center, NEETRAC's member companies comprise utilities that represent around 65% of U.S. electric customers, along with manufacturers who contribute significantly to the products and services offered in the electric utility industry.

“NEETRAC is much more than a testing laboratory to us,” said Sherif Kamel, vice president of New Product Development at Southwire, a NEETRAC member organization. “The deep knowledge and expertise that NEETRAC uses to support our industry’s needs is unparalleled.”

This diverse membership base promotes collaboration and knowledge exchange, keeping NEETRAC at the forefront of industry challenges, advancements, and opportunities.

Sherif, NEETRAC's advisory board chair and a member of the search committee that recommended Hagerman, stated that NEETRAC's staff and facilities aid Southwire in developing, improving, and supporting customers. Additionally, the center enhances the credibility and proficiency of the company's test results. Southwire was founded in 1937 by Roy Richards, a graduate of Georgia Tech, and is a NEETRAC founding member.

Future Potential

Hagerman stressed that with so much uncertainty regarding the future of the domestic power grid, one thing is clear: To evolve NEETRAC will need to enhance its relationship with the industry and scale to help its current and future members throughout North America.

“There’s excitement in not knowing how everything will unfold,” he said. “It’s important for us to be nimble and ready to adapt, but to also use our position to anticipate the needs of our members and provide value and insights to our partners.”

According to Hagerman, the future services of NEETRAC could be driven by several important factors, namely the integration of renewable energy sources, ensuring the security of the grid both in physical and cyber aspects, and harnessing the power of big data.

Investing and expanding in the expertise of NEETRAC's skilled scientists and engineers, its technical staff, and its administrative staff is arguably the most crucial approach to meeting the uncertain demands of the future.

“By nurturing the talents and skills of the team and by incorporating an inclusive approach, we all work toward the shared future of NEETRAC and the Institute. We are all one Georgia Tech,” said Hagerman. “NEETRAC’s role in that future is defined by its cutting-edge evaluations, its world class research, and its continued support of innovation for a resilient and secure domestic power grid for all.”