Celebrating the Remarkable Career of Robert Butera
Bill Dracos Appointed Interim Chief Research Operations Officer as Rob Butera Announces His Retirement 

It is with immense gratitude and admiration that we announce the retirement of Robert Butera, who has served Georgia Tech with the highest dedication and excellence. As the chief research operations officer (CROO), Butera has facilitated the Institute’s research activities, overseeing research integrity assurance, research administration, research operations/infrastructure, and research development. His leadership and vision have left an indelible mark on Georgia Tech's research enterprise.

Butera’s journey at Georgia Tech began long before his role as CROO. He received his undergraduate degree in electrical engineering from Georgia Tech in 1991. He joined the Institute’s faculty in 1999, after earning his Ph.D. from Rice University and spending several years as a postdoctoral researcher at the National Institutes of Health. Over the years, Butera has held numerous pivotal roles, including vice president for research development and operations, associate dean for research in the College of Engineering, and director of the Neural Engineering Center. Prior to joining Georgia Tech’s research leadership, Butera directed the interdisciplinary bioengineering graduate program, then co-founded the Grand Challenges Living Learning Community.

As a professor, Butera graduated 15 Ph.D. students and mentored over 100 undergraduates, for which he received Georgia Tech’s Senior Faculty Outstanding Undergraduate Research Mentor Award in 2016. He also mentored several postdocs and master’s students.

Butera’s accolades are numerous, including the prestigious Georgia Tech ANAK award and election as a Fellow to both the American Association for the Advancement of Science and the American Institute of Medical and Biological Engineering. He held significant leadership roles within the IEEE Engineering in Medicine and Biology Society. These honors reflect his impact on the field of biomedical engineering and his dedication to advancing scientific knowledge.

Beyond his professional achievements, Butera’s personal passions have also enriched the larger Georgia Tech community. His love for whitewater kayaking, which he discovered through Outdoor Recreation Georgia Tech (ORGT), led to a decade of volunteering as an instructor and trip leader. This commitment to adventure and leadership development has inspired many students and colleagues alike.

"Rob's unwavering commitment to excellence and his visionary leadership have been instrumental in advancing Georgia Tech's research mission. His contributions have not only elevated our institution but have also profoundly impacted the broader scientific community. We are deeply grateful for his service and wish him all the best in his well-deserved retirement,” said Tim Lieuwen, executive vice president for Research.

Andrés J. García, executive director of the Parker H. Petit Institute for Bioengineering and Bioscience, shared these heartfelt words: "Rob, the ultimate Yellow Jacket, has been a tireless champion to improve research, educational, and operational processes at Georgia Tech. He has had tremendous positive impact in Georgia Tech, the state, and the nation. We will miss his deep knowledge and expertise, exceptional problem solving, practical perspective, and genuine care for faculty, staff, and students, and we wish him continued success in his next chapter."

Lena Ting, McCamish Foundation Distinguished Chair in Biomedical Engineering in the Walter H. Coulter Department of Biomedical Engineering, said, “Rob’s heart has a huge ‘GT’ stamped on it: He has always been engaged in all aspects of Georgia Tech life. I’m always amazed to hear about his undergrad teaching and mentoring, kayaking with ORGT, and advising his fraternity. At the same time, he worked tirelessly to enhance interdisciplinary research and solve challenges affecting faculty research, all while conducting his own innovative research. Rob is a GT nexus, always in the know about what is going on around campus and – more importantly – how and why it got to be that way. He is a great friend and colleague who is always available for a beer, and I’ll miss him dearly.”

As we bid farewell to Rob, we also extend a warm welcome to Bill Dracos, who will serve as the interim chief research operations officer, effective immediately. Bill brings a wealth of experience from his role as Deputy Chief Operating Officer at the Georgia Tech Research Institute and his previous leadership positions at George Mason University, Emory University, and PricewaterhouseCoopers. We are confident Bill will continue to build on Rob's legacy of excellence and innovation.

Thank you, Rob, for your years of service, your unwavering commitment to Georgia Tech, and your inspiring leadership. We wish you all the best in your retirement and look forward to seeing the new adventures you will undoubtedly embark upon.

Georgia Tech is conducting a national search for the next Chief Research Operations Officer. Learn more about the open position. 

 

 

 

 

Lamarr.AI leverages AI and drones to autonomously diagnose building energy inefficiencies, reducing carbon emissions. The startup, a collaboration between Georgia Tech, MIT, and Syracuse University, raised $1.1 million in pre-seed funding. Their technology provides detailed diagnostics of building exteriors, helping owners save on energy costs and improve indoor air quality.

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Solar power as an electricity source is growing in the United States, with 7% of Americans using it to run their homes. But scientists are still trying to make the solar panel production process more efficient.

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From new farming practices to paleontology, meet four Georgia Tech researchers who improve the climate and predict its future.

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On Jan. 13, the Georgia Tech Strategic Energy Institute (SEI), Southern Company, and Georgia Power hosted a workshop aimed at imparting new information and sparking innovative ideas around the Tech Square Microgrid (TSMG) and the use of its data in education and research. 

Launched in 2021 with a 1.4-megawatt capacity, the microgrid is located on Williams Street, just south of Fifth Street in Tech Square. It is a joint project between Georgia Power and Georgia Tech.

The workshop brought together experts and enthusiasts to discuss the current operations of the TSMG, an essential asset for the energy resilience of Georgia Tech’s High-Performance Computing Center located next to Coda, and to share Georgia Tech studies that use data from the microgrid.

The workshop started with an overview of the microgrid’s current status and capabilities as a resilience resource, provided by Collins Pratt, the TSMG managing engineer from Georgia Power. This was followed by a keynote on TSMG modeling and simulation presented by GTRI research engineer and SEI’s lead on cybersecurity of critical infrastructure initiative, Sam Litchfield, and Adam King, a GTRI research engineer and Ph.D. student. Their insights into the state of the art of microgrid modeling and its role in assessing dependencies between energy grid resources set the stage for the rest of the workshop discussions.

During the panel on “Microgrids and Living Labs,” panelists from academia, Georgia Tech’s Office of Sustainability, and Georgia Power shared their perspectives on microgrid infrastructure and its role in research and education. The discussion emphasized the importance of microgrids as living labs, their potential for wider deployment in distributed energy systems, and the need for skilled graduates in the electrical utility workforce.

To conclude the event, attendees toured the microgrid site across the street. The tour, led by Pratt, provided a firsthand look at the microgrid infrastructure and its operating capabilities.

Reflecting on the significance of the microgrid, SEI’s Interim Executive Director Christine Conwell said, "The data from the microgrid is a vital resource for researchers at Georgia Tech and our metro Atlanta partners. It not only showcases our work in energy resilience but also serves as a living laboratory for developing innovative energy solutions."

Georgia Tech Senior Research Engineer Scott Duncan, who leads the Microgrids initiative at SEI organized the workshop along with Southern Company Principal Research Engineer Andrew Ingram. "The details shared during the workshop have sparked numerous ideas, from an array of perspectives across Georgia Tech, on how we can further utilize the microgrid and the unique data coming from its operations,” said Duncan. “The insights gained today will undoubtedly seed future research and collaborations, pushing the boundaries of what we can achieve in energy resilience."

Andrei Fedorov, Associate Chair for Graduate Studies, Rae S. and Frank H. Neely Chair, and professor in the George W. Woodruff School of Mechanical Engineering, will represent Georgia Tech in a new international research initiative. The program, Adopting Sustainable Partnerships for Innovative Research Ecosystem (ASPIRE) for Top Scientists, is funded by the Japan Science and Technology Agency. It will receive approximately $3.2 million in funding over five years.

The award will support a broad spectrum of multidisciplinary research activities by the multinational teams and intermediate to long-term (three months to one year) collaborative visits to global research sites in Japan, Europe, and the U.S. A total of 46 proposals were submitted to ASPIRE for Top Scientists, out of which 14 were selected by expert evaluation. Each project is an international collaboration and the initiative's key focus is advancing science and technology on an international level.

Fedorov will lead a project titled "Construction of International Data and Analysis Platform for Inorganic Power-storage Materials Informatics with Nano/Micro-Structure" that will explore the intersection of Artificial Intelligence (AI) and Informatics, and Energy. He will represent Georgia Tech as a principal investigator. The planned research will also involve faculty members and graduate students from College of Engineering schools involved in the Strategic Energy Institute.

Read the full story on the George W. Woodruff School of Mechanical Engineering website.

The "solar rebound effect" is a phenomenon where households with residential solar photovoltaic (PV) systems end up consuming more electricity in response to greater solar energy generation. This outcome arises because the cost savings from generating their own electricity lead to increased usage. A recent study by Matthew E. Oliver from the Georgia Institute of Technology and his co-authors, Juan Moreno-Cruz from the University of Waterloo and Kenneth Gillingham from Yale University, delves into this effect, providing crucial insights for policymakers and researchers.

The study, titled "Microeconomics of the Solar Rebound under Net Metering," explores how different net metering policies influence the solar rebound effect. Net metering allows households to sell excess electricity generated by their solar panels back to the grid, often at the retail rate. This policy makes solar PV systems more financially attractive but also impacts household behavior.

The authors developed a theoretical framework to understand the solar rebound. They found that under classic net metering, the rebound is primarily an income effect. Households feel wealthier due to the savings on their electricity bills and thus consume more electricity. However, under net billing, where excess electricity is compensated at a lower rate, a substitution effect also comes into play. This means households might change their consumption patterns based on the relative costs of electricity from the grid versus their solar panels.

The study also incorporates behavioral economics concepts like moral licensing and warm glow effects. Moral licensing occurs when people justify increased consumption because they feel they are already doing something good, like generating green energy. Warm glow refers to the positive feelings from contributing to environmental sustainability, which can either increase or decrease consumption depending on the household's values.

One of the key takeaways from the study is the importance of the regulatory environment. Policymakers need to carefully design net metering policies to balance promoting solar adoption while accounting for the possibility that rebound effects may offset the desired outcomes of grid resilience and reduced greenhouse gas emissions. For instance, switching from net metering to net billing might reduce the rebound effect, leading to better environmental outcomes.

The welfare analysis conducted by the authors shows that the solar rebound's impact on social welfare depends on various factors, including the cleanliness of the electricity grid and the external costs of electricity production. In cleaner grids, the rebound might be less detrimental, while in grids reliant on fossil fuels, it could negate some of the environmental benefits of solar adoption.

This research underscores the complexity of energy policy and the need for nuanced approaches that consider both economic and behavioral factors. By understanding the solar rebound effect, stakeholders can make more informed decisions to promote sustainable energy use.

For more detailed insights, you can explore the full study by Matthew E. Oliver and his co-authors. Their work provides a robust foundation for future empirical research and policy development in the field of renewable energy.

This article was written with the assistance of Microsoft Copilot (Jan. 27, 2025) and edited by Georgia Tech EPIcenter's Gilbert X. Gonzalez and Matthew E. Oliver.

EnergyHack @GT, Georgia Tech’s inaugural student-run energy and sustainability hackathon, kicked off Jan. 17-19, 2025. Organized by the Energy Club at Georgia Tech, the mission of the hackathon was to unite passionate students to tackle critical challenges in the energy industry while fostering innovation and collaboration. 

Over the course of 36 hours, participants collaborated in teams to brainstorm, design, and prototype projects that promote sustainable practices based on diverse problem statements, addressing this year’s tracks: energy storage, energy security, and decarbonization. These themes targeted urgent issues, from balancing renewable energy supply and demand to safeguarding infrastructure against cyber threats and reducing greenhouse gas emissions. The projects were evaluated by a panel of judges. 

Along with showcasing keynote speeches and educational workshops, the event culminated with the top three teams winning cash prizes. With more than 100 registered participants, 17 project submissions, and leaders from some of the biggest energy and tech companies, EnergyHack @GT successfully fostered collaboration and showcased the potential of student-driven solutions for advancements in energy and sustainability. 

“The inaugural student-led EnergyHack was a tremendous success, and I am incredibly proud of the committee members for turning this brilliant idea into an outstanding event,” Dan Molzahn, assistant professor in the School of Electrical and Computer Engineering and faculty advisor for the Energy Club, said. “Their dedication and hard work truly brought this vision to life, fostering innovation and collaboration within the vibrant Georgia Tech student community.” 

The event kicked off with an engaging opening ceremony featuring inspiring keynote speeches that set the tone for the hackathon’s ambitious objectives. Jessica Roberts, assistant professor in the School of Interactive Computing, shared insights into models used to track coal pollution sources and their dispersion across the United States. Steve Hummel, senior vice president at Chart Industries, discussed how artificial intelligence (AI) is reshaping demand projections and driving diversification in generation portfolios. Following the presentations, participants joined a dynamic team mixer to form diverse, multidisciplinary teams and networked with professionals from Kimley-Horn in a dedicated session. 

Throughout the hackathon, participants had access to expert-led workshops and mentorship. A session on "Machine Learning (ML) and AI for Materials Screening and Discovery" by Victor Fung, assistant professor in the School of Computational Science and Engineering, explored the role of AI in advancing sustainable materials. A meet and greet with keynote speakers allowed participants to engage in thought-provoking discussions on energy and sustainability issues. 

The energy and creativity peaked during the Project Expo, where 17 innovative solutions were showcased. Representatives from NVIDIA, GE Vernova, and other industry leaders reviewed projects, offering insights and feedback. 

The closing ceremony celebrated the participants’ achievements and the event highlights, featuring a keynote by Priya Donti, assistant professor at the Massachusetts Institute of Technology's Department of Electrical Engineering and Computer Science and Laboratory for Information and Decision Systems, and founder of Climate Change AI, on using AI to combat climate change and to build sustainability solutions. 

EnergyHack @GT served as a platform for innovation and learning, showcasing the potential of student-led initiatives in shaping the future of energy and sustainability. Awards were presented to the top three projects that stood out for their creativity and impact: 

• Best Overall Hack: Watts The Power, a project that predicts the energy and environmental impact of training ML models, earned the team a $250 cash prize. 
• Second Place: EcoTokens, a Chrome extension designed to reduce token usage in AI tools to save energy, won a $150 prize.
• Third Place: Eco Charge, an electric vehicle charging optimizer designed to minimize CO₂ emissions, secured a $100 prize.

Exponential growth in big data and computing power is transforming climate science, where machine learning is playing a critical role in mapping the physics of our changing climate.

 “What is happening within the field is revolutionary,” says School of Earth and Atmospheric Sciences Associate Chair and Professor Annalisa Bracco, adding that because many climate-related processes — from ocean currents to melting glaciers and weather patterns — can be described with physical equations, these advancements have the potential to help us understand and predict climate in critically important ways. 

Bracco is the lead author of a new review paper providing a comprehensive look at the intersection of AI and climate physics.

The result of an international collaboration between Georgia Tech’s Bracco, Julien Brajard (Nansen Environmental and Remote Sensing Center), Henk A. Dijkstra (Utrecht University), Pedram Hassanzadeh (University of Chicago), Christian Lessig (European Centre for Medium-Range Weather Forecasts), and Claire Monteleoni (University of Colorado Boulder), the paper, ‘Machine learning for the physics of climate,’ was recently published in Nature Reviews Physics. 

“One of our team’s goals was to help people think deeply on how climate science and AI intersect,” Bracco shares. “Machine learning is allowing us to study the physics of climate in a way that was previously impossible. Coupled with increasing amounts of data and observations, we can now investigate climate at scales and resolutions we’ve never been able to before.”

Connecting hidden dots

The team showed that ML is driving change in three key areas: accounting for missing observational data, creating more robust climate models, and enhancing predictions, especially in weather forecasting. However, the research also underscores the limits of AI — and how researchers can work to fill those gaps.

“Machine learning has been fantastic in allowing us to expand the time and the spatial scales for which we have measurements,” says Bracco, explaining that ML could help fill in missing data points — creating a more robust record for researchers to reference. However, like patching a hole in a shirt, this works best when the rest of the material is intact.

“Machine learning can extrapolate from past conditions when observations are abundant, but it can’t yet predict future trends or collect the data we need,” Bracco adds. “To keep advancing, we need scientists who can determine what data we need, collect that data, and solve problems.”

Modeling climate, predicting weather

Machine learning is often used when improving climate models that can simulate changing systems like our atmosphere, oceans, land, biochemistry, and ice. “These models are limited because of our computing power, and are run on a three-dimensional grid,” Bracco explains: below the grid resolution, researchers need to approximate complex physics with simpler equations that computers can solve quickly, a process called ‘parameterization’.

Machine learning is changing that, offering new ways to improve parameterizations, she says. “We can run a model at extremely high resolutions for a short time, so that we don’t need to parameterize as many physical processes — using machine learning to derive the equations that best approximate what is happening at small scales,” she explains. “Then we can use those equations in a coarser model that we can run for hundreds of years.”

While a full climate model based solely on machine learning may remain out of reach, the team found that ML is advancing our ability to accurately predict weather systems and some climate phenomena like El Niño. 

Previously, weather prediction was based on knowing the starting conditions — like temperature, humidity, and barometric pressure — and running a model based on physics equations to predict what might happen next. Now, machine learning is giving researchers the opportunity to learn from the past. “We can use information on what has happened when there were similar starting conditions in previous situations to predict the future without solving the underlying governing equations,” Bracco says. “And all while using orders-of-magnitude less computing resources.”

The human connection

Bracco emphasizes that while AI and ML play a critical role in accelerating research, humans are at the core of progress. “I think the in-person collaboration that led to this paper is, in itself, a testament to the importance of human interaction,” she says, recalling that the research was the result of a workshop organized at the Kavli Institute for Theoretical Physics — one of the team’s first in-person discussions after the Covid-19 pandemic.

“Machine learning is a fantastic tool — but it's not the solution to everything,” she adds. “There is also a real need for human researchers collecting high-quality data, and for interdisciplinary collaboration across fields. I see this as a big challenge, but a great opportunity for computer scientists and physicists, mathematicians, biologists, and chemists to work together.”

 

Funding: National Science Foundation, European Research Council, Office of Naval Research, US Department of Energy, European Space Agency, Choose France Chair in AI.

DOI: https://doi.org/10.1038/s42254-024-00776-3

 

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