In psychology and neuroscience research, a host of behaviors fall under the cognitive umbrella: learning, perceiving the environment, storing memories, and making decisions are just a few. Much like binary code underpins complex computational processes, researchers have long been searching for the molecular mechanisms that enable cognition.

Farzaneh Najafi, an assistant professor in Georgia Tech’s School of Biological Sciences(SBS) , recently received multiple awards that will enable her to dig deeper into the molecular origins of cognitive processes, with the help of interdisciplinary teams.

“If we want to understand cognition, we really have to start small: at the level of molecules, genes, and the genome, and then work our way up to systems, behavior, and cognition,” says Najafi. “Impactful discoveries happen when people from different disciplines come together and collaborate. That’s how we make real breakthroughs.”

Two of her recent awards stem from the third and final year of the Scialog: Molecular Basis of Cognition initiative. Funded by the Research Corporation for Science Advancement (RCSA), the Frederick Gardner Cottrell Foundation, and the Walder Foundation, this initiative has provided 48 multidisciplinary teams with more than $2.4 million to advance this area of research.

“It’s exciting that Farzaneh has won not just one, but two team-based Scialog awards,” said SBS School Chair Jeffrey (Todd) Streelman. “Solving big problems in neuroscience often requires teams, and Farzaneh is well-placed to apply this in her research program.”

With additional funding from the Whitehall Foundation and Chan Zuckerberg Initiative, Najafi is set to lead several interdisciplinary projects to uncover the role of the cerebellum and neocortex (the brain’s outer layer) across distinct cognitive processes. 

“At the end of the day, the goal is to develop effective therapeutics,” says Najafi, whose work has long aimed to better understand and treat psychiatric and neurological disorders. “To develop targeted treatments, we have to identify the molecules that are at the core of these cognitive processes.”

Deeper than thought

Throughout her career, Najafi has focused on how the brain makes and uses predictions to influence learning and behavior, with a particular focus on an area in the back of the brain called the cerebellum.

“Without those predictions, our perceptions and actions would be significantly delayed, which could impact our survival,” explains Najafi. “Learning happens when we update those predictions to better align with the world around us.”

Najafi will bring that cerebellar expertise to two collaborative teams with the Scialog initiative.

Working with researchers from Stanford University and Case Western Reserve University, one of Najafi’s Scialog projects will focus on how sleep deprivation alters the 3D structure of genetic material in different species’ cerebellum— and investigate potential mechanisms to reverse those changes. 

Her second project, in collaboration with researchers from University of California San Francisco and Duke University, explores how the brain chemical norepinephrine affects cerebellar activity across species. This research aims to understand the cerebellum's role in behavioral flexibility and adaptation, revealing how these chemical signals influence various brain functions.

Working across disciplines

Formed at the October 2024 Scialog meeting, Najafi’s two collaborative teams are part of an RCSA initiativethat unites early career scientists in advancing basic science and developing high-risk, high-reward research projects. The Scialog: Molecular Basis of Cognition initiative, begun in 2022, annually gathered around 50 early career researchers to create collaborative proposals.

“The best part of the Scialog meeting was connecting with people from all kinds of disciplines. They worked with different species, used a variety of experimental and computational tools, and some attendees came from non-neuroscience backgrounds,” says Najafi. “I had no idea that these were the topics I was going to write about — they only came about because of the inspiring conversations I had at the meeting. I really loved the experience.”

Both Scialog teams are highly interdisciplinary, with researchers bringing expertise in different techniques and species to the team. Even within her own lab, Najafi attributes impactful research to interdisciplinary teams.

“The only way to solve big questions in neuroscience is through an interdisciplinary approach,” says Najafi, who is affiliated with two Interdisciplinary Research Institutes (IRI) at Georgia Tech: the Parker H. Petit Institute for Bioengineering and Bioscience and the Neuro Next Initiative, a nascent IRI in neuroscience and society. “What’s great about Georgia Tech is its strong emphasis on interdisciplinary collaboration. With these research institutes, the infrastructure is already in place, and they're actively working to expand it.”

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

 

Georgia Institute of Technology is set to play a crucial role in a strategic effort funded by the Defense Advanced Research Project Agency (DARPA) to help bolster America’s national security and global military leadership.  

The project, led by the Texas Institute for Electronics (TIE) at The University of Texas at Austin, represents a total investment of $1.4 billion. The $840 million award from DARPA, announced by TIE in 2024, aims to develop the next generation of high-performing semiconductor microsystems for the Department of Defense (DoD). 

“We are honored to collaborate with TIE and its broader team on this far reaching and strategic program to enable best in class 3D heterogeneous integration (3DHI) processes and technologies in the United States,” said Muhannad S. Bakir, the Dan Fielder Professor in the School of Electrical and Computer Engineering and director of the 3D Systems Packaging Research Center, who is heading the project for Georgia Tech. 

3DHI is a semiconductor manufacturing process that incorporates different materials and components into microsystems with precision assembly. The use of 3DHI allows for the creation of high-performance, compact, and energy-efficient systems. 

The investment is part of DARPA’s Next Generation Microelectronics Manufacturing (NGMM) Program comprised of 32 defense electronics and leading commercial semiconductor companies and 18 nationally recognized academic institutions.

Under the agreement, TIE will establish a national open access R&D and prototyping fabrication facility. The facility will enable the DoD to create higher performance, lower power, lightweight, and compact defense systems. The advancements are expected to have wide-ranging applications, including radar, satellite imaging, and unmanned aerial vehicles.  

Georgia Tech will provide a wide range of expertise in 3DHI including design, fabrication and assembly processes, and characterization to support the NGMM national open-access R&D and prototyping facility at TIE.  

Regents' Professor and Morris M. Bryan, Jr. Professor Suresh K. Sitaraman in the George W. Woodruff School of Mechanical Engineering will be a key contributor to Georgia Tech’s efforts on the project.

“We are delighted to be partnering with UT/TIE on the establishment of a 3D Heterogeneous Integration Microsystem prototyping  facility,” said Sitaraman. “In addition to advancing fundamental science, this project is a great opportunity for Georgia Tech to demonstrate and integrate our ground-breaking and innovative 3DHI research approaches and technology solutions into TIE’s prototyping facility, and understand the challenges involved when translating lab-scale research work to a large industry-strength fabrication facility.” 

ECE Professors Saibal Mukhopadhyay, Arijit Raychowdhury, Visvesh Sathe, and Shimeng Yu will be working alongside Bakir and Sitaraman. 

A significant portion of the research will be conducted at the Institute for Matter and Systems (IMS), which operates Georgia Tech’s state-of-the-art electronics and nanotechnology core facilities. 

Read the press release from TIE and view the project’s team and partners.  

Read Full Article on the College of Engineering Webpage

A researcher in Georgia Tech’s School of Interactive Computing has received the nation’s highest honor given to early career scientists and engineers.

Associate Professor Josiah Hester was one of 400 people awarded the Presidential Early Career Award for Scientists and Engineers (PECASE), the Biden Administration announced in a press release on Tuesday.

The PECASE winners’ research projects are funded by government organizations, including the National Science Foundation (NSF), the National Institutes of Health (NIH), the Centers for Disease Control and Prevention (CDC), and NASA. They will be invited to visit the White House later this year.

Hester joins Associate Professor Juan-Pablo Correa-Baena from the School of Materials Science and Engineering as the two Tech faculty who received the honor.

Hester said his nomination was based on the NSF Faculty Early Career Development Program (CAREER) award he received in 2022 as an assistant professor at Northwestern University. He said the NSF submits its nominations to the White House for the PECASE awards, but researchers are not informed until the list of winners is announced.

“For me, I always thought this was an unachievable, unassailable type of thing because of the reputation of the folks in computing who’ve won previously,” Hester said. “It was always a far-reaching goal. I was shocked. It’s something you would never in a million years think you would win.”

Hester is known for pioneering research in a new subfield of sustainable computing dedicated to creating battery-free devices powered by solar energy, kinetic energy, and radio waves. He co-led a team that developed the first battery-free handheld gaming device.

Last year, Hester co-authored an article published in the Association of Computing Machinery’s in-house journal, the Communications of the ACM, in which he coined the term “Internet of Battery-less Things.”

The Internet of Things is the network of physical computing devices capable of connecting to the internet and exchanging data. However, these devices eventually die. Landfills are overflowing with billions of them and their toxic power cells, harming our ecosystem.

In his CAREER award, Hester outlined projects that would work toward replacing the most used computing devices with sustainable, battery-free alternatives.

“I want everything to be an Internet of Batteryless Things — computational devices that could last forever,” Hester said. “I outlined a bunch of different ways that you could do that from the computer engineering side and a little bit from the human-computer interaction side. They all had a unifying theme of making computing more sustainable and climate-friendly.”

Hester is also a Sloan Research Fellow, an honor he received in 2022. In 2021, Popular Sciene named him to its Brilliant 10 list. He also received the Most Promising Engineer or Scientist Award from the American Indian Science Engineering Society, which recognizes significant contributions from the indigenous peoples of North America and the Pacific Islands in STEM disciplines.

President Bill Clinton established PECASE in 1996. The White House press release recognizes exceptional scientists and engineers who demonstrate leadership early in their careers and present innovative and far-reaching developments in science and technology.

Associate Professor Marta Hatzell has been appointed interim deputy director of the Georgia Tech Strategic Energy Institute (SEI).

Hatzell currently leads the industrial decarbonization and clean catalysis initiative at SEI and holds joint appointments in the George W. Woodruff School of Mechanical Engineering and the School of Chemical and Biomolecular Engineering. Most recently, she led the Materials for Carbon-Neutral Fuel Production track at this year’s Energy Materials Day, which attracted over 400 participants from academia and industry. 

“Marta has been an outstanding addition to SEI’s initiative lead program, where her contributions have already made a significant impact. I am excited to see her further engage with the Georgia Tech energy community in this role,” said Christine Conwell, SEI interim executive director.

Hatzell’s research group focuses on exploring sustainable catalysis and separations to enable clean energy, water, and food production. She serves as the site principal investigator and research thrust leader for CASFER, the National Science Foundation Engineering Research Center (NSF-ERC) with funding of $26 million for advancing sustainable fertilizer production. She is also a principal investigator in the Department of Energy’s $100 million National Alliance for Water Innovation project. 

Hatzell is the recipient of the NSF Early CAREER Award for her work on distributed solar fertilizers and received the Gordon and Betty Moore Inventor fellowship to work on a low-cost, photocatalytic air-breathing system that converts air into liquid, ammonia-based fertilizer. She also received the 2020 Sloan Research Fellowship in Chemistry and the American Chemical Society’s (ACS) Sustainable Chemistry Lectureship Award in 2024. Hatzell serves as a senior editor of the ACS Energy Letters journal.

Before her role at Georgia Tech, she was a postdoctoral researcher in the Department of Materials Science and Engineering at the University of Illinois Urbana-Champaign. She holds a Ph.D. in mechanical engineering from Penn State University. 

“I’m looking forward to working with the SEI staff and faculty to continue to grow Georgia Tech’s impact on the rapidly changing energy sector,” says Hatzell.