�������� researchers are leading and collaborating on four research projects as part of Phase 1 in the U.S. Department of Energy (DOE) , a national initiative to build an AI-for-science ecosystem which accelerates breakthroughs in energy, discovery science and national security.��

The DOE awarded a total of 278 Genesis Mission awards for projects that involve more than 300 participating institutions, including DOE and National Nuclear Security Administration national laboratories, universities and companies. As part of the Genesis Mission, awardees will have access to the Genesis Mission Platform, which includes AI frameworks, advanced AI models from industry partners, and high-performance computing resources across DOE’s National Laboratories and partner facilities.��

“The Genesis Mission represents the kind of bold, collaborative approach needed to accelerate the complex scientific and technological breakthroughs required in our rapidly changing world,” said UW Vice Provost for Research . “Its emphasis on bringing together diverse expertise and cutting-edge technology with strategic partnerships highlights the important role universities play in driving innovation for the nation.”��

The UW-supported Genesis projects span disciplines including advanced sensing technologies, protein design for microelectronic applications, and astronomy data infrastructure, demonstrating the broad potential of AI to accelerate scientific discovery.��

, assistant professor of electrical and computer engineering, received a Genesis award to develop neuromorphic terahertz imaging technology for next-generation augmented reality systems. ��

“Neuromorphic terahertz imagers, or brain-inspired imaging in the terahertz band, give us superhuman vision to see through optically obscured media in real time by combining sensing and computation in a single piece of hardware. The Genesis Mission award supports our research in developing the hardware for the neuromorphic terahertz imager, as well as creating a digital twin of the entire system to train imaging models before implementing them on the actual hardware. This is an important step for future terahertz imaging systems on augmented reality hardware,” Naghavi said. ��

Building on research conducted in UW’s , the project brings together collaborators at Texas A&M University, the University of Utah, ChipNexus and NVIDIA to integrate sensing and computation directly within imaging hardware. By reducing the amount of data that must be transferred between sensors and processors, the technology could enable lightweight, low-cost augmented reality headsets capable of seeing through visually obscured materials in real time while operating with far lower power consumption than conventional systems.����

, director of the , and his colleagues are contributing to two Phase I Genesis Mission projects that apply advances in protein design and artificial intelligence to challenges beyond traditional biomedical applications.��

One project, BIND (Biophysics-Informed Learning of Coordination for Metalloprotein Design), led by the Lawrence Livermore National Laboratory, seeks to develop an AI framework for designing selective metal-binding proteins. The project leverages quantum chemistry, structural biology, machine learning and high-throughput experimentation to advance the computational design strategies of next-generation rare earth element binders. ��These advancements will catalyze change in critical mineral recovery, radionuclide management and environmental monitoring, while advancing DOE priorities in predictive biosystems design. ��

The second project, led by Pacific Northwest National Laboratory, will develop an AI-guided loop for the design, fabrication and evaluation of microelectronic devices. The team will leverage proteins designed to assemble on van der Waals substrates to modulate their properties and organize charge carriers within the synthesized hybrid materials, integrating deep-learning protein models with AI-guided material synthesis and characterization, device fabrication and measurements, and circuit-level performance evaluation to create an iterative design process that improves molecules, materials, and device design. ��

Both IPD projects demonstrate how UW-developed protein design technologies are expanding into new areas of chemistry, materials science, and advanced manufacturing. “The Genesis Mission award provides necessary support to develop data that will vastly improve our models, an essential next step in delivering advances for key global challenges,” Baker said.����

, director of the and founding director of the and , a researcher at DiRAC, are partnering with researchers at Carnegie Mellon University to help develop infrastructure that will make it easier for astronomers to combine and analyze data from a wide range of observatories and scientific instruments. ��

Their project will expand data formats and analysis platforms to support images, spectra, data cubes and other forms of astronomical data while enabling seamless access to information distributed across cloud and high-performance computing systems. The goal is to remove technical barriers that often slow scientific discovery and make large, multimodal datasets more accessible for AI research. ��

“We want the plumbing to be boring so the astronomy can be spectacular,” Caplar said.��

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Today’s wireless technologies harness chunks of the for myriad uses — radio waves broadcast TV and radio; microwaves transmit cellphone signals and cook our food; X-rays image our bodies; gamma rays kill cancerous cells.

, however, is interested in more neglected slices of the spectrum. Naghavi, an assistant professor of electrical and computer engineering at the ��������, studies the “terahertz band,” a region of the spectrum . Terahertz frequencies are notoriously difficult to work with, but they hold enormous potential in the fields of sensing, imaging and communications — future sensors, for example, could help firefighters “see” through smoke during rescue operations.

Naghavi recently joined a cohort of researchers from across the country who were awarded grants by the U.S. Department of Energy’s , an initiative to apply artificial intelligence across a wide range of research areas; other UW researchers are part of a Genesis-funded project to advance AI-driven cosmology. With the grant, Naghavi plans to develop compact, efficient sensors that could enable wearable gadgets to image their environment in new ways.

UW News caught up with Naghavi to learn about his new project and how it extends his work on terahertz frequencies.

What is the terahertz band and why are you studying it?

Hossen Naghavi: The terahertz band is a segment of the electromagnetic spectrum that lies between 100 gigahertz and 10 terahertz — the microwave band sits below it, and the optical band sits above it. That position gives terahertz waves a unique combination of microwave and optical properties. Microwaves can see through opaque materials like clothing, smoke or fire, but their long wavelengths limit the resolution of microwave imaging. Optical waves have the opposite problem. Their wavelengths are short, so they produce high-resolution images, but most materials block visible light completely, which makes it impossible to see inside or behind an object.

Terahertz waves are a sort of “happy medium.” Their wavelengths are short enough to give useful resolution but long enough to see through many materials. That combination allows us to build new sensors and cameras that can detect concealed objects or image scenes through smoke, dust and other conditions that defeat conventional optics.

What are some applications you envision for terahertz frequencies?

HN: is expected to become a defining mode of human-computer interaction, but realizing its full potential requires machines that can perceive and understand their surroundings far beyond what the human eye can see. Consider a high-stakes setting such as firefighting, where an augmented reality headset powered by terahertz waves could help firefighters locate victims or identify hazardous materials through smoke, fog and debris.��

Beyond firefighting and emergency response, terahertz technologies could also aid in autonomous navigation, security screening, industrial inspection, biomedical sensing, molecular spectroscopy, agricultural applications, and 5G and 6G communication networks.��

Sounds exciting! What’s the catch?

HN: Sensors that use terahertz waves, like the ones in our firefighting headset example, have been demonstrated in the lab. However, low-cost, low-power electronics that would be practical in a wearable device have not yet been developed.

Terahertz sensors produce high-resolution image streams, and processing them conventionally means moving enormous amounts of data to a central processor for analysis by an artificial intelligence system. That consumes too much power and adds too much delay to be practical in a lightweight device meant to be worn all day.

Tell us about your new project. How will it address some of the hurdles facing terahertz technologies?

HN: The usual way to build a terahertz imager is to split the job in two. The radar sensor collects raw signals, and a separate processor turns the signals into a picture. That division sounds sensible, but it is the source of most of the trouble. The raw signals arriving at each of the sensor’s antennas are slightly out of step with one another, and the processor has to line them all up before an image can form. That alignment requires a lot of continuous computation, which drains batteries quickly and introduces lag.

The natural comparison is the human eye. Your retina does not ship every photon to your brain for interpretation. It processes what it sees on the spot and passes along something much more compact, which is part of why vision costs your body so little energy. We are trying to give a terahertz sensor the same quality, which is why we describe the design as “neuromorphic,” meaning “brain-inspired.”

Who are you working with on this technology, and what’s next?

HN: My group at the UW and ‘s group at Texas A&M University are designing and building the sensor hardware. at the University of Utah and at ChipNexus are developing and implementing the AI system. This is a highly collaborative project.

Our next big milestone is to demonstrate a terahertz neuromorphic imager as a proof of concept in Phase I of our Genesis Mission project. Moving forward, we hope to expand the project into Phase II to add even more capabilities and make this technology accessible for public usage as early as possible.

For more information, contact Naghavi at naghavi@uw.edu.

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