Science & Technology

��ƷSM��ӰƬ delivers impactful research and creative work, despite federal funding uncertainty

Megan Maneval — Fri, 31 Oct 2025 17:04:13 +0000

��ƷSM��ӰƬ delivers impactful research and creative work, despite federal funding uncertainty Megan Maneval Fri, 10/31/2025 - 11:04

��ƷSM��ӰƬ researchers continued to deliver meaningful, positive outcomes in the university's public research mission through strong results in fiscal year 2024–25. Highlights of their work include big innovations in quantum technology, improving our understanding of space weather, and enhancing environmental resiliency.

The pace of growth in research funding at ��ƷSM��ӰƬ tapered in the new year due to cuts and funding pauses by federal agencies, including the U.S. National Science Foundation (NSF), National Institutes of Health (NIH) and NASA. At $766.7 million, the newly released sponsored research funding numbers for ��ƷSM��ӰƬ reflect a 3.3% increase over the prior year.

��ƷSM��ӰƬ drives $5B boost to Colorado's economy

“The research, scholarship and creative work produced by ��ƷSM��ӰƬ faculty, researchers and students directly impacts people’s lives,” said Massimo Ruzzene, senior vice chancellor for research and innovation and dean of the institutes. “We are committed to advocating for the support needed to drive advances that strengthen our national security, enhance peoples’ health, ensure our nation’s continued leadership in scholarship and innovation, and spark economic development in Colorado and beyond.”

The bulk of the research funding, or 69%, comes from federal agencies, including NASA, the NSF, the National Oceanic and Atmospheric Administration (NOAA), the National Institute of Standards and Technology (NIST), NIH, the Department of Defense and the Department of Energy. The state of Colorado contributed $15 million of the total. Nonprofits and international organizations supported ��ƷSM��ӰƬ research and creative work to the tune of $102 million; industry accounted for $31 million; and other universities provided $47 million of the funding.

Here are a few research program highlights from ��ƷSM��ӰƬ.

Innovating at a quantum scale

The NSF invested $20 million in ��ƷSM��ӰƬ to launch a facility known as the National Quantum Nanofab. In this facility, Colorado researchers and quantum specialists from industry and research institutions around the country will design and build devices that tap into the world of the tiny packets of energy that make up light.

Principal Investigator Scott Diddams, professor in the Department of Electrical, Computer and Energy Engineering, alongside a team of physicists and engineers, leads the work in this makerspace.

Improving understanding of space weather

A team at the Laboratory for Atmospheric and Space Physics (LASP) has received $2 million to develop a concept study for a NASA mission that will investigate how Earth’s lower atmosphere influences the upper atmosphere. The results will improve and expand our understanding of the space weather system surrounding our planet.

The group, which is led by LASP researcher Aimee Merkel, is one of three selected by NASA to develop detailed proposals for the agency’s DYNAMIC (Dynamical Neutral Atmosphere-Ionosphere Coupling) mission.

Helping communities adapt to climate change

��ƷSM��ӰƬ’s Cooperative Institute for Research in Environmental Sciences (CIRES) has received a new five-year, $1.4 million cooperative agreement to continue hosting the North Central Climate Adaptation Science Center (NC CASC) from the U.S. Geological Survey (USGS). Since its founding in 2018, the center provides actionable science to help communities, ecosystems and economies in Colorado, Wyoming, Montana, North Dakota, South Dakota, Kansas and Nebraska adapt to climate change.

Led by William Travis, associate professor of geography, the center advances the development and delivery of actionable science to help fish, wildlife, water, land and people in the North Central region adapt to a changing environment.

Learn more about NC CASC here.

Pairing humans and AI to help students learn

��ƷSM��ӰƬ joined six other teams that make up the Learning Engineering Virtual Institute (LEVI). The institute's goal is to double the rate of middle school math learning within five years, focusing on students from low-income backgrounds.

Professors Sidney D'Mello and Tamara Sumner of the Department of Computer Science and Institute of Cognitive Science join professors Peter Foltz, Jennifer Jacobs and Jeffrey Bush of the Institute of Cognitive Science in leading the project team. ��ƷSM��ӰƬ's project is the Hybrid Human-AI Tutoring (HAT) platform.

Learn more about LEVI and HAT.

Creating a Band-Aid for the heart

In the quest to develop lifelike materials to replace and repair human body parts, scientists face a formidable challenge: Real tissues are often both strong and stretchable and vary in shape and size. A ��ƷSM��ӰƬ-led team, in collaboration with researchers at the University of Pennsylvania, has taken a critical step toward cracking that code:

They’ve developed a new way to 3D print material that is at once elastic enough to withstand a heart’s persistent beating, tough enough to endure the crushing load placed on joints, and easily shapable to fit a patient’s unique defects.

A significant amount of sponsored research funding is directed to programs and researchers with unique expertise, such as biotechnology and aerospace, which stimulates industry.

Sponsored research funding from federal, state, international and foundation entities targets specific projects to advance research in laboratories and in the field. Research funding also helps pay for research-related capital improvements, scientific equipment, travel and salaries for research and support staff and student assistantships. CU cannot divert this funding to non-research-related expenses.

��ƷSM��ӰƬ researchers continued to deliver meaningful, positive outcomes in the university's public research mission through strong results in fiscal year 2024–25.

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Researchers aim to identify pika calls through 'acoustic fingerprinting'

Megan Maneval — Thu, 30 Oct 2025 19:31:43 +0000

Researchers aim to identify pika calls through 'acoustic fingerprinting' Megan Maneval Thu, 10/30/2025 - 13:31

INSTAAR

Chris Ray has studied pika populations in the West for nearly four decades. Today, she is collaborating with doctoral student Rachel Mae Billings on a project that could revolutionize the field.

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New 'molecular dam' stops energy leaks in nanocrystals

Megan Maneval — Tue, 28 Oct 2025 16:25:13 +0000

New 'molecular dam' stops energy leaks in nanocrystals Megan Maneval Tue, 10/28/2025 - 10:25

A molecular engineering breakthrough could make key light-driven reactions over 40 times more efficient.

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Migration no guarantee of bird biodiversity

Megan Maneval — Tue, 28 Oct 2025 16:15:12 +0000

Migration no guarantee of bird biodiversity Megan Maneval Tue, 10/28/2025 - 10:15

Colorado Arts and Sciences Magazine

��ƷSM��ӰƬ researchers are challenging long-held assumptions about the relationship between bird migration and the process by which new species arise.

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How animals get their spots, and why they are beautifully imperfect

Yvaine Ye — Thu, 23 Oct 2025 18:29:11 +0000

How animals get their spots, and why they are beautifully imperfect Yvaine Ye Thu, 10/23/2025 - 12:29

Yvaine Ye

From tiger stripes to leopard spots, the animal world is full of distinctive and intricate patterns.

In a new study, ��ƷSM��ӰƬ scientists refined their previous theory of how animal patterns form and successfully recreated imperfections in natural designs, like irregular spots on a leopard. The new mechanism, described October 27 in Matter, could lead to materials that can respond to their environment, such as fabrics that change color on demand for camouflage.

Top: A male ornate boxfish (Aracana ornata). Bottom left: A close-up picture of the fish’s natural hexagonal pattern. Bottom center: Fish pattern simulation based on Turing’s reaction-diffusion theory. Bottom right: Diffusiophoresis-enhanced reaction-diffusion simulation. (Credit: The Birch Aquarium/Scripps Institution of Oceanography and Benjamin Alessio/��ƷSM��ӰƬ)

“Imperfections are everywhere in nature,” said Ankur Gupta, the study’s lead researcher in the Department of Chemical and Biological Engineering. “We proposed a simple idea that can explain how cells assemble to create these variations.”

For decades, scientists have been trying to crack the code of how different animal patterns emerge from a mass of developing cells. In 1952, mathematician Alan Turing hypothesized that as tissue develops, it produces chemical agents that diffuse in the system in a process similar to pouring milk into coffee. Some of these chemicals activate pigment-producing cells, forming spots. Other chemicals inhibit these cells, creating the blank spaces in between.

But just as milk clouds the coffee, computer simulations based on Turing’s theory produced spots that were blurrier than those found in nature.

Updated simulations generated imperfect and textured hexagon and stripe patterns. (Credit: Siamak Mirfendereski and Ankur Gupta/��ƷSM��ӰƬ)

In 2023, Gupta and his collaborators improved upon Turing’s theory by adding another mechanism called diffusiopherosis, a process where diffusing particles pull other particles along with them. It’s the same principle that helps laundry get clean: As soap diffuses out of the laundry into water, it drags dirt out from the fabric.

When Gupta simulated the purple-and-black hexagon pattern seen on ornate boxfish, a flashy species found in the seas off Australia, he found that diffusiopherosis could generate patterns with sharper outlines than Turing’s original model.

But the team’s results were a little too perfect. All the hexagons were the same size and shape, and the spaces between them were identical.

In nature, no animal has flawless patterns. A zebra’s black stripes vary in thickness, and the hexagons on the boxfish are never perfectly uniform.

So Gupta and his team set off to improve the diffusiopherosis model.
They found that by giving individual cells defined sizes and modeling how each one moved through tissue, their simulations began producing imperfect patterns and textures.

Imagine ping-pong balls of different sizes traveling through a tube. Larger balls would create thicker outlines than smaller ones. When bigger cells cluster, they form patterns that are broader. Sometimes the balls bump into one another and jam the tube, breaking up a continuous line. When cells experience that, they create breaks in the stripes.

“We are able to capture these imperfections and textures simply by giving these cells a size,” Gupta said. Their simulations showed breaks and grainy textures that look far more like what’s found in nature.

In the future, Gupta plans to incorporate more complex interactions among cells and with the background chemical agents to improve their simulations.

Humans have always drawn inspiration from nature. Bats’ ability to navigate using echoes led to sonar technology, which locates objects through sound. Gupta said understanding how pattern-making cells assemble could help engineers design synthetic materials that can change colors based on the environment, much like a chameleon’s skin. It could also help design effective approaches to deliver medicine to a specific part of the body.

“We are drawing inspiration from the imperfect beauty of natural systems and hope to harness these imperfections for new kinds of functionality in the future,” Gupta said.

Engineers have developed a way to simulate natural animal patterns, including their imperfections. The findings could lead to new materials that turn to camouflage on demand.

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A yellow boxfish swimming next to corals. (Credit: Jeffry S.S./Pexels)

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A yellow boxfish swimming next to corals. (Credit: Jeffry S.S./Pexels)

Roam if you want to. Unless you're a wild animal

Megan Maneval — Thu, 23 Oct 2025 13:58:30 +0000

Roam if you want to. Unless you're a wild animal Megan Maneval Thu, 10/23/2025 - 07:58

College of Communication, Media, Design and Information

A new book from journalism Professor Hillary Rosner looks at human-made barriers—visible and not—that have disrupted animal migrations and threaten our ecology.

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AWS down: How a single network outage rippled through businesses, institutions and the economy

Amber Elise Carlson — Wed, 22 Oct 2025 21:33:19 +0000

AWS down: How a single network outage rippled through businesses, institutions and the economy Amber Elise Carlson Wed, 10/22/2025 - 15:33

Amber Carlson

Server racks are pictured in a data center. (Credit: Adobe Stock)

Amazon Web Services (AWS) made worldwide headlines on Monday when the service went offline for hours, disrupting popular apps, services and tools from Zoom and Venmo to Snapchat and Reddit.

According to Reuters, it was the biggest internet disruption since the cybersecurity firm CrowdStrike went down last year. It was also not the first time the AWS data center in northern Virginia has been implicated in a major outage.

What causes this type of network outage? What impacts can it have on businesses, institutions and the economy? And is there anything we can do to make such outages less likely in the future?

To answer these questions, we spoke with Levi Perigo, professor of computer science and co-director of ��ƷSM��ӰƬ’s Professional Master's Program in Network Engineering.

What happened and who did it impact?

The AWS outage was widespread and caused major disruptions for many businesses, resulting in what some experts estimate to be hundreds of billions of dollars in economic impact. The issue stemmed from a failure in the Domain Name System (DNS), which acts as the Internet’s “phone book.” DNS translates the easy-to-remember web addresses we use—like amazon.com—into the numeric IP addresses computers use to communicate.

When part of AWS’s internal DNS infrastructure went down, many of the services and websites hosted by AWS lost the ability to “find” each other. To users, it appeared that websites and applications were broken or offline. Even though DNS is a relatively simple technology, it’s a fundamental part of how the Internet works, so when it fails, the effects can be enormous.

What causes this type of outage to happen?

Levi Perigo

Outages like this can happen for several reasons, but most often it comes down to human or configuration errors that are amplified by the massive scale of operations at companies like AWS. To manage millions of systems efficiently, large cloud providers rely on network automation—essentially using software to configure and control their infrastructure.

In this case, it’s likely that a small misconfiguration or script error was deployed across thousands of systems, resulting in a large-scale failure. These incidents highlight the importance of careful testing, validation, and documentation, especially when automation is involved.

Could it happen again? How vulnerable are we?

Unfortunately, outages like this are always possible. The more we rely on centralized cloud platforms such as AWS, the more we share in their risk. The scale of this week’s disruption shows just how much of the internet depends on a few key providers. While AWS has strong and reliable overall, no system—no matter how advanced—is immune to failure.

What can we do to prevent this or reduce the risk of it happening again?

There are ways to reduce risk, though it’s difficult to eliminate it completely. One key strategy is called multi-cloud architecture—using multiple cloud providers (such as AWS, Google Cloud, and Microsoft Azure) to host services rather than relying on just one. This approach helps ensure that if one provider experiences an outage, the others can keep systems running.

Ultimately, incidents like this remind us that the internet is now critical infrastructure, and its reliability depends not only on technology, but also on careful design, operational discipline, and shared responsibility across providers and customers alike.

A ��ƷSM��ӰƬ network expert discusses Monday’s Amazon Web Services network outage and its wide-ranging impacts.

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5 ways to make AI more trustworthy

Amber Elise Carlson — Tue, 21 Oct 2025 14:52:17 +0000

5 ways to make AI more trustworthy Amber Elise Carlson Tue, 10/21/2025 - 08:52

Amber Carlson

A Waymo self-driving taxi. (Credit: Adobe Stock)

Self-driving taxis are sweeping the country and will likely start service in Colorado in the coming months. How many of us will be lining up to take a ride?

That depends on our level of trust, says Amir Behzadan, a professor in the Department of Civil, Environmental and Architectural Engineering, and a fellow in the Institute of Behavioral Science (IBS) at ��ƷSM��ӰƬ.

He and his team of researchers in the Connected Informatics and Built Environment Research (CIBER) Lab at ��ƷSM��ӰƬ are unearthing new insights into how the artificial intelligence (AI) technology we might encounter in daily life can earn our confidence. They’ve created a framework for developing trustworthy AI tools that benefit people and society.

And in a new paper in the journal AI and Ethics, Behzadan and his Ph.D. student Armita Dabiri drew on that framework to create a conceptual AI tool that incorporates the elements of trustworthiness.

“As a human, when you make yourself vulnerable to potential harm, assuming others have positive intentions, you’re trusting them,” said Behzadan. “And now you can bring that concept from human-human relationships to human-technology relationships.”

How trust forms

Behzadan studies the building blocks of human trust in AI systems that are used in the built environment, from self-driving cars and smart home security systems to mobile public transportation apps and systems that help people collaborate on group projects. He says trust has a critical impact on whether people will adopt and rely on them or not.

Trust is deeply embedded in human civilization, according to Behzadan. Since ancient times, trust has helped people cooperate, share knowledge and resources, form communal bonds and divvy up labor. Early humans began forming communities and trusting those within their inner circles.

Mistrust arose as a survival instinct, making people more cautious when interacting with people outside of their group. Over time, cross-group trade encouraged different groups to interact and become interdependent, but it didn’t eliminate mistrust.

We can see echoes of this trust-mistrust dynamic in modern attitudes toward AI, says Behzadan, especially if it’s developed by corporations, governments or others we might consider “outsiders.” So what does trustworthy AI look like? Here are five main takeaways from Behzadan’s framework.

1. It knows its users.

Amir Behzadan

Many factors affect whether—and how much—we trust new AI technology. Each of us has our own individual inclination toward trust, which is influenced by our ences, value system, cultural beliefs, and even the way our brains are wired.

“Our understanding of trust is really different from one person to the next,” said Behzadan. “Even if you have a very trustworthy system or person, our reaction to that system or person can be very different. You may trust them, and I may not.”

He said it’s important for developers to consider who the users are of an AI tool. What social or cultural norms do they follow? What might their preferences be? How technologically literate are they?

For instance, Amazon Alexa, Google Assistant and other voice assistants offer simpler language, larger text displays on devices and a longer response time for older adults and people who aren’t as technologically savvy, Behzadan said.

2. It’s reliable, ethical and transparent.

Technical trustworthiness generally refers to how well an AI tool works, how safe and secure it is, and how easy it is for users to understand how it works and how their data is used.

An optimally trustworthy tool must do its job accurately and consistently, Behzadan said. If it does fail, it should not harm people, property or the environment. It must also provide security against unauthorized access, protect users’ privacy and be able to adapt and keep working amid unexpected changes. It should also be free from harmful bias and should not discriminate between different users.

Transparency is also key. Behzadan says some AI technologies, such as sophisticated tools used for credit scoring or loan approval, operate like a “black box” that doesn’t allow us to see how our data is used or where it goes once it’s in the system. If the system can share how it’s using data and users can see how it makes decisions, he said, more people might be willing to share their data.

In many settings, like medical diagnosis, the most trustworthy AI tools should complement human expertise and be transparent about their reasoning with expert clinicians, according to Behzadan.

AI developers should not only try to develop trustworthy, ethical tools, but also find ways to measure and improve their tools’ trustworthiness once it is launched for the intended users.

3. It takes context into account.

There are countless uses for AI tools, but a particular tool should be sensitive to the context of the problem it’s trying to solve.

In the newest study, Behzadan and co-researcher Dabiri created a hypothetical scenario where a project team of engineers, urban planners, historic preservationists and government officials had been tasked with repairing and maintaining a historical building in downtown Denver. Such work can be complex and involve competing priorities, like cost effectiveness, energy savings, historical integrity and safety.

The researchers proposed a conceptual AI assistive tool called PreservAI that could be designed to balance competing interests, incorporate stakeholder input, analyze different outcomes and trade-offs, and collaborate helpfully with humans rather than replacing their expertise.

Ideally, AI tools should incorporate as much contextual information as possible so they can work reliably.

4. It’s easy to use and asks users how it’s doing.

The AI tool should not only do its job efficiently, but also provide a good user experience, keeping errors to a minimum, engaging users and building in ways to address potential frustrations, Behzadan said.

Another key ingredient for building trust? Actually allowing people to use AI systems and challenge AI outcomes.

“Even if you have the most trustworthy system, if you don't let people interact with it, they are not going to trust it. If very few people have really tested it, you can't expect an entire society to trust it and use it,” he said.

Finally, stakeholders should be able to provide feedback on how well the tool is working. That feedback can be helpful in improving the tool and making it more trustworthy for future users.

5. When trust is lost, it adapts to rebuild it.

Our trust in new technology can change over time. One person might generally trust new technology and be excited to ride in a self-driving taxi, but if they read news stories about the taxis getting in crashes, they might start to lose trust.

That trust can later be rebuilt, said Behzadan, although users can remain skeptical about the tool.

For instance, he said, the “Tay” chatbot by Microsoft failed within hours of its launch in 2016 because it picked up harmful language from social media and began to post offensive tweets. The incident caused public outrage. But later that same year, Microsoft released a new chatbot, “Zo,” with stronger content filtering and other guardrails. Although some users criticized Zo as a “censored” chatbot, its improved design helped more people trust it.

There’s no way to completely eliminate the risk that comes with trusting AI, Behzadan said. AI systems rely on people being willing to share data—the less data the system has, the less reliable it is. But there’s always a risk of data being misused or AI not working the way it’s supposed to.

When we’re willing to use AI systems and share our data with them, though, the systems become better at their jobs and more trustworthy. And while no system is perfect, Behzadan feels the benefits outweigh the downsides.

"When people trust AI systems enough to share their data and engage with them meaningfully, those systems can improve significantly, becoming more accurate, fair, and useful,” he said.

“Trust is not just a benefit to the technology; it is a pathway for people to gain more personalized and effective support from AI in return.”

Beyond the Story

Our research impact by the numbers:

$742 million in research funding earned in 2023–24
No. 5 U.S. university for startup creation
$1.4 billion impact of ��ƷSM��ӰƬ's research activities on the Colorado economy in 2023–24

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��ƷSM��ӰƬ engineers have designed a framework to help technology developers create artificial intelligence people will actually want to use.

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Open-source software allows for efficient 3D printing with multiple materials

Megan Maneval — Thu, 16 Oct 2025 20:06:43 +0000

Open-source software allows for efficient 3D printing with multiple materials Megan Maneval Thu, 10/16/2025 - 14:06

College of Engineering and Applied Science

Assistant Professor Robert MacCurdy and doctoral student Charles Wade have created an open-source software package that uses functions and code to map not just shapes but where different materials belong in a 3D object. The project has the potential to transform 3D printing by enabling engineers to design multi-material objects more smartly and efficiently.

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Nobel Laureate John Martinis once served as graduate student mentor at ��ƷSM��ӰƬ

Elizabeth Lock — Thu, 09 Oct 2025 21:04:56 +0000

Nobel Laureate John Martinis once served as graduate student mentor at ��ƷSM��ӰƬ Elizabeth Lock Thu, 10/09/2025 - 15:04

Like many rockstar scientists, 2025 Nobel Prize in Physics winner John Martinis spent time in Boulder's rich scientific ecosystem. Martinis mentored graduate students and inspired others in quantum computing.

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Science & Technology

��ƷSM��ӰƬ delivers impactful research and creative work, despite federal funding uncertainty

Innovating at a quantum scale

Improving understanding of space weather

Helping communities adapt to climate change

Pairing humans and AI to help students learn

Creating a Band-Aid for the heart

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AWS down: How a single network outage rippled through businesses, institutions and the economy

What happened and who did it impact?

What causes this type of outage to happen?

Could it happen again? How vulnerable are we?

What can we do to prevent this or reduce the risk of it happening again?

Related Articles

5 ways to make AI more trustworthy

How trust forms

1. It knows its users.

2. It’s reliable, ethical and transparent.

3. It takes context into account.

4. It’s easy to use and asks users how it’s doing.

5. When trust is lost, it adapts to rebuild it.

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Open-source software allows for efficient 3D printing with multiple materials

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Nobel Laureate John Martinis once served as graduate student mentor at ��ƷSM��ӰƬ

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Science & Technology

��ƷSM����ӰƬ delivers impactful research and creative work, despite federal funding uncertainty

Innovating at a quantum scale

Improving understanding of space weather

Helping communities adapt to climate change

Pairing humans and AI to help students learn

Creating a Band-Aid for the heart

Related Articles

Researchers aim to identify pika calls through 'acoustic fingerprinting'

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New 'molecular dam' stops energy leaks in nanocrystals

Related Articles

Migration no guarantee of bird biodiversity

Related Articles

How animals get their spots, and why they are beautifully imperfect

Related Articles

Roam if you want to. Unless you're a wild animal

Related Articles

AWS down: How a single network outage rippled through businesses, institutions and the economy

What happened and who did it impact?

What causes this type of outage to happen?

Could it happen again? How vulnerable are we?

What can we do to prevent this or reduce the risk of it happening again?

Related Articles

5 ways to make AI more trustworthy

How trust forms

1. It knows its users.

2. It’s reliable, ethical and transparent.

3. It takes context into account.

4. It’s easy to use and asks users how it’s doing.

5. When trust is lost, it adapts to rebuild it.

Related Articles

Open-source software allows for efficient 3D printing with multiple materials

Related Articles

Nobel Laureate John Martinis once served as graduate student mentor at ��ƷSM����ӰƬ

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��ƷSM��ӰƬ delivers impactful research and creative work, despite federal funding uncertainty

Nobel Laureate John Martinis once served as graduate student mentor at ��ƷSM��ӰƬ