AI

Engineering an AI-ready future

Hanna Nordwall — Thu, 21 May 2026 17:51:26 +0000

Engineering an AI-ready future Hanna Nordwall Thu, 05/21/2026 - 11:51

Caitlin Rockett

CU Engineering strives for an intentional approach to incorporating AI in its research and teaching mission

When it comes to engaging with artificial intelligence in education, CU Engineering is “unique,” said Sriram Sankaranarayanan, associate dean and professor of computer science. His Office of Digital Education places “a lot of focus” on how his colleagues incorporate AI into curricula.

“If the future requires students to be good at using AI and also good engineers,” he said, “then we train students to be strong in both.”

Across the college, PhD students use AI to build interactive diagrams from static textbooks, researchers study its biases and costs, and students are enrolling in a new professional master’s program focused on AI. Faculty have created space to help one another learn about AI, while others encourage students to use it to refine papers and iterate ideas.

Illustration by Hanna Nordwall

The why of AI in the classroom

Diane Sieber, an associate professor in the Herbst Program for Engineering, Ethics and Society, runs the Generative Futures Lab, an informal space where faculty, staff and students can explore AI. She developed a framework to help instructors decide what level of AI use is appropriate for different assignments.

“We even made icons for syllabi, ranging from ‘full AI use encouraged’ to ‘AI use restricted,’ with explanations for each,” Sieber said.

Alvaro Velasquez, assistant professor of computer science, has already seen the benefits of AI in graduate-student writing. “They write the paper, and by iterating with AI, they refine it to a point where it’s actually very, very well written,” he said.

For students with AI anxiety, Sankaranarayanan asks they “treat this as a challenge.”

“Try to gain expertise beyond what AI can replace,” he says. “Think broadly about opportunities and the skills you need to thrive, so you don’t feel victimized by a changing technological landscape.”

Making STEM accessible through AI

“I have a very bullish idea of what AI can do and how it can help us. I understand why people are cautious, but universities are supposed to look at the long arc of history.”

— Daniel Acuña

Many faculty see AI as a tool for broadening access to STEM education. Velasquez believes AI could eventually help close gender and socioeconomic gaps by functioning as a personalized tutor.

To that end, ATLAS Institute Assistant Professor Ryo Suzuki is developing tools such as Augmented Physics, which uses AI alongside augmented and virtual reality to turn static textbook diagrams into interactive simulations.

“Now, imagine if AI could not only respond in text but also generate animated explanations in real time, going beyond text to make learning engaging, visual and playful,” Suzuki said.

Thomas Breideband, associate director of the NSF National AI Institute for Student- AI Teaming, works with an interdisciplinary community of researchers to study how AI can support collaboration in learning environments — particularly in middle and high school, where STEM participation gaps often emerge.

“Collaboration is a critical 21st-century skill, but it is very rarely explicitly practiced,” Breideband said. He and his colleagues are currently working with schools to integrate AI-enhanced curriculum units in classrooms.

AI in the lab

Researchers also interrogate AI. In Associate Professor Daniel Acuña’s lab, his team uses AI techniques to study how large language models absorb “prestige bias” from language used to describe scientific research.

“Instead of saying, ‘scientists found X,’ journalists say, ‘Harvard scientists found X,’” Acuña said. Because LLMs learn from that same data, Acuña hopes his work can help highlight — and eventually correct — those patterns.

Velasquez is tackling another challenge: AI’s immense computational cost. His research on neurosymbolic AI seeks to end “gatekeeping” and "monopolization" in AI.

“When it comes to natural language generation, it comes at a tremendous cost,” Velasquez said. “The neurosymbolic AI community has seen cases where we can use 100,000 to a million times less data.”

New AI degree program

The newly launched Professional Master’s in Artificial Intelligence merges technical skills with ethical considerations.

“If one of our graduates is hired by a company like Walmart, they should be able to analyze consumer data to decide what products to buy and how to manage inventory,” Sankaranarayanan said. “But they should also be able to say, ‘This approach preserves privacy, complies with regulations and is ethically sound.’”

The online degree option through Coursera is up and running, while the on-campus version begins in fall 2026.

Educators agree that they must be intentional in their approach to teaching AI.

“Technology has a very mixed record,” said Sankaranarayanan. “People fear losing jobs, and that is a valid fear, but it doesn’t have to go that way. That’s where education becomes extremely important.”

CU Engineering strives for an intentional approach to incorporating AI in its research and teaching missions

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Downstream data

Hanna Nordwall — Wed, 20 May 2026 14:43:17 +0000

Downstream data Hanna Nordwall Wed, 05/20/2026 - 08:43

Susan Glairon

Researcher using AI to improve and personalize flood prediction

When Zhi Li was young, flash floods regularly swept through his village in China.

Once while he was swimming in a river, the water rose suddenly, submerging 10-year-old Li and pushing him downstream. Though massive amounts of rain had fallen upstream, where Li swam the sky remained a clear, deceptive blue.

“It was so quick,” said Li, an assistant professor of civil engineering who joined ��ñ�� in fall 2025. “I had no clue there would be a flood.

Fortunately, a stranger pulled him to safety. The experience inspired Li to devote his life to flood research. “Floods don’t necessarily happen where the rain falls,” Li said. “In my community, many lives were taken by floods. It was devastating.”

Improved simulations

In the United States, the National Weather Service issues weather forecasts and warnings based on expected rainfall and whether the precipitation is likely to overflow nearby rivers, streams or dams.

At Li’s Flood Lab at ��ñ��, his simulations draw on NWS rainfall predictions and detailed terrain data, including ground permeability, land use, soil type and vegetation cover. By combining U.S. Geological Survey terrain maps with AI, his models predict flooding with far greater precision and speed than the Federal Emergency Management Agency’s traditional physics-based models.

His approach can pinpoint where floodwater will pool at a one-meter resolution, detailed enough to show whether an individual building is likely to flood, compared with FEMA’s 10-meter resolution.

Li said achieving one-meter resolution using FEMA’s traditional approach would require extensive expertise and about a year of computation. Using AI, he can simulate an entire county in just two to three hours at a far lower cost.

“Drilling it down to single households is only possible once you have an AI product like this,” Li said. “It was unimaginable in the past.”

To improve model accuracy, Li checks his results with local experts who know which areas are most vulnerable to flooding. This human insight serves as a guardrail for AI, which can sometimes “hallucinate” false warnings.

Personalized warnings

Li’s research also involves changing how flood risk is communicated. Instead of the traditional top-down approach, issuing a single warning message for an entire county, he envisions a customized alert that starts with individual households and scales up to neighborhoods, communities and counties.

“Floods don’t necessarily happen where the rain falls.”

“There is evidence that during floods, some of the people with language barriers were unable to evacuate in time and lost their lives,” Li said. “Personalized warnings can help ensure critical information is clearly communicated so people can act quickly.”

His goal is to use data from the American Community Survey, an annual U.S. Census Bureau report on household demographics, to generate personalized warnings in each resident’s preferred language about whether their home will likely be affected. Evacuation guidance would also reflect a person’s mobility needs and access to transportation.

Flood prediction for all

Li is also developing an AI-powered assistant to democratize access to flood modeling. The approach aims to remove technical barriers that limit flood modeling to experts. Anyone would be able to see an area’s overall flood risk based on historical events. Users could interact with the model in a ChatGPT-style chat to explore flood risk maps by region.

The platform will eventually include real-time alerts and interactive simulations to empower communities to better understand their flood risks during an event without waiting for official warnings.

“I hope the model can be used anywhere in the world to reduce flood damage and provide accessible information to people at risk,” Li said. “That goal has always guided my research.”

Measuring the cost

Li also has a vision for measuring a flood’s total impact to human health, ecology, agriculture and the urban economy as a way to mitigate flood costs.

Comparing it to the total gross domestic product (GDP) that is used to evaluate countries’ prosperity, he envisions creating a “gross flood damage” value to help policymakers determine the amount of government aid for a community and how to reduce flood impact in future years.

Invisible costs, such as a loss of income due to flooded agricultural and other work spaces, would also be included.

Researcher using AI to improve and personalize flood prediction

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News & Noteworthy

Hanna Nordwall — Fri, 15 May 2026 20:44:46 +0000

News & Noteworthy Hanna Nordwall Fri, 05/15/2026 - 14:44

CU Engineering hosts NAE Quantum & Space Symposium

��ñ��’s College of Engineering and Applied Science hosted the National Academy of Engineering’s Regional Meeting & Symposium, which focused on the convergence of quantum technologies and space applications. Participants discussed technical pathways for space deployment, implications for satellite architectures and national security applications and shared insights on accelerating the transition from laboratory prototypes to mission-ready systems. The program leveraged Colorado’s interconnected ecosystem of academic quantum and aerospace research, national laboratories, and commercial quantum, space and technology partners to facilitate technical exchange across academia, government and industry on this emerging frontier.

Clockwise from top: NAE Symposium hosts and special guests, from left, Hanspeter Schaub, Scott Diddams, Dana Anderson, Tsu-Jae Liu and Keith Molenaar; ��ñ�� Chancellor Justin Schwartz greets an attendee; aerospace PhD student Zack Funke explains his research during the poster session.

Scott Diddams

Diddams, Schaub elected to NAE

Hanspeter Schaub

Two CU Engineering faculty members were elected to the 2025 class of the National Academy of Engineering.

Scott Diddams is a professor and Robert H. Davis Endowed Chair in Discovery Learning in the Department of Electrical, Computer and Energy Engineering. He is also affiliated with the Department of Physics and the National Institute of Standards and Technology. He was recognized for his outstanding contributions in optical frequency combs and their applications.

Hanspeter Schaub is a distinguished professor and chair of the Ann and H.J. Smead Department of Aerospace Engineering Sciences. A leader in the field of astrodynamics and spacecraft control, his research has advanced theoretical and practical understanding of spacecraft operations.

Diddams and Schaub were among 128 new U.S. members and 21 international members in the class of 2025.

Degrees launched in AI, sustainable engineering

CU Engineering has launched two master’s programs designed to meet industry demand in key areas of national importance.

A Master of Science in artificial intelligence is now available both online and in-person (starting fall 2027), making ��ñ�� one of only a handful of universities offering a master’s degree in AI. The core curriculum addresses a breadth of areas central to AI engineering expertise, including machine learning, statistical learning, natural language processing and ethics.

The Master of Science in sustainable engineering represents a new model of cross-college collaboration at ��ñ��, uniting expertise from business, engineering and the natural sciences to prepare students for the global demand for sustainability jobs. The nine-month program features an integrated 15-credit core with students from ��ñ��’s MS in Sustainable Business, as well as engineering-focused electives and a capstone project with real-world partners in industry or government.

Astronaut Candidate and U.S. Navy Lt. Cmdr. Erin Overcash. Photo credit: NASA

Alum tapped as NASA astronaut candidate

In September, Erin Overcash (AeroEngr'14, MS'17) reported for duty as part of NASA's 2025 astronaut candidate class. In addition to her ��ñ�� degrees, she attended U.S. Navy flight school and has logged more than 1,300 hours of flight in a variety of aircraft, according to her astronaut profile.

During her time at ��ñ��, Overcash competed in track and field in the pentathlon, hurdles and high jump, among other events. She went on to train with the USA Rugby Women's National Team and has also competed in Ironman Triathlon events.

Marcus Holzinger
Hatfield Endowed Professor

Professorship established in space policy & law

��ñ�� donors Dale and Patricia Hatfield have given $2.5 million to establish the Hatfield Endowed Professorship in Space Policy & Law.

Underscoring the university’s commitment to leadership in this fast-evolving field, the professorship will drive teaching and research on space policy and law, with broad implications for national security, global communications, navigation, weather forecasting and international collaboration.

This interdisciplinary position will rotate every two years between the College of Engineering and Applied Science, the Leeds School of Business and Silicon Flatirons, supporting faculty whose teaching and research advance this work. Professor Marcus J. Holzinger of the Ann and H.J. Smead Department of Aerospace Engineering Sciences is the inaugural Hatfield Endowed Professor, bringing expertise in space policy, domain awareness, development and strategy.

New book addresses engineering student wellness

As Counseling and Psychiatric Services therapists embedded in the College of Engineering and Applied Science, Audrey Gilfillan and Alison West have more than eight years of combined experience supporting engineering students.

They recently harnessed that experience to co-author Decompile Your Mind: An Engineer’s Guide to Thoughts and Emotions, which tackles common challenges faced by engineering students, including perfectionism, imposter syndrome, self-criticism, loneliness, emotional suppression, rumination and uncertainty.

“Engineers have inspired us to rethink how we approach mental health — but the content itself offers value to many people, not just engineers,” West said. “Anyone who sees the world through an analytical, logical lens can gain value from this book.”

Jay Arehart
Assistant Teaching Professor

Symposium tackles embodied carbon reduction practices and materials

��ñ��’s Department of Civil, Environmental and Architectural Engineering and the Structural Engineering Institute co-hosted a summer symposium focused on advancing the structural engineering profession toward zero carbon.

The event, which drew 166 participants from 65 companies, marked an industry-wide step toward cutting emissions tied to building materials like steel and concrete, said faculty member and event organizer Jay Arehart.

The event explored design practices and materials that reduce embodied carbon — the greenhouse gases emitted during the production, transport and disposal of building materials. Arehart said he believed it was the largest gathering to date of structural engineers focused on embodied carbon reductions.

CU President Todd Saliman, left, with Amy Moreno-Sherwood

Inclusivity champion wins CU System award

Amy Moreno-Sherwood, senior director of the Campos Student Center (formerly the BOLD Center), was the recipient of the 2025 President’s Inclusive Excellence Award. The award is one of the university’s highest honors for individuals who go above and beyond to build inclusive and empowering communities.

Dean Keith Molenaar said Moreno-Sherwood’s unwavering commitment has profoundly impacted the college community. “Amy’s leadership of the Campos Student Center has elevated efforts to support engineering students of all backgrounds,” Molenaar said.

“Amy’s dedication and innovative approach are truly inspiring. Her recognition with the President’s Inclusive Excellence Award is a testament to her exceptional contributions.”

Learn what events and innovations have been taking place in the College of Engineering and Applied Science.

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Scientists harness AI to reveal forces behind glacier surges

Charles Ferrer — Thu, 05 Mar 2026 15:27:27 +0000

Scientists harness AI to reveal forces behind glacier surges Charles Ferrer Thu, 03/05/2026 - 08:27

Glaciers are constantly changing and reshaping the Earth’s surface. ��ñ�� researchers have developed a new machine learning tool to better understand how Arctic glaciers suddenly accelerate or “surge”.

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5 ways to make AI more trustworthy

Susan Glairon — Wed, 22 Oct 2025 20:44:13 +0000

5 ways to make AI more trustworthy Susan Glairon Wed, 10/22/2025 - 14:44

In a new paper in the journal, "AI and Ethics," Professor Amir Behzadan and his PhD student, Armita Dabiri, are unearthing new insights into how the artificial intelligence (AI) technology we might encounter in daily life, such as self-driving cars, can earn our confidence.

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Robot regret: New research helps robots make safer decisions around humans

Jeff Zehnder — Fri, 29 Aug 2025 16:28:28 +0000

Robot regret: New research helps robots make safer decisions around humans Jeff Zehnder Fri, 08/29/2025 - 10:28

Imagine for a moment that you’re in an auto factory. A robot and a human are working next to each other on the production line. The robot is busy rapidly assembling car doors while the human runs quality control, inspecting the doors for damage and making sure they come together as they should.

Robots and humans can make formidable teams in manufacturing, health care and numerous other industries. While the robot might be quicker and more effective at monotonous, repetitive tasks like assembling large auto parts, the person can excel at certain tasks that are more complex or require more dexterity.

But there can be a dark side to these robot-human interactions. People are prone to making mistakes and acting unpredictably, which can create unexpected situations that robots aren’t prepared to handle. The results can be tragic.

New and emerging research could change the way robots handle the uncertainty that comes hand-in-hand with human interactions. Morteza Lahijanian, an associate professor in ��ñ��’s Ann and H.J. Smead Department of Aerospace Engineering Sciences, develops processes that let robots make safer decisions around humans while still trying to complete their tasks efficiently.

From left, engineering professor Morteza Lahijanian and graduate student Karan Muvvala watch as a robotic arm completes a task using wooden blocks. (Credit: Casey Cass)

In a new study presented at the International Joint Conference on Artificial Intelligence in August 2025, Lahijanian and graduate students Karan Muvvala and Qi Heng Ho devised new algorithms that help robots create the best possible outcomes from their actions in situations that carry some uncertainty and risk.

“How do we go from very structured environments where there is no human, where the robots are doing everything by themselves, to unstructured environments where there are a lot of uncertainties and other agents?” Lahijanian asked.

“If you’re a robot, you have to be able to interact with others. You have to put yourself out there and take a risk and see what happens. But how do you make that decision, and how much risk do you want to tolerate?”

Similar to humans, robots have mental models that they use to make decisions. When working with a human, a robot will try to predict the person’s actions and respond accordingly. The robot is optimized for completing a task—assembling an auto part, for example—but ideally, it will also take other factors into consideration.

In the new study, the research team drew upon game theory, a mathematical concept that originated in economics, to develop the new algorithms for robots. Game theory analyzes how companies, governments and individuals make decisions in a system where other “players” are also making choices that affect the ultimate outcome.

In robotics, game theory conceptualizes a robot as being one of numerous players in a game that it’s trying to win. For a robot, “winning” is completing a task successfully—but winning is never guaranteed when there’s a human in the mix, and keeping the human safe is also a top priority.

So instead of trying to guarantee a robot will always win, the researchers proposed the concept of a robot finding an “admissible strategy.” Using such a strategy, a robot will accomplish as much of its task as possible while also minimizing any harm, including to a human.

“In choosing a strategy, you don't want the robot to seem very adversarial,” said Lahijanian. “In order to give that softness to the robot, we look at the notion of regret. Is the robot going to regret its action in the future? And in optimizing for the best action at the moment, you try to take an action that you won't regret.”

Let’s go back to the auto factory where the robot and human are working side-by-side. If the person makes mistakes or is not cooperative, using the researchers’ algorithms, a robot could take matters into its own hands. If the person is making mistakes, the robot will try to fix these without endangering the person. But if that doesn’t work, the robot could, for example, pick up what it’s working on and take it to a safer area to finish its task.

Karan Muvvala watches the robotic arm pick up a blue block. (Credit: Casey Cass)

Much like a chess champion who thinks several turns ahead about an opponent’s possible moves, a robot will try to anticipate what a person will do and stay several steps ahead of them, Lahijanian said.

But the goal is not to attempt the impossible and perfectly predict a person’s actions. Instead, the goal is to create robots that put people’s safety first.

“If you want to have collaboration between a human and a robot, the robot has to adjust itself to the human. We don't want humans to adjust themselves to the robot,” he said. “You can have a human who is a novice and doesn't know what they're doing, or you can have a human who is an expert. But as a robot, you don't know which kind of human you're going to get. So you need to have a strategy for all possible cases.”

And when robots can work safely alongside humans, they can enhance people's lives and provide real and tangible benefits to society.

As more industries embrace robots and artificial intelligence, there are many lingering questions about what AI will ultimately be capable of doing, whether it will be able to take over the jobs that people have historically done, and what that could mean for humanity. But there are upsides to robots being able to take on certain types of jobs. They could work in fields with labor shortages, such as health care for older populations, and physically challenging jobs that may take a toll on workers’ health.

Lahijanian also believes that, when they're used correctly, robots and AI can enhance human talents and expand what we're capable of doing.

"Human-robot collaboration is about combining complementary strengths: humans contribute intelligence, judgment, and flexibility, while robots offer precision, strength, and reliability," he said.

"Together, they can achieve more than either could alone, safely and efficiently."

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��ñ�� advancing artificial intelligence research for real-world applications

Caroline Harrah — Mon, 25 Aug 2025 15:58:15 +0000

��ñ�� advancing artificial intelligence research for real-world applications Caroline Harrah Mon, 08/25/2025 - 09:58

Caroline Harrah

A modified Boston Dynamics Spot robot operates in a mine as part of an experiment leading up to the DARPA Subterranean Challenge.

��ñ�� researchers maneuver a robot through fallen rock and debris in an experimental mine tunnel in Colorado. Somewhere in the darkness ahead, potential survivors could be running out of air. The robot stops, assesses the unstable ceiling above, then continues toward areas too dangerous for human rescuers.

Other teams in the College of Engineering and Applied Sciences are developing systems that analyze satellite imagery to identify environmental changes invisible to the human eye, while computers mine years of medical records in seconds to help doctors save lives.

Meanwhile, researchers are developing computer systems that describe unfamiliar spaces in detail, guiding someone through a building by noting, for example, "stairs ahead, handrail on your right, doorway opens to a lobby beyond."

These scenarios illustrate a few of the artificial intelligence (AI) discoveries happening at ��ñ��, where researchers collaborate across disciplines to develop trustworthy systems that work alongside humans to address challenges in emergency response, space and planetary exploration, medical diagnosis, education, environmental prediction, accessibility applications and more.

When robots venture where humans cannot

Sean Humbert, professor of mechanical engineering and director of ��ñ��'s Robotics Program, oversees a lab where autonomous systems and bio-inspired robots learn to operate in places and situations where direct human engagement creates unacceptable risk. The algorithms developed by Humbert’s team must process sensor data within milliseconds, adapting to terrain that shifts without warning in contaminated areas, deep ocean trenches and collapsed structures where every decision could mean the difference between rescue and catastrophe.

Humbert, along with Christoffer Heckman and Eric Frew, faculty in computer science and aerospace engineering sciences, respectively, recently led a team of CU researchers in the DARPA Subterranean Challenge to test these systems in unmapped caves, where GPS and communication links were unavailable. Equipment failures and navigation problems in real conditions taught the team lessons impossible to learn in the lab. This iterative process of real-world testing proves essential for developing truly reliable autonomous rescue systems.

��ñ��'s first humanoid robot is being prepared to perform electric vehicle (EV) lithium-ion battery pack disassembly.

Heckman has also partnered with the Army Research Laboratory to investigate the use of vision-language models, such as those employed in ChatGPT, for building robotic contextual awareness. Building on these AI agents, Heckman’s group is developing models that help interpret statements like “go check out the backpack in the rear of the building,” which provide spatial context to robotic assistants.

Morteza Lahijanian, associate professor of aerospace engineering sciences, approaches the same domain with a fundamentally different methodology. Where some systems learn from experience, Lahijanian applies formal verification techniques to help ensure safe behavior before deployment. His team is pioneering a new AI paradigm that complements learning with logic-based reasoning, enabling autonomous systems to make decisions grounded in both intuition and logic.

In space applications, where missions are costly and communication delays are unacceptable, Lahijanian develops autonomous systems for spacecraft that must dock with satellites and space stations without human intervention. His mathematical verification methods ensure these systems can handle situations no programmer could anticipate.

Teaching robots to work with people

Human-robot collaboration requires systems that can learn from and communicate with their human teammates. Brad Hayes, associate professor of computer science, combines advances in machine learning techniques, including Explainable AI, Reinforcement Learning, and Imitation Learning, with foundational principles from robotics and psychology to develop intelligent, reliable, and adaptable autonomous collaborators. By working at the intersection of pervasive and personalized artificial intelligence, large language models, collaborative agents, and decision support, his work produces the technologies that empower human-robot teams to be greater than the sum of their parts.

Alessandro Roncone, assistant professor of computer science and associate director of the Robotics Program, designs robots that act as teammates by understanding human goals and adapting accordingly. His work addresses tricky questions: When should the robot override the human? How can it warn people about limitations without being annoying? Roncone’s research suggests that some chemists hate when robots second-guess their decisions. Others become too dependent on robotic assistance. Achieving balance requires understanding individual personalities.

The challenge of making machines understand

James H. Martin, professor of computer science and faculty fellow at the Institute of Cognitive Science, works on natural language processing systems that can capture meaning in language and exploit that knowledge in practical applications. Language is often vague and ambiguous, requiring context and background knowledge to achieve adequate interpretations. Despite advances with large language models, current approaches struggle with ambiguous language. Supported by awards from the National Institutes of Health, Martin and his colleagues have been developing systems to mine electronic medical records for temporal and causal patterns to improve clinical outcomes. As part of his work with the National Science Foundation AI Institute for Student-AI Teaming (iSAT), located here at ��ñ��, Martin and his students are contributing to systems to analyze and improve instructional discourse in K-12 STEM classrooms.

Professor Alessandro Roncone and a PhD student are working on a collaborative robot that, in the future, will assist people across complex environments, from factories to hospitals.

Maria Pacheco, assistant professor of computer science, faces her own linguistic puzzle. While LLMs are adept at interpreting and producing language, how to use them effectively for knowledge-intensive purposes remains an open question. Whenever LLMs need access to knowledge they were not trained on, or to provide transparent, faithful explanations for their decisions, they fall short. Pacheco studies how to integrate the language capabilities of LLMs with external, structured knowledge resources to develop robust language technology employed in real-world applications.

Beyond recognition: AI that truly sees

Danna Gurari, assistant professor of computer science, applies neural network models to generate spatial descriptions rather than standard object classification. Developed with input from individuals who have vision impairments, her systems provide detailed image descriptions that enable AI-generated spatial navigation. People require different types of information in various contexts. Her work addresses the challenge of providing relevant details without overwhelming users with unnecessary information.

Standardizing how we teach and visualize AI architectures

Associate professor Tom Yeh’s AI research, represented by the AI by Hand project, bridges human-computer interaction and computer vision to make deep learning more intuitive and accessible. With over 200,000 followers across social media platforms, the project has achieved global impact by demystifying complex AI concepts through hand-drawn visual explanations. Yeh invented a novel unified representation framework for neural network architectures, designed to help learners and practitioners better understand, compare and build models. By combining rigorous technical insight with human-centered design, Yeh’s research empowers diverse audiences to engage more meaningfully with the foundations of modern AI.

Embedding Earth's data to improve environmental monitoring

Satellite data offer an unprecedented window into Earth and its changing conditions, but turning this firehose of data into usable information requires new technologies. Esther Rolf, assistant professor of computer science, develops machine learning systems that coalesce satellite data into succinct, general-purpose representations of the Earth. These embeddings unlock new large-scale applications in environmental monitoring; her recent research identified previously unmonitored artisanal mining activity across Sub-Saharan Africa. Rolf pushes the frontier of geospatial AI, aligning fundamental research advances with goals of computational efficiency and accessibility.

Looking forward

As AI systems integrate into scientific, industrial and public domains, ��ñ�� researchers are addressing both technical challenges, such as ensuring reliability and explainability, and social dimensions, including fairness and privacy protection. Rather than replacing human judgment, research aims to create AI that enhances human capabilities and decision-making.

Whether developing robots for dangerous rescue missions, creating educational tools that help people understand AI, or building systems that track environmental changes across the globe, ��ñ�� researchers are advancing technology that amplifies human capability and safeguards human agency.

From robots navigating disaster zones to AI that supports doctors, astronauts, and students, ��ñ�� researchers are creating real-world systems that redefine how artificial intelligence serves humanity. Their work spans life-saving rescue missions, space exploration, environmental monitoring, and human-AI collaboration and more. Discover how ��ñ�� is leading the next wave of AI innovation.

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Civil, environmental and architectural engineering welcomes two new faculty

Susan Glairon — Sat, 16 Aug 2025 10:57:58 +0000

Civil, environmental and architectural engineering welcomes two new faculty Susan Glairon Sat, 08/16/2025 - 04:57

Susan Glairon

Meet Assistant Professors Laura Sunberg and Zhi Li — and see why we’re so excited to have these talented scholars on our team.

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Research institute building the AI-literate workforce of the future receives major new grant

Emily Adams — Thu, 31 Jul 2025 19:28:04 +0000

Research institute building the AI-literate workforce of the future receives major new grant Emily Adams Thu, 07/31/2025 - 13:28

Pioneering research institute led by the ��ñ�� launched in 2020 to explore how classrooms could become more effective and engaging learning environments.

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Researchers test the trustworthiness of AI—by playing sudoku

Emily Adams — Mon, 28 Jul 2025 17:15:26 +0000

Researchers test the trustworthiness of AI—by playing sudoku Emily Adams Mon, 07/28/2025 - 11:15

In a new study, a team of computer scientists and engineers from the ��ñ�� created nearly 2,300 original sudoku puzzles, which require players to enter numbers into a grid following certain rules, then asked several AI tools to fill them in.

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AI

Engineering an AI-ready future

The why of AI in the classroom

Making STEM accessible through AI

AI in the lab

New AI degree program

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Downstream data

Improved simulations

Personalized warnings

Flood prediction for all

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News & Noteworthy

CU Engineering hosts NAE Quantum & Space Symposium

Diddams, Schaub elected to NAE

Degrees launched in AI, sustainable engineering

Alum tapped as NASA astronaut candidate

Professorship established in space policy & law

New book addresses engineering student wellness

Symposium tackles embodied carbon reduction practices and materials

Inclusivity champion wins CU System award

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Scientists harness AI to reveal forces behind glacier surges

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5 ways to make AI more trustworthy

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Robot regret: New research helps robots make safer decisions around humans

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��ñ���� advancing artificial intelligence research for real-world applications

When robots venture where humans cannot

Teaching robots to work with people

The challenge of making machines understand

Beyond recognition: AI that truly sees

Standardizing how we teach and visualize AI architectures

Embedding Earth's data to improve environmental monitoring

Looking forward

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Civil, environmental and architectural engineering welcomes two new faculty

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Research institute building the AI-literate workforce of the future receives major new grant

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Researchers test the trustworthiness of AI—by playing sudoku

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��ñ�� advancing artificial intelligence research for real-world applications