From lab to real life: ASU research drives impact across computing and engineering

The pacemaker. The internet. GPS. Even Gatorade.

Some of the most impactful technologies in modern life didn’t start as commercial products. They emerged not from corporate brainstorming sessions or venture-backed moonshots, but from university research labs — places built to explore hard questions without demanding immediate payoff.

Long before a technology is profitable, scalable or even fully understood, universities are often the ones willing to dream it into existence.

Today, artificial intelligence, or AI, is reshaping work and decision-making. Cyber threats are everywhere, from hospitals to cities to elections. And as Americans live longer, many want to age at home, creating a need for technologies that support care, safety and independence. These are problems without quick fixes. They demand sustained, public-interest technology research — the kind universities are well equipped to deliver.

That's where the School of Computing and Augmented Intelligence, part of the Ira A. Fulton Schools of Engineering at Arizona State University, comes in.

Within ASU’s $1 billion research enterprise, the School of Computing and Augmented Intelligence stands out as a hub for technology research that is both ambitious and deeply applied.

The school’s work spans AI, robotics, cybersecurity, advanced manufacturing and data-driven discovery. These are fields in which progress depends on sustained investment, specialized infrastructure and teams willing to tackle problems that do not come with ready solutions. This is research designed not just to push theory forward but to change how real systems are designed and deployed.

That momentum is reflected in new national benchmarks.

Each year, the Higher Education Research and Development (HERD) Survey, from the U.S. National Science Foundation, or NSF, provides the most comprehensive accounting of research activity across U.S. universities. The survey tracks research expenditures, an indicator of how much work is happening in labs, classrooms and collaborative spaces.

In the most recent HERD rankings, the school placed:

• No. 6 in industrial and manufacturing engineering, ahead of Penn State, Purdue, Stanford and the University of Arizona.
• No. 11 in computer and information sciences, ahead of the University of Washington, Princeton and UCLA.

In fiscal year 2025, the School of Computing and Augmented Intelligence reported nearly $39 million in total research expenditures, including significant funding from the NSF. That investment supports faculty-led research, trains graduate students and enables projects that are too complex, too long-term or too publicly focused for industry to pursue alone.

Those rankings signal momentum, but they also invite a fair question: What does that investment actually do for people?

Ross Maciejewski, director of the school, offers a straightforward answer.

“Research dollars matter, but impact matters more,” Maciejewski says. “The public doesn’t just want to know how much research we do. They want to know how it benefits them. Our goal is technology research that improves lives, strengthens communities and solves real problems.”

Across the School of Computing and Augmented Intelligence, that philosophy is driving projects aimed at moving technology out of the lab and into real-world use. The following sections highlight several of those efforts

One promise of technology research is greater efficiency — machines that save time by taking on the dirty, dull and dangerous tasks people would rather avoid.

Siddharth Srivastava, a Fulton Schools associate professor of computer science and engineering, is working to make that promise achievable.

Backed by NSF funding, Srivastava’s research focuses on AI systems that enable robots to learn complex tasks on their own. That flexibility could unlock safer hospital cleaning, faster disaster response and more affordable household robots for Americans who want to remain at home as they age. By reducing the need for expert hand coding, the research lowers cost and expands access, turning robotics from a niche tool into a broadly useful technology.

Satellites collect staggering amounts of data, but turning that information into useful insight remains a challenge.

With support from the National Science Foundation, Hannah Kerner is developing AI-powered tools to help people make sense of satellite data.

A Fulton Schools assistant professor of computer science and engineering, Kerner focuses on enabling users to track changes in land use and agriculture across the globe, including in regions where reliable data has long been scarce.

The payoff is immediate and global — mapping croplands to strengthen food security, monitoring environmental change, and delivering satellite insights directly to farmers and communities. By lowering technical barriers, Kerner’s work ensures that powerful technology doesn’t remain locked behind university walls. It gets used.

Cyberattacks rarely announce themselves.

They slip through tiny flaws buried deep in software, moving faster than human defenders can keep up. And the consequences are costly.

In the U.S. alone, thousands of cybercrime complaints are filed every day, with reported financial losses reaching into the billions annually.

Tiffany Bao is using technology research to help close that gap.

Bao is a Fulton Schools associate professor of computer science and engineering. With support from the NSF, she is developing SE-bot, an AI-powered system designed to mimic the intuition of elite cybersecurity experts.

SE-bot learns how analysts prioritize threats and strategically explores software paths, uncovering vulnerabilities before attackers can exploit them. The work reflects a preventive approach to technology research, focused on identifying weaknesses early and stopping harm before it spreads.

Technology research reshapes industry when ideas move from theory into real-world production. In advanced manufacturing, that process can be especially complex.

Ashif Iquebal, a Fulton Schools assistant professor of industrial engineering, and his team are using AI to tackle one of advanced manufacturing’s toughest challenges: reliably controlling how metal forms during 3D printing.

Supported by the NSF, the team is developing physics-informed AI models to guide the additive manufacturing of stainless steel. As a real-world demonstration of scale, the researchers are 3D printing a complex naval propeller — a part whose size, geometry and performance demands push current manufacturing methods to their limits.

The project shows how interdisciplinary technology research can strengthen industrial systems in aerospace, defense and energy, where precision is imperative.

University Professor of Technology and Innovation Sethuraman Panchanathan, the former director of the National Science Foundation and founding chair of the School of Computing and Augmented Intelligence, has spent decades watching new technologies move from uncertainty to widespread use. He says the earliest stages of research are often misunderstood and undervalued.

“Technology research rarely looks revolutionary at the moment it begins,” Panchanathan says. “It often looks uncertain, and its potential for impact and return on investment may not be obvious. That is exactly why curiosity-driven, discovery-based, exploratory research should be led by universities.”

Funding milestones reflect more than growth. They signal sustained support for research intended to serve the public interest — from robots designed to reduce risk and AI tools that strengthen food systems to technologies that defend digital infrastructure and manufacturing methods that improve industrial performance.

Technology research shapes what comes next long before outcomes are certain. And across the School of Computing and Augmented Intelligence, that work is already underway.