New Purdue initiative to accelerate discoveries driven by artificial intelligence

WEST LAFAYETTE, Ind. — A new initiative brings together disciplines across Purdue University to make valuable datasets more easily discoverable and accessible, enabling faster scientific breakthroughs using artificial intelligence and machine learning techniques.

The initiative, called Datasets and Infrastructure for Physical AI Innovation, was announced Nov. 13 at the summit AI Frontiers: Uniting Education, Business and Government for Real-World Innovation, hosted by Purdue and Google.

The initiative is a collaboration between Purdue’s Institute for Physical Artificial Intelligence, nanoHUB, the Rosen Center for Advanced Computing, Purdue Libraries and experts in various domains. Together, these teams are developing and deploying data infrastructure to enable Purdue researchers, collaborators and partners to take physical AI to the next level.

This effort aims to support the entire data life cycle — capturing data at the source, curating it for AI and machine learning, connecting it to high-performance computing resources for model training and inference, enabling real-world decision-making for Purdue and partners, and supporting feedback for new experiments and data collection efforts.

These datasets will range from geosciences and agriculture to life sciences and climate. See a selection of datasets developed as part of this initiative.

Raw data originating from lab equipment, field measurements, high-performance computing simulations, road and traffic imagery, and curated documents are indexed into AI-ready resources available directly on Purdue’s world-class cyberinfrastructure to develop AI models and assess their trustworthiness. Real-time data is used to turn these AI models into smart digital twins for autonomous physical AI applications in transportation, supply chains and manufacturing.

With the increasing availability of autonomous and embodied infrastructure, AI researchers foresee these models teaching themselves and accelerating discoveries. The initiative is rounded out by frameworks and processes for handling and managing access to licensed and controlled datasets on Purdue’s AI supercomputing facilities.

“Our researchers are producing extraordinary data with the potential to transform science and society,” said Dan DeLaurentis, executive vice president for research. “This initiative ensures that those datasets are ready to drive artificial intelligence and machine learning, enabling discoveries that are faster, smarter and more reproducible.”

One example of the initiative’s impact is an intelligent digital twin for semiconductor manufacturing, developed in collaboration with Purdue’s Birck Nanotechnology Center. Experimental data from processing tools at Birck is automatically captured and streamed to digital resources hosted on Purdue’s cyberinfrastructure. AI models are continually refined as new data arrives, improving their predictions and guiding optimal processing “recipes” for semiconductor devices. In effect, the digital twin teaches itself — enhancing yield, reducing waste and accelerating innovation in advanced manufacturing.

A second example focuses on digital agriculture. Using a smartphone application, farmers can collect data from their fields using remote imaging platforms such as drones, which are streamed to Purdue servers. There, the data is used to refine AI models to provide real-time, personalized feedback that helps farmers maximize yield and resource utilization. The system closes the loop between data collection, analysis and actionable insights, creating continuously improving digital twins that integrate data and models from individual plants all the way up to entire farms.

By making Purdue’s research data AI-ready, connected and reusable, the initiative supports the university’s commitment to excellence at scale. It ensures that Purdue’s vast research enterprise not only produces new knowledge but also feeds a growing ecosystem of digital twins, intelligent systems and open-data resources that amplify impact across domains — from materials and manufacturing to agriculture and health.

“This effort is about unlocking the full potential of Purdue data,” said Alejandro Strachan, a Reilly Professor of Materials Engineering and research fellow on intelligent twins and digital innovation. “By linking data, high-performance computing and artificial intelligence, we’re creating a foundation where every new experiment makes our AI models smarter and our research more impactful at Purdue and beyond.”

The effort also aligns with Purdue Computes, an initiative that encompasses the university’s research and programs in physical AI, computing, semiconductors and quantum science.

About Purdue University

Purdue University is a public research university leading with excellence at scale. Ranked among top 10 public universities in the United States, Purdue discovers, disseminates and deploys knowledge with a quality and at a scale second to none. More than 107,000 students study at Purdue across multiple campuses, locations and modalities, including more than 58,000 at our main campus locations in West Lafayette and Indianapolis. Committed to affordability and accessibility, Purdue’s main campus has frozen tuition 14 years in a row. See how Purdue never stops in the persistent pursuit of the next giant leap — including its integrated, comprehensive Indianapolis urban expansion; the Mitch Daniels School of Business; Purdue Computes; and the One Health initiative — at https://www.purdue.edu/president/strategic-initiatives.