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Purdue Secures Two DOE Genesis Mission AI Projects to Accelerate Scientific Discovery
Purdue University has been awarded two projects under the U.S. Department of Energy’s (DOE) Genesis Mission, a national effort to speed scientific progress with artificial intelligence (AI). The awards, announced in West Lafayette, Indiana, place Purdue at the forefront of AI‑driven research in physics, astronomy, and computer science.
The Genesis Mission, launched in November 2025, selected 278 projects from more than 5,000 submissions across all 50 states. Purdue is the only university in Indiana to lead a project in the program. The two projects, led by faculty from the College of Science, focus on data science and AI applications for cutting‑edge experiments.
The first project is headed by Professor Wei Xie of the Department of Physics and Astronomy, Assistant Professor Miaoyuan Liu, and Assistant Professor Ruqi Zhang of the Department of Computer Science. Their team will develop autonomous, on‑sensor machine‑learning models for the Electron‑Ion Collider (EIC), the world’s first polarized electron‑ion collider currently under construction at Brookhaven National Laboratory. The models will use agentic AI to identify significant particle interactions in real time and compress data streams, enabling detectors to prioritize the most valuable information and reduce data loss.
"The selection of two Purdue projects for the Genesis Mission awards underscores our academic progress," said Dan DeLaurentis, Purdue’s executive vice president for research. "Successfully using AI to push the rate of scientific discovery can establish a new future in scientific discovery."
The second project is led by Professor David F. Gleich of the Department of Computer Science. Gleich’s research will investigate how large language models (LLMs) can directly cite their training data—a capability that would allow scientists to trace AI predictions back to source information. The work will be conducted in partnership with Oak Ridge National Laboratory, while Xie’s team partners with Los Alamos National Laboratory and the Fermi National Accelerator Laboratory.
Purdue’s involvement in the Genesis Mission extends beyond these two projects. Five other faculty members are part of awards led by institutions elsewhere: Professor David Nolte is working on AI workflows for critical minerals; Professor Laura J. Pyrak‑Nolte is involved in neural operators for geothermal systems and a physics‑informed model for crustal fracture; Professor Xipeng Shen is developing an LLM workflow for code generation on emerging AI accelerators; Professor Joerg Appenzeller is researching polar‑material SRAM and logic; and Professor Stylianos Chatzidakis is applying AI to cyber‑assured digital twins for small modular reactors.
The Genesis Mission is a DOE initiative that aims to create a centralized AI platform to accelerate discovery across energy, national security, and basic science. The program provides access to AI agent frameworks, advanced models, and software tools, and encourages collaboration between academia, industry, and national laboratories.
Purdue’s projects fit within the university’s broader Computing Initiative, which emphasizes physical AI, quantum science, and semiconductor innovation. The university, ranked among the top 10 public universities in the United States, enrolls more than 106,000 students across its campuses.
The two Purdue projects are expected to deliver AI tools that can be deployed in high‑energy physics experiments and other data‑intensive scientific domains. By automating data filtering and providing transparent model citations, the research aims to reduce the time scientists spend on data preprocessing and increase confidence in AI‑derived insights.
While the projects are still in early development stages, the awards signal strong institutional support for AI research in the physical sciences. The Genesis Mission’s selection criteria emphasize the potential for AI to transform scientific workflows, and Purdue’s faculty have demonstrated expertise in both theoretical and applied aspects of machine learning.
The outcomes of these projects will be shared with the broader scientific community through publications, workshops, and collaborations with national laboratories. The work also aligns with DOE’s goal of maintaining U.S. leadership in high‑performance computing and advanced scientific instrumentation.
In summary, Purdue’s dual Genesis Mission awards highlight the university’s capacity to integrate AI into frontier physics research. The projects will advance real‑time data analysis for the upcoming Electron‑Ion Collider and improve the traceability of AI predictions in scientific contexts, reinforcing the role of AI as a catalyst for accelerated discovery.
The Genesis Mission, launched in November 2025, selected 278 projects from more than 5,000 submissions across all 50 states. Purdue is the only university in Indiana to lead a project in the program. The two projects, led by faculty from the College of Science, focus on data science and AI applications for cutting‑edge experiments.
The first project is headed by Professor Wei Xie of the Department of Physics and Astronomy, Assistant Professor Miaoyuan Liu, and Assistant Professor Ruqi Zhang of the Department of Computer Science. Their team will develop autonomous, on‑sensor machine‑learning models for the Electron‑Ion Collider (EIC), the world’s first polarized electron‑ion collider currently under construction at Brookhaven National Laboratory. The models will use agentic AI to identify significant particle interactions in real time and compress data streams, enabling detectors to prioritize the most valuable information and reduce data loss.
"The selection of two Purdue projects for the Genesis Mission awards underscores our academic progress," said Dan DeLaurentis, Purdue’s executive vice president for research. "Successfully using AI to push the rate of scientific discovery can establish a new future in scientific discovery."
The second project is led by Professor David F. Gleich of the Department of Computer Science. Gleich’s research will investigate how large language models (LLMs) can directly cite their training data—a capability that would allow scientists to trace AI predictions back to source information. The work will be conducted in partnership with Oak Ridge National Laboratory, while Xie’s team partners with Los Alamos National Laboratory and the Fermi National Accelerator Laboratory.
Purdue’s involvement in the Genesis Mission extends beyond these two projects. Five other faculty members are part of awards led by institutions elsewhere: Professor David Nolte is working on AI workflows for critical minerals; Professor Laura J. Pyrak‑Nolte is involved in neural operators for geothermal systems and a physics‑informed model for crustal fracture; Professor Xipeng Shen is developing an LLM workflow for code generation on emerging AI accelerators; Professor Joerg Appenzeller is researching polar‑material SRAM and logic; and Professor Stylianos Chatzidakis is applying AI to cyber‑assured digital twins for small modular reactors.
The Genesis Mission is a DOE initiative that aims to create a centralized AI platform to accelerate discovery across energy, national security, and basic science. The program provides access to AI agent frameworks, advanced models, and software tools, and encourages collaboration between academia, industry, and national laboratories.
Purdue’s projects fit within the university’s broader Computing Initiative, which emphasizes physical AI, quantum science, and semiconductor innovation. The university, ranked among the top 10 public universities in the United States, enrolls more than 106,000 students across its campuses.
The two Purdue projects are expected to deliver AI tools that can be deployed in high‑energy physics experiments and other data‑intensive scientific domains. By automating data filtering and providing transparent model citations, the research aims to reduce the time scientists spend on data preprocessing and increase confidence in AI‑derived insights.
While the projects are still in early development stages, the awards signal strong institutional support for AI research in the physical sciences. The Genesis Mission’s selection criteria emphasize the potential for AI to transform scientific workflows, and Purdue’s faculty have demonstrated expertise in both theoretical and applied aspects of machine learning.
The outcomes of these projects will be shared with the broader scientific community through publications, workshops, and collaborations with national laboratories. The work also aligns with DOE’s goal of maintaining U.S. leadership in high‑performance computing and advanced scientific instrumentation.
In summary, Purdue’s dual Genesis Mission awards highlight the university’s capacity to integrate AI into frontier physics research. The projects will advance real‑time data analysis for the upcoming Electron‑Ion Collider and improve the traceability of AI predictions in scientific contexts, reinforcing the role of AI as a catalyst for accelerated discovery.
