Early Career Award recipient Aleksandra Ćiprijanović aims to create universal AI analysis framework
Early Career Award recipient Aleksandra Ćiprijanović aims to create universal AI analysis framework
Publish Date: 2026-04-02 10:00:00
Source Domain: news.fnal.gov
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Recognition: Aleksandra Ćiprijanović, a Wilson Fellow and associate scientist at Fermilab, received a 2025 DOE Early Career Award for her project titled “Bridging the Gap Between Scientific Datasets with Artificial Intelligence.”
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Research Challenge: Ćiprijanović’s work aims to address the domain shift problem in AI model performance, which occurs when a model trained on simulation data does not perform well on real-world data.
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Project Goal: The project seeks to create a universal AI analysis framework that bridges the gap between simulated and experimental data to improve the performance of AI models across high-energy physics.
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Project Scope: The framework, expected to be delivered as a software package, is designed to be general and easy to use for various high-energy physics applications, including cosmological data, collider physics, and neutrino physics.
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Institutional Support: Fermilab’s science and computing capabilities are expected to significantly support Ćiprijanović’s project by providing necessary resources and access to experts from different high-energy physics frontiers.
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Interdisciplinary Collaboration: Successful project outcomes will rely on input and testing from experts across multiple domains within Fermilab to refine and validate the framework.
These points cover key aspects of Aleksandra Ćiprijanović’s award and research project, highlighting her innovation, goals, methodology, the support system at her institution, and planned collaborations.
