Selected work

Representative Papers

Bridging the Gap Between Modern UX Design and Particle Accelerator Control Room Interfaces

Dec 16, 2025

Human-system interfaces (HSIs) in particle accelerator control rooms have long lagged behind contemporary usability and safety-critical UX standards. Method: This study proposes and empirically validates the first human factors–driven UX design framework tailored to high-safety, high-complexity accelerator environments. Grounded in human factors engineering (HF), user-centered design (UCD), cognitive ergonomics analysis, and iterative prototype evaluation, the framework establishes four core principles: clarity, consistency, responsiveness, and cognitive accessibility. It was implemented and tested in realistic operational scenarios on Fermilab’s ACORN platform, involving cross-role stakeholders—operators, domain experts, and engineers. Contribution/Results: The HSI redesign significantly improved operational efficiency and team collaboration quality while reducing operator error rates. Crucially, the framework demonstrates scalability: it maintains intuitive usability and operational effectiveness even as system complexity increases.

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Beyond Like-for-Like: A User-centered Approach to Modernizing Legacy Applications

Nov 26, 2025

Legacy application modernization often stagnates at superficial replacement—updating toolchains and UI aesthetics while neglecting users’ actual needs. To address this, we propose a user-centered, incremental refactoring methodology. Our approach systematically identifies divergent requirements of novice and expert users through contextual interviews, task analysis, and behavioral log mining. It then integrates iterative prototyping with functional mapping from the legacy system to achieve organic alignment between established operational logic and modern GUI paradigms. Crucially, user participation is embedded throughout the entire modernization lifecycle—not merely as post-hoc validation. Evaluation results demonstrate that the resulting prototype significantly improves task completion efficiency (+32%) and user acceptance (Net Promoter Score +41), confirming the method’s effectiveness in preserving core functionality while simultaneously enhancing usability, learnability, and efficiency.

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Accelerating Control Systems with GitOps: A Path to Automation and Reliability

Nov 07, 2025

This study addresses operational inefficiencies, poor auditability, and upgrade challenges in legacy control systems of large-scale scientific facilities—such as CERN, Diamond Light Source, and Fermilab’s ACORN project. We propose a GitOps-based modernization framework that adopts Git as the single source of truth for declarative configurations and tightly integrates containerization, Infrastructure-as-Code (IaC), and cloud-native principles to establish an automated, traceable, and version-controlled control infrastructure. Notably, this work represents the first systematic integration of modern data pipelines and AI/ML capabilities into accelerator science control systems, enabling automated configuration deployment, closed-loop runtime telemetry, and intelligent anomaly detection. Empirical evaluation demonstrates significant improvements in system reliability, maintainability, and regulatory audit compliance. The approach provides a reusable technical paradigm and engineering framework for the digital transformation of big-science facilities.

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Using Containers to Speed Up Development, to Run Integration Tests and to Teach About Distributed Systems

Jul 28, 2025

To address the challenges of difficult development and debugging, complex integration testing environments, and high pedagogical barriers in the GlideinWMS distributed system, this paper proposes the “Workspace Container” methodology—a unified, lightweight, containerized environment for development and education. Built upon a multi-container architecture—including Factory, Frontend, compute nodes, and batch systems—it integrates Docker and VS Code to enable one-click local deployment, offline debugging, and seamless IDE collaboration. The key contribution lies in abstracting development, testing, and teaching workflows into reusable, composable, standardized container units, thereby substantially reducing onboarding overhead for new users. Empirical validation across multiple workshops confirms that the full system runs efficiently on commodity laptops, accelerates development and debugging cycles, and significantly improves instructional interactivity and experimental reproducibility.

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eLog analysis for accelerators: status and future outlook

Jun 15, 2025

To address inefficient electronic log (eLog) information retrieval, weak knowledge management, and delayed fault diagnosis in large-scale accelerator facilities, this paper proposes the first Retrieval-Augmented Generation (RAG)-enhanced eLog analysis framework tailored for high-reliability scientific environments. The framework tightly integrates RAG with domain-adaptive natural language processing, multi-source heterogeneous log structuring and vectorization, and real-time interfacing with accelerator control systems. Crucially, it embeds RAG deeply within the operational control closed loop to enable semantic-level log understanding and real-time operator assistance. Prototyped across four major U.S. national laboratories—including Fermilab and Jefferson Lab—the framework achieves a 42% improvement in key information retrieval accuracy and reduces mean time to fault attribution by 35%, significantly enhancing operational efficiency and knowledge reuse capability.

0 citationsRead paper

Recent publications

Latest Papers

Bridging the Gap Between Modern UX Design and Particle Accelerator Control Room Interfaces

Dec 16, 2025

Human-system interfaces (HSIs) in particle accelerator control rooms have long lagged behind contemporary usability and safety-critical UX standards. Method: This study proposes and empirically validates the first human factors–driven UX design framework tailored to high-safety, high-complexity accelerator environments. Grounded in human factors engineering (HF), user-centered design (UCD), cognitive ergonomics analysis, and iterative prototype evaluation, the framework establishes four core principles: clarity, consistency, responsiveness, and cognitive accessibility. It was implemented and tested in realistic operational scenarios on Fermilab’s ACORN platform, involving cross-role stakeholders—operators, domain experts, and engineers. Contribution/Results: The HSI redesign significantly improved operational efficiency and team collaboration quality while reducing operator error rates. Crucially, the framework demonstrates scalability: it maintains intuitive usability and operational effectiveness even as system complexity increases.

0 citationsRead paper

Beyond Like-for-Like: A User-centered Approach to Modernizing Legacy Applications

Nov 26, 2025

Legacy application modernization often stagnates at superficial replacement—updating toolchains and UI aesthetics while neglecting users’ actual needs. To address this, we propose a user-centered, incremental refactoring methodology. Our approach systematically identifies divergent requirements of novice and expert users through contextual interviews, task analysis, and behavioral log mining. It then integrates iterative prototyping with functional mapping from the legacy system to achieve organic alignment between established operational logic and modern GUI paradigms. Crucially, user participation is embedded throughout the entire modernization lifecycle—not merely as post-hoc validation. Evaluation results demonstrate that the resulting prototype significantly improves task completion efficiency (+32%) and user acceptance (Net Promoter Score +41), confirming the method’s effectiveness in preserving core functionality while simultaneously enhancing usability, learnability, and efficiency.

0 citationsRead paper

Accelerating Control Systems with GitOps: A Path to Automation and Reliability

Nov 07, 2025

This study addresses operational inefficiencies, poor auditability, and upgrade challenges in legacy control systems of large-scale scientific facilities—such as CERN, Diamond Light Source, and Fermilab’s ACORN project. We propose a GitOps-based modernization framework that adopts Git as the single source of truth for declarative configurations and tightly integrates containerization, Infrastructure-as-Code (IaC), and cloud-native principles to establish an automated, traceable, and version-controlled control infrastructure. Notably, this work represents the first systematic integration of modern data pipelines and AI/ML capabilities into accelerator science control systems, enabling automated configuration deployment, closed-loop runtime telemetry, and intelligent anomaly detection. Empirical evaluation demonstrates significant improvements in system reliability, maintainability, and regulatory audit compliance. The approach provides a reusable technical paradigm and engineering framework for the digital transformation of big-science facilities.

0 citationsRead paper

Using Containers to Speed Up Development, to Run Integration Tests and to Teach About Distributed Systems

Jul 28, 2025

To address the challenges of difficult development and debugging, complex integration testing environments, and high pedagogical barriers in the GlideinWMS distributed system, this paper proposes the “Workspace Container” methodology—a unified, lightweight, containerized environment for development and education. Built upon a multi-container architecture—including Factory, Frontend, compute nodes, and batch systems—it integrates Docker and VS Code to enable one-click local deployment, offline debugging, and seamless IDE collaboration. The key contribution lies in abstracting development, testing, and teaching workflows into reusable, composable, standardized container units, thereby substantially reducing onboarding overhead for new users. Empirical validation across multiple workshops confirms that the full system runs efficiently on commodity laptops, accelerates development and debugging cycles, and significantly improves instructional interactivity and experimental reproducibility.

0 citationsRead paper

eLog analysis for accelerators: status and future outlook

Jun 15, 2025

To address inefficient electronic log (eLog) information retrieval, weak knowledge management, and delayed fault diagnosis in large-scale accelerator facilities, this paper proposes the first Retrieval-Augmented Generation (RAG)-enhanced eLog analysis framework tailored for high-reliability scientific environments. The framework tightly integrates RAG with domain-adaptive natural language processing, multi-source heterogeneous log structuring and vectorization, and real-time interfacing with accelerator control systems. Crucially, it embeds RAG deeply within the operational control closed loop to enable semantic-level log understanding and real-time operator assistance. Prototyped across four major U.S. national laboratories—including Fermilab and Jefferson Lab—the framework achieves a 42% improvement in key information retrieval accuracy and reduces mean time to fault attribution by 35%, significantly enhancing operational efficiency and knowledge reuse capability.

0 citationsRead paper