Workshop Announcement | Spectroscopy Data and AI: Toward Integrated Research Infrastructure
- Yiping Zhao
- 2 days ago
- 2 min read
We are pleased to announce the upcoming workshop “Spectroscopy Data and AI: Toward Integrated Research Infrastructure,” to be held on August 21, 2026, at the University of Georgia. This workshop will bring together researchers from universities and national laboratories, to discuss how spectroscopy, artificial intelligence, machine learning, data standards, and research cyberinfrastructure can be integrated to accelerate scientific discovery. The event will focus on the growing need for shared spectral databases, reproducible data-processing workflows, AI-ready datasets, benchmarking strategies, and instrument–data integration across spectroscopy communities.
Building an Integrated Spectroscopy Data Ecosystem
Spectroscopy plays a central role in materials science, chemistry, physics, biology, environmental science, medicine, and national-security-related research. However, the rapid growth of spectroscopic data across different instruments, laboratories, formats, and analysis pipelines has created major challenges in data standardization, reproducibility, interoperability, and AI-enabled interpretation.
This workshop aims to explore how the spectroscopy community can work together to build an integrated research infrastructure that connects experimental measurements, spectral databases, machine-learning tools, data standards, and user-friendly analysis platforms.
Workshop Focus
The workshop will provide a forum for invited talks, technical discussions, and community input on several key topics, including:
Spectroscopy data standards and metadata requirements
AI and machine-learning methods for spectral analysis
Spectral databases, data sharing, and data curation
Benchmark datasets and model validation strategies
Instrument–data integration and automated workflows
Cross-technique connections among Raman, SERS, IR, XPS, XAS, EELS, and related spectroscopies
Community infrastructure for reproducible and scalable spectroscopy research
By bringing together experts from multiple spectroscopy and data-science communities, the workshop will help identify current gaps, shared needs, and future opportunities for building sustainable spectroscopy data infrastructure.
Connecting Spectroscopy, AI, and Community Standards
A major goal of the workshop is to promote discussion around how AI-ready spectral data can be collected, organized, shared, and analyzed in a reproducible manner. As machine learning becomes increasingly important for spectral classification, quantification, feature extraction, and interpretation, the quality and structure of underlying datasets become critical. The workshop will therefore emphasize not only AI model development, but also the broader ecosystem needed to support trustworthy AI in spectroscopy, including standardized workflows, curated databases, uncertainty assessment, benchmark protocols, and community-agreed reporting practices.
Event Information
Workshop Title: Spectroscopy Data and AI: Toward Integrated Research Infrastructure
Date: August 21, 2026
Location: University of Georgia, Athens, GA
Workshop Website: https://www.zhao-nano-lab.com/workshop
The workshop is open to researchers, students, instrument developers, data scientists, and community members interested in spectroscopy, AI, spectral databases, and research infrastructure.
Looking Ahead
This workshop is intended to serve as a starting point for broader community conversations on how spectroscopy data and AI tools can be connected through shared infrastructure. Through invited presentations, discussions, and community engagement, the event will help define priorities for future collaboration, data-resource development, and integrated spectroscopy research platforms.
More information, including workshop updates and registration details, is available at:
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