Webinar Announcement: Spectral Preprocessing, Chemometrics, and Machine Learning for Nanomaterial-Based Spectroscopy

I am pleased to invite you to an upcoming Nanomaterials Webinar exploring the rapidly evolving intersection of spectroscopy, chemometrics, artificial intelligence, and machine learning.

📅 Date: September 15, 2026

⏰ Time: 9:00 AM EDT | 3:00 PM CEST

🌐 Format: Online

🔗 Information & Registration: https://sciforum.net/event/Nanomaterials-30

Spectral Preprocessing, Chemometrics, and Machine Learning for Nanomaterial-Based Spectroscopy

Advances in Raman spectroscopy and surface-enhanced Raman spectroscopy (SERS) are generating increasingly complex and data-rich measurements. Extracting reliable and reproducible information from these data requires robust approaches for spectral preprocessing, multivariate analysis, machine learning, and AI-enabled interpretation.

This webinar will bring together researchers working across spectroscopy, nanomaterials, statistics, machine learning, and data infrastructure to discuss both methodological advances and practical applications.

Speakers include:

• Prof. Kimberly Hamad-Schifferli, University of Massachusetts Boston

• Dr. Xianyan Chen, University of Georgia

• Dr. Bo Hu, Xidian University

• Prof. Yiping Zhao, University of Georgia

• Mr. Fengbo Ma, University of Georgia

Topics will include spectral preprocessing and baseline correction, chemometrics and high-dimensional data analysis, machine/deep learning for Raman and SERS, spectral interpretation and prediction, and reproducible AI-ready spectral data infrastructure. We will also introduce SpectraGuru, an open platform designed to support reproducible and FAIR-aligned spectral data analysis and AI-enabled spectroscopy.

I hope you will join us and share this announcement with colleagues, students, postdoctoral researchers, and others interested in spectroscopy, nanomaterials, data science, and AI/ML.

Registration and additional information:https://sciforum.net/event/Nanomaterials-30