Thomas Bocklitz

Thomas Bocklitz is a Professor at the Leibniz Institute of Photonic Technology, leading the Photonic Data Science working group. His research focuses on integrating machine learning with spectroscopic and medical imaging techniques to enhance diagnostic accuracy and analytical workflows.

• University: Leibniz Institute of Photonic Technology
• School: Research Department Photonic Data Science
• Academic Rank: Professor
• Email: thomas.bocklitz@leibniz-ipht.de

Research Interests: Bocklitz specializes in applying machine learning to spectroscopy (Raman, SERS, LIBS) and biomedical imaging. His work addresses challenges like spectral artifacts correction, image quality assessment, and class imbalance in histopathology data. He also explores explainable AI for spectroscopy and medical image registration across modalities.

Publication Trends: His recent publications (2025) emphasize spatially aware deep learning for hyperspectral data, improved feature extraction methods in medical imaging, and custom CNN architectures for LIBS analysis. Earlier works (2024) focus on systematic reviews of SERS biomedical applications, Raman spectroscopy artifacts, and endomicroscopic AI for tumor diagnostics.

Labs and Collaborations: Bocklitz collaborates with institutions like Universitätsklinikum Jena and researchers such as Jürgen Popp, Elena Corbetta, and Jhonatan Contreras. He leads a working group at Leibniz-IPHT, focusing on photonic data science for clinical and analytical applications.