Research
Vision.
Where gemmological tradition meets computational science — our research programme advances the field through data-driven approaches to long-standing analytical challenges.
"To push the boundaries of gemmological diagnostics by integrating machine learning, advanced spectroscopy, and computational geology — creating tools and knowledge that benefit the entire community."
— G-ID Labs Research Vision Statement
Active Research Domains.
ML-Driven Origin Classification
Developing supervised and unsupervised learning models to classify gemstone origin based on trace element chemistry, spectral fingerprints, and inclusion patterns.
Automated Spectral Processing
Building pipelines for automated Raman and FTIR spectra processing — baseline correction, peak identification, and pattern matching against reference libraries.
Treatment Signature Discovery
Identifying novel spectroscopic markers for emerging treatment methods, including low-temperature heating, diffusion variants, and new filler materials.
Reference Database Expansion
Systematically growing our database of characterised reference specimens — the foundation for accurate origin classification and treatment detection.
Open to Partnership.
We believe the best research happens through collaboration. We actively engage with universities, other laboratories, and industry organisations to share knowledge, validate methods, and advance the field together.
Academic Partnerships
Joint research with Chiang Mai University STeP programme and Srinakharinwirot University
Industry Conferences
Active presenters at IGC, GIT Conference, BGJF seminars
Standards Bodies
Engagement with LMHC, CIBJO, and national accreditation bodies
Collaborate With Us.
Interested in research collaboration, data sharing, or joint publications? We welcome enquiries from academia and industry.
Contact Research Team