Slobodan Sasic Wins Coblentz Society–Williams-Wright Award
Slobodan Sasic has won the 2017 Coblentz Society–Williams-Wright Award.
Slobodan Sasic has won the 2017 Coblentz Society–Williams-Wright Award. He was presented with the award on Wednesday, March 8, at Pittcon 2017 in Chicago, Illinois.
Sasic received his PhD from the University of Belgrade in Serbia. He worked at Kwansei-Gakuin University (Japan) on a variety of applications of vibrational spectroscopy, chemometrics, 2D correlation spectroscopy, and surface-enhanced Raman spectroscopy (SERS). He then worked at MIT on a method for non-invasive analysis of glucose based on Raman spectroscopy and multivariate calibration. He joined Pfizer (and later Vertex) next, where he specialized in vibrational spectroscopy–based chemical imaging of pharmaceuticals, and on using NIR spectroscopy for monitoring of the blending of pharmaceutical materials. Sasic currently works at SSCI/AMRI using vibrational spectroscopy, chemical imaging, X-ray powder diffraction, and chemometrics for the analysis of pharmaceutical solid forms.
Artificial Intelligence Accelerates Molecular Vibration Analysis, Study Finds
July 1st 2025A new review led by researchers from MIT and Oak Ridge National Laboratory outlines how artificial intelligence (AI) is transforming the study of molecular vibrations and phonons, making spectroscopic analysis faster, more accurate, and more accessible.
Machine Learning and Optical Spectroscopy Advance CNS Tumor Diagnostics
July 1st 2025A new review article highlights how researchers in Moscow are integrating machine learning with optical spectroscopy techniques to enhance real-time diagnosis and surgical precision in central nervous system tumor treatment.
New Ecofriendly Spectrophotometric Method Boosts Accuracy in Veterinary Drug Analysis
June 30th 2025A recent study showcases a cost-effective, ecofriendly UV spectrophotometric method enhanced with dimension reduction algorithms to accurately quantify veterinary drugs dexamethasone and prednisolone, offering a sustainable alternative to traditional analysis techniques.
