M. Ghaffari (Mahdiyeh)

She is an analytical chemist/data scientist with a focus on chemical and biological data analysis. Her main research area is multidisciplinary, involving applications of hyperspectral imaging and chemometrics for the characterization of foods, polymers, and biological systems.
In 2017, she defended her Ph.D. in Analytical Chemistry/Chemometrics. During her Ph.D. she was a visiting researcher in the Laboratory of Infrared and Raman Spectrochemistry (LASIR), Villeneuve d'Ascq, France. The main focus of the visit was to evaluate the method of multi-excitation hyperspectral imaging (4D) by confocal microscopy combined with chemometrics to identify different components in the developing wheat grain based on their autofluorescence properties.
During her time as a post-doctoral researcher (2018) at the University of Lille, she solved several important issues dealing with big data analysis by proposing essential information concept. The introduced algorithm can deal with big data sets for storage/analysis.
These days as a post-doctoral researcher at Radboud University (2021) she is working on plastic sorting (mono/multilayer) using RGB and hyperspectral images to develop an efficient sorting for a green and sustainable environment.
Her academic interests focus on the development of new chemometrics methods to go further in the exploration of various spectral data sets, mainly in hyperspectral imaging.
In summary, her main research expertise includes:
- Signal unmixing
(MCR-ALS, NMF and etc.)
- Exploratory data analysis
(PCA and etc.)
- Image analysis
(RGB, 3D/4D HSI)
- Image preprocessing
- Remote sensing
- Multivariate statistical analysis
- Experimental design
- Pattern recognition
- Data management