Dr Rajendhar Junjuri

The Laser spectroscopy area is vast, and I have expertise in working with different spectroscopic techniques, namely LIBS, Raman, NIR, and CARS. Also, I have specialized in exploring various Machine learning (ML)/ Deep learning (DL) / Chemometric algorithms to analyze spectroscopic data. 

During my Phd, I have demonstrated various applications like plastic waste sorting, biological tissue mapping, and standoff detection of explosives uasing LIBS. As an experimentalist, I designed Optical layouts from scratch to develop a low-cost standoff LIBS system. Further, as a Data analyst, I developed baseline correction and curve-fitting codes and explored various ML/DL algorithms such as Partial least squares-Discriminant analysis (PLS-DA), Support Vector Machine (SVM), Artificial neural networks (ANN), Principal component analysis (PCA), and Random forest (RF) for analyzing the spectroscopic data.

In the last two years, I worked on the CARS spectoscopy phase retreival methods using deep learning algorthims such as Convolutional neural networks (CNN), Long short-term memory (LSTM),  and Autoencoders, etc.

Major research areas:

LIBS • Vibrational Spectroscopy (Raman, CARS, NIR, FTIR, SRS)• Biopharmaceutical monitoring • Process analytical technology (PAT)