Meenu Ajith

Meenu Ajith, Ph.D., currently serves as a Postdoctoral Research Associate at TReNDS Center, focusing on image generation and brain network identification through diffusion models, as well as calculating brain health indexes using variational autoencoders from fMRI data. Prior experience includes a role as a Research Assistant at the University of New Mexico School of Engineering, where Meenu Ajith developed multimodal deep learning algorithms for solar irradiance forecasting and conducted analyses of unsupervised segmentation algorithms for infrared images. Additionally, experience as a Teaching Assistant at The University of New Mexico involved instructing students in Probability Methods in Engineering and developing educational materials. Meenu Ajith holds a Ph.D. in Machine Learning, a Master's degree in Electrical Engineering, and a Bachelor of Technology in Electrical, Electronics and Communications Engineering, all from institutions within the University of New Mexico and Amrita School of Engineering.