Compressive Sensing, Inference and learning with sparse/deep generative models, Statistical Signal Processing, Signal processing for communication and imaging, FMCW radar signal processing. 

[Jan 24] SERB Core Research Grant proposal on "Compressed Sensing-Based Ultra-High Resolution Automotive FMCW Radars"  has been accepted. 

Congratulations to Neha Singh for receiving the best poster presentation award in IndoML-2023 workshop, held in IIT Bombay,  for her poster titled "Robust Desketching of r-Separable Matrices". [snap]     

Our paper titled "Semi-NMF Regularization-Based Autoencoder Training for Hyperspectral Unmixing" has been accepted in 30th National Conference on Communications (NCC), 2024.

Expert lectures in Short Term Course on Advances in Communication and Signal Processing Techniques (ACST-2023) in NIT Kurukshetra on the topic "Sparsity-aware techniques for cross-interference cancellation in automotive FMCW Radars".

Our paper titled "Desketching of r-Separable Matrices from Compressive Linear Measurements" has been accepted in IEEE International Workshop on Machine Learning for Signal Processing Workshop (MLSP), 2023.

Our paper titled "Proximal Subgradient Descent Method for Cancelling Cross-Interference in FMCW Radars" has been accepted in IEEE Statistical Signal Processing Workshop (SSP), 2023.