Research
I work on sparse signal processing applied to sensing and control. Sensing and control are essential and challenging in applications like autonomous driving, structural health monitoring, and communications, with millions of users and diverse sensors generating enormous data. For example, autonomous driving uses multiple radar, LiDAR, and cameras to learn the surroundings and steer the vehicles accordingly. My research goal is to provide domain-specific mathematical frameworks for such systems, using sparse signal processing to gather and analyze (sensor) data and design control strategies.
Some of my past and ongoing projects are on the following problems:
Sensing/Mapping
Environment-awareness for intelligent vehicles: Sensor fusion for automotive application using spatial sparsity and correlation
Image recovery: Sparse Bayesian dictionary learning algorithms for image denoising; one-bit compressed sensing for image compression
Structural health monitoring: Sparse anomaly mapping and sensor placement
Missing data: Sparse recovery and guarantees
Network Control
Controllability of network opinion using a manipulative agent with limited (sparse) influence on the network
Deep reinforcement algorithms for anomaly detection with sparse sensing
System analysis (observability, controllability, and stabilizability) with sparsity constraints
Wireless Communication
IRS-aided wireless channel estimation exploiting angular sparsity
Online Bayesian algorithms for wideband OFDM wireless channel estimation exploiting sparsity in the lag domain
Spectrum cartography algorithms for estimating the intensity map of a radio frequency map exploiting spatial sparsity
Project funding:
2024-2030: Atmospheric Turbulence Informed Machine Learning for Laser Satellite Communications (DAILSCOM)
NWO TTW Open Technology Programme with Rudolf Saathof (AE), Justin Dauwels, Sukanta Basu (CiTG)
2023-28: Signal Processing for Environment-Aware Radar (SPEAR)
Top consortium for Knowledge and Innovation (TKI) programme jointly with Nitin Myers and NXP semiconductors
2022-23: Statistical Inference and Control Design for Sparsity-constrained Linear Dynamical Systems"
IISc and TU Delft Collaborative Research Grant 2022