Raj Rao Nadakuditi

Raj Rao Nadakuditi is an Associate Professor in the Department of Electrical Engineering and Computer Science at the University of Michigan, College of Engineering. His research bridges statistical signal processing, random matrix theory, and machine learning with applications in sensing, imaging, and communications.

Research Interests:

• Statistical Signal Processing and Learning
• Random Matrix Theory and Applications
• Signal Processing for Sensor Networks
• Light Transport Through Opaque Media
• Eigen-wavefront Imaging for Brain Circuit Mapping
• High-Dimensional Data Analysis

His recent work focuses on overcoming fundamental limits in imaging through highly scattering media, such as brain tissue, by leveraging eigen-wavefronts and algorithmic innovations. This has direct implications for the BRAIN Initiative and optical neuroimaging.

Publications Trends: His most recent articles reflect a strong emphasis on the application of random matrix theory to signal detection, covariance estimation, and imaging through random media. Key themes include eigenvalue analysis, high-dimensional statistics, spectral methods, and wavefront shaping for deep-tissue imaging.

Scientific Awards:

• DARPA Young Faculty Award (2014)
• ONR Young Investigator Program Award
• AFOSR Young Investigator Program Award

Advising and Grants: Prof. Nadakuditi has advised students in advanced signal processing and machine learning. His research is generously supported by the National Science Foundation, DARPA, Office of Naval Research, Air Force Office of Scientific Research, and Army Research Office’s MURI program. He has led projects on fundamental limits of imaging and robust signal processing in low-SNR environments.

Labs and Teams: He collaborates with Prof. Eric Michielssen on computational electromagnetics and is part of the broader EECS research community at the University of Michigan focused on autonomy, AI, and precision health. His group works on theoretical and applied aspects of sensing and imaging systems.