Rajesh Rajamani

Rajesh Rajamani is a Professor in the Department of Mechanical Engineering at the University of Minnesota, College of Science and Engineering. His research spans control systems, nonlinear dynamics, and applications in transportation and medical cyber-physical systems. He actively leads multiple funded research projects and contributes to interdisciplinary innovation.

His research interests lie at the intersection of control theory and real-world engineering applications. Key areas include nonlinear observer design, actuator and sensor systems, vehicle dynamics and safety, and medical cyber-physical systems. He applies these to diverse domains such as autonomous vehicles, smart infrastructure, combustion engines, and closed-loop drug delivery.

The recent publication trends reflect a strong focus on intelligent transportation (e.g., e-scooter safety, smart traffic signs), health monitoring using non-intrusive sensors, and control of pharmacological systems. His work combines deep theoretical control methods with practical implementation using real-time estimation, sensor fusion, and machine learning.

• Principal Investigator on multiple NSF and DOT-funded projects
• Expert commentator in media on transportation safety and automation
• Active collaborations with researchers in mechanical, biomedical, and electrical engineering
• Extensive publication record in top journals including IEEE Transactions and Mechanical Systems and Signal Processing

Rajamani has secured significant grant funding, including recent awards from the National Science Foundation and the Minnesota Department of Transportation, supporting projects on smart traffic systems, non-contact actuator sensing, and medical cyber-physical systems. These grants highlight sustained research impact and leadership.

He is involved in developing innovative technologies through university-industry partnerships and technology transfer initiatives, particularly in sensing and control for industrial and medical applications. His lab focuses on real-time estimation, feedback control, and system integration for safety-critical systems.