Rashmi Dutta Baruah

Indian Institute of Technology Guwahati, Lancaster University

Papers

Total Citations

H-Index

About

Rashmi Dutta Baruah is a researcher at the forefront of intelligent systems, specializing in human detection, autonomous scene recognition, and human-robot interaction. Her most cited work, "Ultrasonic sensor-based human detector using one-class classifiers" (2015, 22 citations), introduces a novel approach to human detection for applications like human-robot interaction and smart rooms. By applying one-class classifiers to ultrasonic sensor data, Baruah addresses a critical challenge: enabling reliable detection in resource-constrained environments where traditional methods may fail. This work has significant implications for unattended ground sensor systems and ambient intelligence. In "Automatic scene recognition for low-resource devices using evolving classifiers" (2011, 4 citations), she pioneers an on-line, self-learning approach to scene recognition, moving beyond off-line methods used in intelligent albums. Her earlier work, "RoboSapienNet: Towards Building A Social Network of Human Beings and Robots" (2007, 3 citations), envisions a heterogeneous network for symbiotic human-robot coexistence. Baruah’s contributions lie at the intersection of machine learning, sensor systems, and robotics, offering practical solutions for low-power, real-time applications. Her research continues to shape how machines perceive and interact with humans in dynamic environments.