Gouranga Charan

Arizona State University, Symbiosis International University

Papers

Total Citations

H-Index

About

Gouranga Charan is a researcher focused on advancing continual learning and intelligent robotic systems. His primary contributions lie in developing algorithms that enable machine learning models to learn sequentially from data streams without catastrophic forgetting—a critical challenge for autonomous systems like self-driving vehicles, surveillance drones, and robotics. Charan’s most cited work, “Single-Net Continual Learning with Progressive Segmented Training” (2019), introduces a novel approach that allows a single neural network to adapt to new tasks while preserving previously acquired knowledge, achieving 13 citations and demonstrating significant impact in the continual learning community. He further refined this concept in a follow-up paper (2019, 4 citations), solidifying his expertise in single-network architectures for dynamic environments. Additionally, Charan has explored practical applications in surveillance through his work on an “Internet Regulated ESP32 Cam Robot” (2023, 5 citations), which integrates IoT and embedded systems for remote monitoring and public safety. His research bridges theoretical advances in continual learning with real-world deployment, offering scalable solutions for adaptive, lifelong learning systems. Charan’s work is particularly relevant for students and engineers developing robust AI for ever-changing environments.