Jaymit Surve
Papers
1
Total Citations
6
H-Index
1
About
Jaymit Surve is a rising researcher at the intersection of disaster robotics and artificial intelligence, with a primary focus on developing intelligent systems for post-earthquake search and rescue (SAR) missions. His most notable contribution is a novel survivor detection framework that integrates snake robots with deep learning-based object identification algorithms, enabling rapid and reliable localization of humans trapped under debris. This work, published in 2024 and already garnering 6 citations, addresses a critical bottleneck in emergency response by automating the detection process in environments too dangerous or inaccessible for human rescuers. By combining agile robotic locomotion with state-of-the-art computer vision, Surve’s approach promises to significantly reduce response times and improve survival rates in disaster scenarios. His research exemplifies a practical, high-impact application of deep learning in autonomous systems, bridging the gap between theoretical AI advances and real-world humanitarian needs. As an early-career scholar, Surve is establishing himself as a key voice in the growing field of robotic disaster response, with his work laying the groundwork for future innovations in autonomous emergency management.
Research Focus
Key Achievements
Top Papers
- 1