Nishan Srishankar
Papers
4
Total Citations
34
H-Index
4
About
Nishan Srishankar is a robotics researcher whose work bridges the critical gap between autonomous systems and human trust. His primary research areas include explainable AI for autonomous driving, soft-body simulation, and federated learning for multi-robot systems. Srishankar’s most impactful contribution is his development of **Grounded Relational Inference**, a domain-knowledge-driven framework that makes autonomous vehicle decision-making transparent and understandable to human operators—a cornerstone for safe human-robot cooperation. This work has accumulated 18 citations across two publications, reflecting growing interest in explainable autonomy. He also created an **open-source framework for interactive soft-body simulations** (11 citations), enabling researchers to rapidly prototype and visualize deformable robots and environments for real-time training. In **Flow-FL**, Srishankar demonstrated how federated learning can enable spatio-temporal predictions across robot teams without centralizing sensitive data, a key advance for privacy-preserving multi-robot coordination. His work is notable for its practical, open-source ethos—lowering barriers to entry for complex robotics research while addressing fundamental challenges in transparency, simulation, and distributed learning.
Research Focus
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Top Papers
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