Rashmi Bhaskara

Papers

Total Citations

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About

Rashmi Bhaskara is a leading researcher at the intersection of robotics, artificial intelligence, and human-robot interaction, with a primary focus on enabling safe and socially-aware robot navigation through dense, unpredictable crowds. Her work addresses the fundamental challenge of predicting pedestrian trajectories, a critical component for robots operating in complex, uncontrolled environments. Bhaskara’s major contributions include the development of **SG-LSTM (Social Group LSTM)**, a novel deep learning architecture that models the influence of social groups on pedestrian movement, allowing robots to navigate more naturally and safely among people. This work has garnered significant attention, accumulating 8 citations since its publication in 2023. More recently, she introduced the **Flow-Guided Markov Neural Operator**, a cutting-edge framework for trajectory prediction that integrates environmental context, crowd density, and social norms, achieving 7 citations in 2024. Her research is notable for its practical impact, directly addressing the real-world deployment of personal robots beyond controlled industrial settings. Bhaskara’s innovative approaches are shaping the future of autonomous navigation, making her a rising star in the field of socially-compliant robotics.