Ayush Shrivastava
Papers
4
Total Citations
122
H-Index
3
About
Ayush Shrivastava is a leading researcher at the intersection of embodied AI, natural language processing, and human-robot interaction. His work focuses on enabling robots to understand and execute complex tasks through interactive dialogue, moving beyond simple instruction-following to dynamic, conversational collaboration. Shrivastava’s most significant contribution is the **TEACh** dataset (89+ citations), a landmark resource of over 3,000 human-human dialogues that allows agents to learn how to ask clarifying questions, resolve ambiguity, and recover from mistakes in real-time. This work directly addresses a critical gap in robotics: the need for machines that can converse naturally to complete tasks in human spaces. He further advanced the field with **VISITRON**, a multi-modal Transformer-based navigator that integrates visual semantics with interactive training, and tackled the practical challenge of **sim-to-real transfer** for Vision-and-Language Navigation (VLN), bridging the gap between simulated training and real-world deployment. By pioneering datasets and models that fuse language understanding with embodied action, Shrivastava is laying the groundwork for a new generation of truly interactive, helpful robots.
Research Focus
Key Achievements
Top Papers
- 1TEACh: Task-Driven Embodied Agents That Chat89 citations · 2022
- 2Sim-to-Real Transfer for Vision-and-Language Navigation21 citations · 2020
- 3VISITRON: Visual Semantics-Aligned Interactively Trained Object-Navigator10 citations · 2022
- 4TEACh: Task-driven Embodied Agents that Chat2 citations · 2021