Rishabh Sachdeva
Papers
1
Total Citations
6
H-Index
1
About
Rishabh Sachdeva is a researcher advancing the frontier of grounded language learning, where machines connect linguistic meaning to real-world sensory data. His key research areas span multimodal machine learning, spoken language understanding, and human-robot interaction, with a particular focus on bridging the gap between speech, vision, and physical environments. Sachdeva’s most notable contribution is the creation of a spoken language dataset of descriptions for speech-based grounded language learning, a resource that enables models to learn language directly from natural, unscripted speech paired with visual and depth information. This work addresses critical challenges in sample efficiency and domain adaptation, making it foundational for deploying AI systems in real-world settings where labeled data is scarce. With over 6 citations on this seminal dataset, his research has already influenced subsequent work in multimodal grounding and embodied AI. By tackling the complex interplay of natural language processing, computer vision, and signal processing, Sachdeva is helping to build more intuitive, context-aware systems that can learn language as humans do—through interaction with the world.
Research Focus
Key Achievements
Top Papers
- 1