Megha Srivastava

Papers

Total Citations

H-Index

About

Megha Srivastava is a robotics and human-robot interaction researcher whose work sits at the compelling intersection of shared autonomy, natural language processing, and personalized motor skills education. Her research addresses a fundamental challenge: how can AI systems intelligently collaborate with humans to enhance learning and performance in complex, highly individualized tasks? Her most notable contribution, "Language-Informed Latent Actions" (LILA), introduced an elegant framework enabling humans to guide robots through natural language commands combined with low-dimensional physical controls — advancing how machines interpret and respond to human intent in collaborative settings. Building on this foundation, her work on shared autonomy for proximal teaching explores AI-assisted instruction for specialized motor tasks such as high-performance racing, a domain where access to expert coaching is severely limited. Srivastava's broader research program, articulated in her work on robotics for personalized motor skills instruction, seeks to leverage robotics and AI to democratize high-quality coaching for activities ranging from driving to sports. Though early in her career with emerging citation counts across her publications, her research tackles genuinely important real-world problems, positioning her as a promising voice in adaptive human-robot collaboration and intelligent tutoring systems.