Synthetic Data Generation for Multimodal Perception call for proposals - Fall 2026

Supports synthetic training data for models that understand everyday human activity. Topics include scene-conditioned text-to-simulation motion and interaction, causally coherent audio-visual synthesis, hours-scale multimodal episode generation with persistent world state, and action-conditioned scenario synthesis using world models. Research should improve activity coverage, cross-modal consistency, episode duration and control over generated scenarios. Use the ARA proposal template; four pages excluding appendices are encouraged. Decisions are expected in February 2027.

Applications close on 4 November 2026 at 11:59pm Pacific Time.

Full-time faculty at an accredited academic institution or permanent researchers at a legally recognised non-governmental nonprofit. One primary-PI proposal per call period; co-PIs must also qualify. Amazon employment/contracting in the previous 12 months, specified household conflicts and Amazon cloud-procurement authority disqualify applicants. Government employees are excluded except university employees. Applicants must meet age-of-majority and programme rules.