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CASE STUDY · YRI FELLOW

Making AI-planned drone teams fail safely, accepted at an IEEE conference

Language models are starting to plan missions for teams of drones, but a single bad plan can cascade across the whole fleet. Mohammed studied where validation checks should sit in that planning process, and how their placement affects both how well failures are contained and how much compute the system spends. His paired study gives a practical answer to a question that matters as AI takes on more control of physical systems.

FIELDAI & Autonomous Systems
RESULTFirst-author paper accepted at an IEEE conference
VENUEIEEE, 2026
BEFORE THE FELLOWSHIP

An 11th grader in Riyadh, Saudi Arabia with a strong interest in using AI to solve real problems, and no published research.

AFTER

First author of a study on validation and failure containment in AI-planned multi-drone missions, accepted at an IEEE conference.

THE LEDGER
01First-author paper accepted at an IEEE conference
02Studied failure containment in AI-planned multi-drone missions
03Measured the tradeoff between validation placement and compute cost
04Research from Saudi Arabia on safety in autonomous systems
NEXT CASE STUDYAdit Agarwal, First-author paper accepted at an IEEE conference

Every case study starts with one application.

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