Case File2024
Etihad Rail × NYUAD AI & Robotics Collaboration
NYU Abu Dhabi · CAIR with Etihad Rail
Challenge, contribution, and outcome
CHALLENGE
Etihad Rail needed a credible path to integrate AI and robotics into depot operations without treating university research as a one-off demo.
MY CONTRIBUTION
Led industry-facing translation of CAIR autonomous-systems research into a strategic collaboration with Etihad Rail — stakeholder engagement, lab visits, and depot inspection with Spot, which I operated to gather multimodal locomotive data for analysis and predictive maintenance, plus public demonstration of partnership intent.
OUTCOME
Established a public industry collaboration featuring depot Spot inspections that collect multimodal locomotive data for predictive maintenance analysis.
Narrative
Industry engagement with Etihad Rail to explore integrating artificial intelligence and robotics into rail operations — including depot inspection trials where I operated Boston Dynamics Spot to collect multimodal data around locomotives for downstream analysis and predictive maintenance — translating NYUAD research capabilities into collaborative experiments aimed at efficiency, sustainability, and next-generation rail transport standards.
System Record
- Domain
- DOMAINIndustry EngagementDOMAINAerial · Ground · Underwater RoboticsDOMAINPerception & Sensing
- Application
- APPRail TransportAPPIndustrial Inspection
- Laboratory
- Platforms
- PLATFORMBoston Dynamics Spot
- Methods
- METHODSensor Fusion
- Period
- 2024
Development & Validation
- Featured in Etihad Rail's public announcement of the collaboration with New York University Abu Dhabi on AI and robotics for rail operations.
- At the Etihad Rail depot I used Spot for locomotive inspection — collecting multimodal sensor data that feeds further analysis aimed at predictive maintenance rather than one-off visual checks alone.
- Aligns with CAIR's commercialization track: stakeholder engagement, lab and site visits, and industry-facing translation of autonomous systems research.
- Part of a broader external engagement model spanning infrastructure partners across the UAE transport and logistics ecosystem.
Credits & Collaborators
Nikolaos Giakoumidis
NYU Abu Dhabi · CAIR
Commercial Lead
Etihad Rail
Industry partner
Center for Artificial Intelligence and Robotics (CAIR)
NYU Abu Dhabi
Research partner
Anthony Tzes
NYU Abu Dhabi · CAIR
Principal Investigator
Evidence
Related
Related projects
Photos
DEPOT — MULTIMODAL LOCOMOTIVE SCAN
TRACKSIDE — DATA FOR PREDICTIVE MAINT.
YARD — SPOT MULTIMODAL COLLECTION