Research

Connecting Industrial Physical AI with resilient production networks.

My research spans two complementary levels of manufacturing intelligence: deployable Industrial Physical AI at the shop-floor level and Manufacturing-as-a-Service at the production-network level. I develop robotic automation and digital-twin systems, capability representations, and coordination methods for making distributed production resources measurable and discoverable, with the long-term goal of enabling their deployment on demand.

Research program connecting shop-floor Industrial Physical AI, cyber manufacturing systems, and resilient production networks
Foundation — Shop FloorIndustrial Physical AI, digital twins & robotic automation
Current Focus — Network LevelManufacturing capability representation, supplier identification & production allocation
Long-Term Vision — IntegrationResilient production networks with deployable automation
01

Manufacturing Capability Representation & Discovery

Methods that make the capabilities of manufacturing suppliers and robotic systems visible, comparable, and searchable.

Multimodal capability representationManufacturing knowledge graphsCAD and assembly retrievalCapability-aware search and ranking
02

Resilient Cyber Manufacturing Networks

Methods for discovering and coordinating distributed manufacturing resources during normal operations and disruptions while protecting sensitive capability information.

Supplier mesh networksResilient production allocationMulti-tier supplier coordinationPrivacy-preserving capability sharing
03

Industrial Physical AI Deployment & Qualification

Methods to translate industrial task requirements into measurable system capabilities, evaluate deployment evidence, and qualify automation systems for real-world use.

Task requirement-to-capability mappingMachine-tending performance evaluationDeployment evidence and qualificationDigital-twin-assisted validation