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Building machine learning that runs at the edge, onboard the vessel, where compute is limited and there is no shore connection to fall back on. With 13 years across edge AI and robotics, he specializes in real-time inference on constrained hardware, model optimization that fits demanding networks into a tight compute budget without sacrificing accuracy, and fault detection in systems that have to keep working when a sensor drops out. His work spans perception pipelines and multi-sensor synchronization, which is the same class of problem Co-Captain solves at scale across hundreds of onboard systems. At Pollentia, Ibrahim focuses on the intelligence layer, making onboard inference fast enough and reliable enough to support real-time decisions at sea.
