Representative engineering systems spanning multimodal learning, autonomous reasoning, neuro-symbolic AI, and embedded systems. Full implementation details live on GitHub or each program's dedicated site.
A research program exploring thought as the next natural interface between humans and machines through non-invasive brain-computer interfaces.
A neuro-symbolic reasoning system investigating how intelligent systems can continuously acquire knowledge while remaining transparent, reproducible, and trustworthy.
An autonomous research agent that studies unfamiliar manufacturing domains, determines how sensor data should be processed, and produces AI-ready datasets and structured knowledge representations.
A deep learning system for large-scale wildlife audio classification using convolutional and transformer-based architectures, developed for the BirdCLEF challenge.
Reverse engineered VEX's analog communication protocol to enable commodity sensors to operate as native VEX peripherals, reducing hardware cost by approximately 90%.