Engineering notes on intelligent physical systems.

Topics covered

• Physical AI — The intersection of machine learning and real-world physical systems.
• Edge AI — Deploying intelligence where the mission happens, without cloud dependency.
• Multi-Agent Systems — Coordination and reasoning across distributed autonomous agents.
• Distributed Optimization — Planning and optimization under real-world constraints.
• Trustworthy AI — Confidence, risk awareness, calibration, and explainability.
• Computer Vision — Perception stacks for autonomous physical systems.
• Deep Learning — Neural architectures for physical intelligence.
• Mission Systems — Human-machine teaming and operator-aware autonomy.
• Engineering Intelligence — AI copilots and tools for engineering workflows.
• Drones / UAV — Quadrotor control, swarms, mission planning.