Atomfair Brainwave Hub: SciBase II / Computational Modeling and Optimization / AI-driven automation and adaptive systems engineering

AI-driven automation and adaptive systems engineering

Showing 13-24 of 26 articles

Bridging sim-to-real transfer gaps with adaptive physics-informed neural networks

Enhancing neutrino detection sensitivity using self-optimizing reactor monitoring systems

Implementing lights-out production for fault-tolerant quantum computing components

Via self-supervised curriculum learning to accelerate robotic skill acquisition in unstructured environments

Biomimetic proprioceptive feedback loops for adaptive control in soft robotics

Closed-loop deep brain stimulation systems adapting to synaptic time delays

Self-optimizing chemical reactors using unconventional chaotic mixing methodologies

Using affordance-based manipulation to improve robotic adaptability in unstructured environments

With collaborative robot cells for adaptive assembly of modular space habitats

Via multi-modal embodiment to improve human-robot collaboration in warehouses

Human-in-the-loop adaptation for biodegradable electronics in medical implants

Designing adaptive CNC toolpaths using 2D material heterostructures for precision machining