Published proceedings

We present a reinforcement-learning framework for adaptive beamforming in dense low-power IoT deployments, reducing energy per delivered bit by 34% in simulation across three interference regimes.

We present a convolutional approach to fault detection in smart electrical grids, evaluated on three public datasets. The model detects line faults 40 percent faster than baseline methods while retaining precision above 0.95. This paper tests the Technology Fist publication pipeline end to end.