This workshop will bring together researchers and practitioners to discuss recent advances in energy-efficient machine learning (ML). As ML models grow in scale and complexity, optimizing their energy consumption has become a critical research challenge. Topics will include model compression, quantization, hardware-aware neural architectures, sustainable AI frameworks, and energy-efficient inference techniques. The workshop will feature invited talks and ample time for networking.