The creation of conscious AI systems represents one of the most fascinating technical challenges in artificial intelligence, bridging deep learning architectures with embodied cognition and computational models of consciousness. This interdisciplinary research field has evolved beyond philosophical debates into concrete implementation approaches with dual objectives. Researchers are developing computational frameworks inspired by biological consciousness to create AI systems with awareness capabilities, while simultaneously using these implementations to validate and refine our theoretical understanding of consciousness. This research program integrates cutting-edge approaches from neural networks to cognitive architectures, from reinforcement learning in embodied agents to neuro-symbolic integration, from developmental learning to predictive processing and bio-inspired computing. Recent advances in foundation models and large language models have opened new perspectives on emergent properties that might relate to conscious AI systems, while neuroscience findings continue to inform the computational requirements for conscious processing in AI systems. The seminar will present state-of-the-art architectural frameworks, computational models, and experimental implementations in conscious AI systems research. Through technical analysis of case studies, we will examine how different AI approaches address key aspects of consciousness such as self-modeling, phenomenal experience, and metacognition. The discussion will be particularly relevant for researchers working at the intersection of deep learning, cognitive architectures, and embodied AI.