Bio
Marco Levantesi is a Ph.D. candidate at Magdeburg University, pioneering research in Large Agentic/Action Models (LAMs) to transform the landscape of AI-driven autonomous systems. His work focuses on the integration of Large Language Models (LLMs) within agent systems, pushing the boundaries of AI by bridging language models with agentic action-taking capabilities. Through his research, Marco is exploring this emerging field to establish LAMs as a core technology for intelligent, adaptive, and action-oriented applications, laying the foundation for his entire Ph.D. journey.
With a robust background in optimization techniques and genetic algorithms, Marco is particularly interested in enhancing problem-solving approaches through innovative LLM applications. His expertise extends across Python, TensorFlow, and PyTorch, where he has hands-on experience in developing predictive models and AI-driven solutions. Marco also holds certifications in AI development and machine learning from IBM and DeepLearning.AI, solidifying his technical foundation.
Outside of academia, Marco is a passionate drone enthusiast and enjoys photography and videography, blending his analytical and creative pursuits. He is enthusiastic about driving forward the new frontier of AI, where LLMs evolve into intelligent action-oriented systems, marking a significant step towards the future of autonomous, responsive agents.