Yao Zhang

Hello there! 👋 I’m Yao! I am currently pursuing a PhD at LMU Munich under the guidance of Prof. Dr. Volker Tresp. Prior to starting my PhD, I received my master’s degree in 2021 and my bachelor’s degree in 2019, both from LMU Munich, where I specialized in data mining under the guidance of Prof. Dr. Thomas Seidl.

My research interests center around Multimodal Learning and LLM Powered Autonomous Agents, with a strong focus on Continual Learning, Federated Learning, and PEFTs (Parameter-Efficient Fine-Tuning). In my work, I strive to develop methodologies that allow AI models to adapt to new tasks or datasets with minimal adjustments to their parameters, thereby enhancing their adaptability and efficiency while minimizing computational demands. This focus is driven by the goal of making AI more practical and sustainable. Through the integration of these key areas, I aim to contribute to the development of AI systems that are capable of sustained learning and adaptation, utilizing decentralized data in a manner that respects privacy concerns. My research is grounded in practical experimentation and the application of these concepts in real-world scenarios.

• Multimodal Learning (Continual Learning, Federated Learning, PEFTs)
• LLM Powered Autonomous Agents

Feel free to email me if you are interested in my research or want to chat more when dropping by Munich 🍻. I am always open to new opportunities and collaborations!