I am a research Master's student (MA.Sc) in Artificial Intelligence and Machine Learning at the School of Software and AI, Yunnan University, with a solid research background in the integration of deep learning and blockchain technology. My previous work has focused on applying deep learning techniques, with a specific emphasis on reinforcement learning , to optimize the performance of blockchain systems within IoT frameworks.
My research interests span a broad range of topics, including blockchain technology, reinforcement learning, time series forecasting, federated learning, and large language models (LLMs). I am increasingly interested in exploring how these technologies can be integrated into more general intelligent systems, particularly within the context of cyber-physical systems (CPS) and decentralized AI applications.
While my current research has primarily focused on blockchain, I aim to extend my future work beyond this domain, with a broader focus on enabling intelligent, secure, and efficient interactions between physical and computational components in complex systems. This will be achieved through the application of tools from machine learning, large language models (LLMs), and distributed computing.
For more information about my academic work, please refer to platforms such as [Researchgate] and [ORCID].